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198:: An experiment is designed to test the effects of a new pesticide on a specific patch of grass. The grass area contains a major elevation change and thus consists of two distinct regions â 'high elevation' and 'low elevation'. A treatment group (the new pesticide) and a placebo group are applied to both the high elevation and low elevation areas of grass. In this instance the researcher is blocking the elevation factor which may account for variability in the pesticide's application.
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224:. Both groups are then asked to use their shoes for a period of time, and then measure the degree of wear of the soles. This is a workable experimental design, but purely from the point of view of statistical accuracy (ignoring any other factors), a better design would be to give each person one regular sole and one new sole, randomly assigning the two types to the left and right shoe of each volunteer. Such a design is called a "randomized complete
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the different dosages. The blocked way to run this experiment, assuming you can convince manufacturing to let you put four experimental wafers in a furnace run, would be to put four wafers with different dosages in each of three furnace runs. The only randomization would be choosing which of the three wafers with dosage 1 would go into furnace run 1, and similarly for the wafers with dosages 2, 3 and 4.
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In the first example provided above, the sex of the patient would be a nuisance variable. For example, consider if the drug was a diet pill and the researchers wanted to test the effect of the diet pills on weight loss. The explanatory variable is the diet pill and the response variable is the amount
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are usually of the least importance (think of the fact that temperature of a reactor or the batch of raw materials is more important than the combination of the two â this is especially true when more (3, 4, ...) factors are present); thus it is preferable to confound this variability with the higher
97:
that are similar to one another in groups (blocks) based on one or more variables. These variables are chosen carefully to minimize the impact of their variability on the observed outcomes. There are different ways that blocking can be implemented, resulting in different confounding effects. However,
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A non-blocked way to run this experiment would be to run each of the twelve experimental wafers, in random order, one per furnace run. That would increase the experimental error of each resistivity measurement by the run-to-run furnace variability and make it more difficult to study the effects of
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An ideal way to run this experiment would be to run all the 4x3=12 wafers in the same furnace run. That would eliminate the nuisance furnace factor completely. However, regular production wafers have furnace priority, and only a few experimental wafers are allowed into any furnace run at the same
379:
Blocking is used to remove the effects of a few of the most important nuisance variables. Randomization is then used to reduce the contaminating effects of the remaining nuisance variables. For important nuisance variables, blocking will yield higher significance in the variables of interest than
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In our previous diet pills example, a blocking factor could be the sex of a patient. We could put individuals into one of two blocks (male or female). And within each of the two blocks, we can randomly assign the patients to either the diet pill (treatment) or placebo pill (control). By
261:
In the examples listed above, a nuisance variable is a variable that is not the primary focus of the study but can affect the outcomes of the experiment. They are considered potential sources of variability that, if not controlled or accounted for, may confound the interpretation between the
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You may choose to randomly assign experimental units to treatment conditions within each block which may help ensure that any unaccounted for variability is spread evenly across treatment groups. However, depending on how you assign treatments to blocks, you may obtain a different number of
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Suppose engineers at a semiconductor manufacturing facility want to test whether different wafer implant material dosages have a significant effect on resistivity measurements after a diffusion process taking place in a furnace. They have four different dosages they want to try and enough
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A nuisance factor is used as a blocking factor if every level of the primary factor occurs the same number of times with each level of the nuisance factor. The analysis of the experiment will focus on the effect of varying levels of the primary factor within each block of the experiment.
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When studying probability theory the blocks method consists of splitting a sample into blocks (groups) separated by smaller subblocks so that the blocks can be considered almost independent. The blocks method helps proving limit theorems in the case of dependent random variables.
445:, where a different effect gets confounded each time, the interaction effects are partially confounded instead of completely sacrificing one single effect. Replication enhances the reliability of results and allows for a more robust assessment of treatment effects.
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By using one of these methods to account for nuisance variables, researchers can enhance the internal validity of their experiments, ensuring that the effects observed are more likely attributable to the manipulated variables rather than extraneous influences.
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designs. Today, blocking still plays a pivotal role in experimental design, and in recent years, advancements in statistical software and computational capabilities have allowed researchers to explore more intricate blocking designs.
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To address nuisance variables, researchers can employ different methods such as blocking or randomization. Blocking involves grouping experimental units based on levels of the nuisance variable to control for its influence.
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the different methods share the same purpose: to control variability introduced by specific factors that could influence the outcome of an experiment. The roots of blocking originated from the statistician,
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of weight loss. Although the sex of the patient is not the main focus of the experimentâthe effect of the drug isâit is possible that the sex of the individual will affect the amount of weight lost.
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Blocking reduces unexplained variability. Its principle lies in the fact that variability which cannot be overcome (e.g. needing two batches of raw material to produce 1 container of a chemical) is
114:
The use of blocking in experimental design has an evolving history that spans multiple disciplines. The foundational concepts of blocking date back to the early 20th century with statisticians like
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122:(ANOVA) set the groundwork for grouping experimental units to control for extraneous variables. Blocking evolved over the years, leading to the formalization of randomized block designs and
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confounded effects. Therefore, the number of as well as which specific effects get confounded can be chosen which means that assigning treatments to blocks is superior over
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The nuisance factor they are concerned with is "furnace run" since it is known that each furnace run differs from the last and impacts many process parameters.
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204:: Suppose a process is invented that intends to make the soles of shoes last longer, and a plan is formed to conduct a field trial. Given a group of
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Bernstein S.N. (1926) Sur l'extension du thĂ©orĂšme limite du calcul des probabilitĂ©s aux sommes de quantitĂ©s dĂ©pendantes. Math. Annalen, v. 97, 1â59.
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There are consequences to partitioning a certain sized experiment into a certain number of blocks as the number of blocks determines the number of
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blocking on sex, this source of variability is controlled, therefore, leading to greater interpretation of how the diet pills affect weight loss.
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Carefully choose blocking factors based on their relevance to the study as well as their potential to confound the primary factors of interest.
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involves a series of steps to effectively control for extraneous variables and enhance the precision of treatment effect estimates.
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Ibragimov I.A. and Linnik Yu.V. (1971) Independent and stationary sequences of random variables. Wolters-Noordhoff, Groningen.
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An alternate way of summarizing the design trials would be to use a 4x3 matrix whose 4 rows are the levels of the treatment
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228:." This design will be more sensitive than the first, because each person is acting as his/her own control and thus the
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2171:
Addelman, S. (1970). "Variability of
Treatments and Experimental Units in the Design and Analysis of Experiments".
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or aliased with a(n) (higher/highest order) interaction to eliminate its influence on the end product. High order
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By extension, note that the trials for any K-factor randomized block design are simply the cell indices of a
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Novak S.Y. (2011) Extreme Value
Methods with Applications to Finance. Chapman & Hall/CRC Press, London.
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Identify potential factors that are not the primary focus of the study but could introduce variability.
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1949:(1983) Extremes and Related Properties of Random Sequences and Processes. New York: Springer Verlag.
1628:(GRBD) allow tests of blockâtreatment interaction, and has exactly one blocking factor like the RCBD.
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156:: An experiment is designed to test a new drug on patients. There are two levels of the treatment,
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1634:(and other rowâcolumn designs) have two blocking factors that are believed to have no interaction.
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2063:"Focus on Data: Statistical Design of Experiments and Sample Size Selection Using Power Analysis"
325:: The method was successfully applied in the theory of sums of dependent random variables and in
2630:"Some Consequences of randomization in a Generalization of the Balanced Incomplete Block Design"
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in groups (blocks) that are similar to one another. Typically, a blocking factor is a source of
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One useful way to look at a randomized block experiment is to consider it as a collection of
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Wilk, M. B. (1955). "The
Randomization Analysis of a Generalized Randomized Block Design".
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be the blocking factor furnace run. Then the experiment can be described as follows:
430:
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94:
2485:
Lentner, Marvin; Thomas Bishop (1993). "The
Generalized RCB Design (Chapter 6.13)".
1946:
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1981:
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helps distribute the effects of nuisance variables evenly across treatment groups.
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experimental wafers from the same lot to run three wafers at each of the dosages.
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2363:
Gates, C.E. (Nov 1995). "What Really Is
Experimental Error in Block Designs?".
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2445:. Vol. I: Introduction to Experimental Design (Second ed.). Wiley.
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1715:
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229:
217:
99:
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225:
192:. This reduces sources of variability and thus leads to greater precision.
177:
123:
2489:(Second ed.). Blacksburg, VA: Valley Book Company. pp. 225â226.
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experiments, each run within one of the blocks of the total experiment.
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1986:
1969:
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the assignment of the two kinds of soles. This type of experiment is a
1146:
The model for a randomized block design with one nuisance variable is
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5853:
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2468:. Vol. 2: Advanced Experimental Design (First ed.). Wiley.
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2027:
1970:"An approximation algorithm for blocking of an experimental design"
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2436:
2413:
7710:
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4911:
4612:
2529:
2515:(corrected reprint of the 1971 Wiley ed.). New York: Dover.
2511:
Constructions and
Combinatorial Problems in Design of Experiments
2399:(Corrected reprint of (1952) Wiley ed.). Robert E. Krieger.
257:
Nuisance variable (sex) effect on response variable (weight loss)
164:
1245:{\displaystyle Y_{ij}=\mu +T_{i}+B_{j}+\mathrm {random\ error} }
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3814:
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1852:
Berger, Paul D.; Maurer, Robert E.; Celli, Giovana B. (2018).
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and whose columns are the 3 levels of the blocking variable
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2753:
158:
313:
No blocking (left) vs blocking (right) experimental design
16:
Design of experiments to collect similar contexts together
1556:{\displaystyle {\overline {Y}}_{\cdot j}-{\overline {Y}}}
1444:{\displaystyle {\overline {Y}}_{i\cdot }-{\overline {Y}}}
286:
Blocking used for nuisance factors that can be controlled
2535:
Block
Designs: Analysis, Combinatorics and Applications
2126:
1740:"R. A. Fisher and the Design of Experiments, 1922-1926"
2331:
2308:
2009:
Pashley, Nicole E.; Miratrix, Luke W. (July 7, 2021).
1035:. The cells in the matrix have indices that match the
403:
341:
Without blocking: diet pills vs placebo on weight loss
306:
that is not of primary interest to the experimenter.
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Autoregressive conditional heteroskedasticity (ARCH)
4575:
Autoregressive conditional heteroskedasticity (ARCH)
2503:
2484:
2317:. Vol. I: Analysis. New York: Springer-Verlag.
1657:
184:
factor accounting for treatment variability between
2340:. Vol. II: Design. New York: Springer-Verlag.
2203:(1948). "The Validity of Comparative Experiments".
2142:(1969). "The Generalized Randomized Block Design".
2061:Ledolter, Johannes; Kardon, Randy H. (2020-07-09).
895:Before randomization, the design trials look like:
353:
With blocking: diet pills vs placebo on weight loss
6836:
4037:
2508:
2333:
2310:
1974:Journal of the Royal Statistical Society, Series B
1894:, New York, NY: Springer, 2008, pp. 447â448,
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1443:
1383:
1310:is the general location parameter (i.e., the mean)
1244:
750:
679:
631:
610:
589:
367:Block a few of the most important nuisance factors
2391:
1851:
1783:
1781:
357:
208:volunteers, one possible design would be to give
8050:
2278:: CS1 maint: bot: original URL status unknown (
2067:Investigative Ophthalmology & Visual Science
2015:Journal of Educational and Behavioral Statistics
795:
375:"Block what you can; randomize what you cannot."
6922:Multivariate adaptive regression splines (MARS)
4123:Multivariate adaptive regression splines (MARS)
2422:. Vol. I and II (Second ed.). Wiley.
2284:Pre-publication chapters are available on-line.
2173:Journal of the American Statistical Association
2011:"Block What You Can, Except When You Shouldn't"
2008:
1816:
1814:
1812:
1810:
1808:
1789:"5.3.3.3.3. Blocking of full factorial designs"
2127:National Institute of Standards and Technology
2060:
1778:
423:
395:
7803:
5477:
5004:
2678:
249:Nuisance variable effect on response variable
2570:
2287:
1805:
2056:
2054:
7810:
7796:
5522:
5484:
5470:
5011:
4997:
2723:
2685:
2671:
2261:. Archived from the original on 2011-03-06
736:= number of levels (settings) of factor 4
216:/2 of them shoes with the ordinary soles,
6135:
5018:
3336:
2645:
2094:
2026:
1985:
1593:{\displaystyle {\overline {Y}}_{\cdot j}}
1481:{\displaystyle {\overline {Y}}_{i\cdot }}
727:= number of levels (settings) of factor 3
718:= number of levels (settings) of factor 2
709:= number of levels (settings) of factor 1
69:Learn how and when to remove this message
7817:
2552:Shah, Kirti R.; Sinha, Bikas K. (1989).
2206:Journal of the Royal Statistical Society
2199:
2170:
2138:
2051:
1967:
1847:
1845:
1843:
1841:
1016:
768:= number of levels (settings) of factor
348:
336:
308:
252:
244:
212:/2 of them shoes with the new soles and
32:This article includes a list of general
2627:
2336:Block designs: A Randomization approach
2313:Block designs: A Randomization approach
441:By running a different design for each
8051:
7448:KaplanâMeier estimator (product limit)
4649:KaplanâMeier estimator (product limit)
2397:The Design and Analysis of Experiments
2241:
1892:The Concise Encyclopedia of Statistics
7791:
7521:
7088:
6835:
6134:
5904:
5521:
5465:
4992:
4722:
4289:
4036:
3335:
3105:
2722:
2666:
2634:The Annals of Mathematical Statistics
2362:
1838:
1733:
1731:
1319:is the effect for being in treatment
411:
240:
7758:
7458:Accelerated failure time (AFT) model
4959:
4659:Accelerated failure time (AFT) model
2598:
2581:Combinatorics of Experimental Design
1626:Generalized randomized block designs
321:The blocks method was introduced by
18:
7770:
7053:Analysis of variance (ANOVA, anova)
5905:
5360:Generalized randomized block design
4971:
4254:Analysis of variance (ANOVA, anova)
3106:
1822:"5.3.3.2. Randomized block designs"
1737:
1711:Dependent and independent variables
1691:Generalized randomized block design
404:Select appropriate blocking factors
264:independent and dependent variables
180:trial. The sex of the patient is a
13:
7148:CochranâMantelâHaenszel statistics
5774:Pearson product-moment correlation
4349:CochranâMantelâHaenszel statistics
2975:Pearson product-moment correlation
2466:Design and Analysis of Experiments
2443:Design and Analysis of Experiments
2420:Design and Analysis of Experiments
1728:
1619:
1238:
1235:
1232:
1229:
1226:
1220:
1217:
1214:
1211:
1208:
1205:
38:it lacks sufficient corresponding
14:
8070:
5411:Sequential probability ratio test
2332:CaliĆski T.; Kageyama S. (2003).
2309:CaliĆski T.; Kageyama S. (2000).
2248:Design of Comparative Experiments
1945:Leadbetter M.R., Lindgren G. and
1648:Hyper-Graeco-Latin square designs
1339:is the effect for being in block
383:
7769:
7757:
7745:
7732:
7731:
7522:
5434:
5336:Polynomial and rational modeling
4970:
4958:
4946:
4933:
4932:
4723:
2487:Experimental design and analysis
2291:Linear Algebra and Linear Models
2121: This article incorporates
2116:
1660:
23:
7407:Least-squares spectral analysis
4608:Least-squares spectral analysis
2132:
2002:
1961:
1696:Glossary of experimental design
1384:{\displaystyle {\overline {Y}}}
466:Randomized block designs (RBD)
298:, blocking is the arranging of
232:is more closely matched to the
102:, following his development of
7961:CremonaâRichmond configuration
6388:Mean-unbiased minimum-variance
5491:
5103:Replication versus subsampling
3589:Mean-unbiased minimum-variance
2692:
2251:. Cambridge University Press.
1952:
1939:
1930:
1921:
1880:
821:= 2 factors (1 primary factor
436:
358:Definition of blocking factors
1:
7701:Geographic information system
6917:Simultaneous equations models
4902:Geographic information system
4118:Simultaneous equations models
2294:(Second ed.). Springer.
1900:10.1007/978-0-387-32833-1_344
1721:
1391:= the average of all the data
1265:is any observation for which
796:Description of the experiment
8038:Kirkman's schoolgirl problem
7971:GrĂŒnbaumâRigby configuration
6884:Coefficient of determination
6495:Uniformly most powerful test
5330:Response surface methodology
5238:Analysis of variance (Anova)
4085:Coefficient of determination
3696:Uniformly most powerful test
1576:
1548:
1526:
1464:
1436:
1414:
1376:
1354:
775:
448:
222:completely randomized design
7:
7931:MöbiusâKantor configuration
7453:Proportional hazards models
7397:Spectral density estimation
7379:Vector autoregression (VAR)
6813:Maximum posterior estimator
6045:Randomized controlled trial
5400:Randomized controlled trial
4654:Proportional hazards models
4598:Spectral density estimation
4580:Vector autoregression (VAR)
4014:Maximum posterior estimator
3246:Randomized controlled trial
1653:
424:Assign treatments to blocks
396:Identify nuisance variables
147:
10:
8075:
8017:BruckâRyserâChowla theorem
7213:Multivariate distributions
5633:Average absolute deviation
4414:Multivariate distributions
2834:Average absolute deviation
332:
109:
8025:
8007:SzemerĂ©diâTrotter theorem
7989:
7911:
7846:
7825:
7727:
7681:
7618:
7571:
7534:
7530:
7517:
7489:
7471:
7438:
7429:
7387:
7334:
7295:
7244:
7235:
7201:Structural equation model
7156:
7113:
7109:
7084:
7043:
7009:
6963:
6930:
6892:
6859:
6855:
6831:
6771:
6680:
6599:
6563:
6554:
6537:Score/Lagrange multiplier
6522:
6475:
6420:
6346:
6337:
6147:
6143:
6130:
6089:
6063:
6015:
5970:
5952:Sample size determination
5917:
5913:
5900:
5804:
5759:
5733:
5715:
5671:
5623:
5543:
5534:
5530:
5517:
5499:
5419:
5288:
5183:
5116:
5026:
4928:
4882:
4819:
4772:
4735:
4731:
4718:
4690:
4672:
4639:
4630:
4588:
4535:
4496:
4445:
4436:
4402:Structural equation model
4357:
4314:
4310:
4285:
4244:
4210:
4164:
4131:
4093:
4060:
4056:
4032:
3972:
3881:
3800:
3764:
3755:
3738:Score/Lagrange multiplier
3723:
3676:
3621:
3547:
3538:
3348:
3344:
3331:
3290:
3264:
3216:
3171:
3153:Sample size determination
3118:
3114:
3101:
3005:
2960:
2934:
2916:
2872:
2824:
2744:
2735:
2731:
2718:
2700:
2554:Theory of Optimal Designs
2365:The American Statistician
2144:The American Statistician
2037:10.3102/10769986211027240
1968:Karmakar, Bikram (2022).
1888:"Randomized Block Design"
1864:10.1007/978-3-319-64583-4
1744:The American Statistician
1738:Box, Joan Fisher (1980).
388:Implementing blocking in
118:. His work in developing
7997:SylvesterâGallai theorem
7696:Environmental statistics
7218:Elliptical distributions
7011:Generalized linear model
6940:Simple linear regression
6710:HodgesâLehmann estimator
6167:Probability distribution
6076:Stochastic approximation
5638:Coefficient of variation
5386:Repeated measures design
5098:Restricted randomization
4897:Environmental statistics
4419:Elliptical distributions
4212:Generalized linear model
4141:Simple linear regression
3911:HodgesâLehmann estimator
3368:Probability distribution
3277:Stochastic approximation
2839:Coefficient of variation
2628:Zyskind, George (1963).
2533:; Padgett, L.V. (2005).
1638:Latin hypercube sampling
1141:
871:= 1 replication per cell
453:
8002:De BruijnâErdĆs theorem
7946:Desargues configuration
7356:Cross-correlation (XCF)
6964:Non-standard predictors
6398:LehmannâScheffĂ© theorem
6071:Adaptive clinical trial
4557:Cross-correlation (XCF)
4165:Non-standard predictors
3599:LehmannâScheffĂ© theorem
3272:Adaptive clinical trial
2647:10.1214/aoms/1177703889
751:{\displaystyle \vdots }
680:{\displaystyle \cdots }
632:{\displaystyle \vdots }
611:{\displaystyle \vdots }
590:{\displaystyle \vdots }
53:more precise citations.
7752:Mathematics portal
7573:Engineering statistics
7481:NelsonâAalen estimator
7058:Analysis of covariance
6945:Ordinary least squares
6869:Pearson product-moment
6273:Statistical functional
6184:Empirical distribution
6017:Controlled experiments
5746:Frequency distribution
5524:Descriptive statistics
5441:Mathematics portal
5203:Ordinary least squares
4953:Mathematics portal
4774:Engineering statistics
4682:NelsonâAalen estimator
4259:Analysis of covariance
4146:Ordinary least squares
4070:Pearson product-moment
3474:Statistical functional
3385:Empirical distribution
3218:Controlled experiments
2947:Frequency distribution
2725:Descriptive statistics
2123:public domain material
1706:Paired difference test
1594:
1557:
1482:
1445:
1385:
1304:is the blocking factor
1246:
828:and 1 blocking factor
807:be dosage "level" and
752:
681:
633:
612:
591:
354:
342:
314:
258:
250:
130:
8059:Design of experiments
8033:Design of experiments
7668:Population statistics
7610:System identification
7344:Autocorrelation (ACF)
7272:Exponential smoothing
7186:Discriminant analysis
7181:Canonical correlation
7045:Partition of variance
6907:Regression validation
6751:(JonckheereâTerpstra)
6650:Likelihood-ratio test
6339:Frequentist inference
6251:Locationâscale family
6172:Sampling distribution
6137:Statistical inference
6104:Cross-sectional study
6091:Observational studies
6050:Randomized experiment
5879:Stem-and-leaf display
5681:Central limit theorem
5038:Scientific experiment
5020:Design of experiments
4869:Population statistics
4811:System identification
4545:Autocorrelation (ACF)
4473:Exponential smoothing
4387:Discriminant analysis
4382:Canonical correlation
4246:Partition of variance
4108:Regression validation
3952:(JonckheereâTerpstra)
3851:Likelihood-ratio test
3540:Frequentist inference
3452:Locationâscale family
3373:Sampling distribution
3338:Statistical inference
3305:Cross-sectional study
3292:Observational studies
3251:Randomized experiment
3080:Stem-and-leaf display
2882:Central limit theorem
2288:Bapat, R. B. (2000).
1595:
1558:
1483:
1446:
1386:
1295:is the primary factor
1247:
1017:Matrix representation
859:= 3 levels of factor
844:= 4 levels of factor
753:
682:
634:
613:
592:
460:completely randomized
371:The general rule is:
352:
340:
312:
296:design of experiments
256:
248:
87:design of experiments
7966:Kummer configuration
7936:Pappus configuration
7819:Incidence structures
7591:Probabilistic design
7176:Principal components
7019:Exponential families
6971:Nonlinear regression
6950:General linear model
6912:Mixed effects models
6902:Errors and residuals
6879:Confounding variable
6781:Bayesian probability
6759:Van der Waerden test
6749:Ordered alternative
6514:Multiple comparisons
6393:RaoâBlackwellization
6356:Estimating equations
6312:Statistical distance
6030:Factorial experiment
5563:Arithmetic-Geometric
5312:Fractional factorial
4792:Probabilistic design
4377:Principal components
4220:Exponential families
4172:Nonlinear regression
4151:General linear model
4113:Mixed effects models
4103:Errors and residuals
4080:Confounding variable
3982:Bayesian probability
3960:Van der Waerden test
3950:Ordered alternative
3715:Multiple comparisons
3594:RaoâBlackwellization
3557:Estimating equations
3513:Statistical distance
3231:Factorial experiment
2764:Arithmetic-Geometric
2572:Street, Anne Penfold
2537:. World Scientific.
2531:Raghavarao, Damaraju
2505:Raghavarao, Damaraju
2079:10.1167/iovs.61.8.11
1686:Combinatorial design
1676:Algebraic statistics
1643:Graeco-Latin squares
1567:
1517:
1455:
1405:
1368:
1153:
1138:dimensional matrix.
1049:combinations above.
742:
671:
623:
602:
581:
327:extreme value theory
120:analysis of variance
93:is the arranging of
7976:Klein configuration
7956:SchlÀfli double six
7941:Hesse configuration
7921:Complete quadrangle
7663:Official statistics
7586:Methods engineering
7267:Seasonal adjustment
7035:Poisson regressions
6955:Bayesian regression
6894:Regression analysis
6874:Partial correlation
6846:Regression analysis
6445:Prediction interval
6440:Likelihood interval
6430:Confidence interval
6422:Interval estimation
6383:Unbiased estimators
6201:Model specification
6081:Up-and-down designs
5769:Partial correlation
5725:Index of dispersion
5643:Interquartile range
5446:Statistical outline
5406:Sequential analysis
5371:Graeco-Latin square
5280:Multiple comparison
5227:Hierarchical model:
4864:Official statistics
4787:Methods engineering
4468:Seasonal adjustment
4236:Poisson regressions
4156:Bayesian regression
4095:Regression analysis
4075:Partial correlation
4047:Regression analysis
3646:Prediction interval
3641:Likelihood interval
3631:Confidence interval
3623:Interval estimation
3584:Unbiased estimators
3402:Model specification
3282:Up-and-down designs
2970:Partial correlation
2926:Index of dispersion
2844:Interquartile range
2556:. Springer-Verlag.
2460:Hinkelmann, Klaus;
2437:Hinkelmann, Klaus;
2414:Hinkelmann, Klaus;
1855:Experimental Design
467:
390:experimental design
7951:Reye configuration
7683:Spatial statistics
7563:Medical statistics
7463:First hitting time
7417:Whittle likelihood
7068:Degrees of freedom
7063:Multivariate ANOVA
6996:Heteroscedasticity
6808:Bayesian estimator
6773:Bayesian inference
6622:KolmogorovâSmirnov
6507:Randomization test
6477:Testing hypotheses
6450:Tolerance interval
6361:Maximum likelihood
6256:Exponential family
6189:Density estimation
6149:Statistical theory
6109:Natural experiment
6055:Scientific control
5972:Survey methodology
5658:Standard deviation
5451:Statistical topics
5043:Statistical design
4884:Spatial statistics
4764:Medical statistics
4664:First hitting time
4618:Whittle likelihood
4269:Degrees of freedom
4264:Multivariate ANOVA
4197:Heteroscedasticity
4009:Bayesian estimator
3974:Bayesian inference
3823:KolmogorovâSmirnov
3708:Randomization test
3678:Testing hypotheses
3651:Tolerance interval
3562:Maximum likelihood
3457:Exponential family
3390:Density estimation
3350:Statistical theory
3310:Natural experiment
3256:Scientific control
3173:Survey methodology
2859:Standard deviation
2576:Street, Deborah J.
2179:(331): 1095â1108.
1987:10.1111/rssb.12545
1668:Mathematics portal
1590:
1553:
1478:
1441:
1381:
1242:
748:
677:
629:
608:
587:
474:Number of factors
465:
412:Define block sizes
355:
343:
315:
300:experimental units
259:
251:
241:Nuisance variables
168:, administered to
95:experimental units
8046:
8045:
7785:
7784:
7723:
7722:
7719:
7718:
7658:National accounts
7628:Actuarial science
7620:Social statistics
7513:
7512:
7509:
7508:
7505:
7504:
7440:Survival function
7425:
7424:
7287:Granger causality
7128:Contingency table
7103:Survival analysis
7080:
7079:
7076:
7075:
6932:Linear regression
6827:
6826:
6823:
6822:
6798:Credible interval
6767:
6766:
6550:
6549:
6366:Method of moments
6235:Parametric family
6196:Statistical model
6126:
6125:
6122:
6121:
6040:Random assignment
5962:Statistical power
5896:
5895:
5892:
5891:
5741:Contingency table
5711:
5710:
5578:Generalized/power
5459:
5458:
5346:Central composite
5244:Cochran's theorem
5198:Linear regression
5175:Nuisance variable
5088:Random assignment
5065:Experimental unit
4986:
4985:
4924:
4923:
4920:
4919:
4859:National accounts
4829:Actuarial science
4821:Social statistics
4714:
4713:
4710:
4709:
4706:
4705:
4641:Survival function
4626:
4625:
4488:Granger causality
4329:Contingency table
4304:Survival analysis
4281:
4280:
4277:
4276:
4133:Linear regression
4028:
4027:
4024:
4023:
3999:Credible interval
3968:
3967:
3751:
3750:
3567:Method of moments
3436:Parametric family
3397:Statistical model
3327:
3326:
3323:
3322:
3241:Random assignment
3163:Statistical power
3097:
3096:
3093:
3092:
2942:Contingency table
2912:
2911:
2779:Generalized/power
2584:. Oxford U. P. .
2475:978-0-471-55177-5
2462:Kempthorne, Oscar
2452:978-0-471-72756-9
2439:Kempthorne, Oscar
2429:978-0-470-38551-7
2416:Kempthorne, Oscar
2393:Kempthorne, Oscar
2301:978-0-387-98871-9
2258:978-0-521-68357-9
1909:978-0-387-32833-1
1873:978-3-319-64582-7
1600:= average of all
1579:
1551:
1529:
1488:= average of all
1467:
1439:
1417:
1379:
1225:
1132:
1131:
1014:
1013:
891:= 4 * 3 = 12 runs
697:
696:
431:random assignment
79:
78:
71:
8066:
7881:Projective plane
7833:Incidence matrix
7812:
7805:
7798:
7789:
7788:
7773:
7772:
7761:
7760:
7750:
7749:
7735:
7734:
7638:Crime statistics
7532:
7531:
7519:
7518:
7436:
7435:
7402:Fourier analysis
7389:Frequency domain
7369:
7316:
7282:Structural break
7242:
7241:
7191:Cluster analysis
7138:Log-linear model
7111:
7110:
7086:
7085:
7027:
7001:Homoscedasticity
6857:
6856:
6833:
6832:
6752:
6744:
6736:
6735:(KruskalâWallis)
6720:
6705:
6660:Cross validation
6645:
6627:AndersonâDarling
6574:
6561:
6560:
6532:Likelihood-ratio
6524:Parametric tests
6502:Permutation test
6485:1- & 2-tails
6376:Minimum distance
6348:Point estimation
6344:
6343:
6295:Optimal decision
6246:
6145:
6144:
6132:
6131:
6114:Quasi-experiment
6064:Adaptive designs
5915:
5914:
5902:
5901:
5779:Rank correlation
5541:
5540:
5532:
5531:
5519:
5518:
5486:
5479:
5472:
5463:
5462:
5439:
5438:
5376:Orthogonal array
5013:
5006:
4999:
4990:
4989:
4974:
4973:
4962:
4961:
4951:
4950:
4936:
4935:
4839:Crime statistics
4733:
4732:
4720:
4719:
4637:
4636:
4603:Fourier analysis
4590:Frequency domain
4570:
4517:
4483:Structural break
4443:
4442:
4392:Cluster analysis
4339:Log-linear model
4312:
4311:
4287:
4286:
4228:
4202:Homoscedasticity
4058:
4057:
4034:
4033:
3953:
3945:
3937:
3936:(KruskalâWallis)
3921:
3906:
3861:Cross validation
3846:
3828:AndersonâDarling
3775:
3762:
3761:
3733:Likelihood-ratio
3725:Parametric tests
3703:Permutation test
3686:1- & 2-tails
3577:Minimum distance
3549:Point estimation
3545:
3544:
3496:Optimal decision
3447:
3346:
3345:
3333:
3332:
3315:Quasi-experiment
3265:Adaptive designs
3116:
3115:
3103:
3102:
2980:Rank correlation
2742:
2741:
2733:
2732:
2720:
2719:
2687:
2680:
2673:
2664:
2663:
2659:
2649:
2640:(4): 1569â1581.
2624:
2595:
2567:
2548:
2526:
2514:
2500:
2479:
2456:
2433:
2410:
2388:
2359:
2339:
2328:
2316:
2305:
2283:
2277:
2269:
2267:
2266:
2238:
2196:
2167:
2120:
2119:
2109:
2108:
2098:
2058:
2049:
2048:
2030:
2006:
2000:
1999:
1989:
1980:(5): 1726â1750.
1965:
1959:
1956:
1950:
1943:
1937:
1934:
1928:
1925:
1919:
1918:
1917:
1916:
1884:
1878:
1877:
1849:
1836:
1835:
1833:
1832:
1826:www.itl.nist.gov
1818:
1803:
1802:
1800:
1799:
1793:www.itl.nist.gov
1785:
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1572:
1562:
1560:
1559:
1554:
1552:
1544:
1539:
1538:
1530:
1522:
1487:
1485:
1484:
1479:
1477:
1476:
1468:
1460:
1450:
1448:
1447:
1442:
1440:
1432:
1427:
1426:
1418:
1410:
1390:
1388:
1387:
1382:
1380:
1372:
1251:
1249:
1248:
1243:
1241:
1223:
1200:
1199:
1187:
1186:
1168:
1167:
1052:
1051:
898:
897:
757:
755:
754:
749:
686:
684:
683:
678:
638:
636:
635:
630:
617:
615:
614:
609:
596:
594:
593:
588:
468:
464:
116:Ronald A. Fisher
74:
67:
63:
60:
54:
49:this article by
40:inline citations
27:
26:
19:
8074:
8073:
8069:
8068:
8067:
8065:
8064:
8063:
8049:
8048:
8047:
8042:
8021:
7985:
7907:
7842:
7838:Incidence graph
7821:
7816:
7786:
7781:
7744:
7715:
7677:
7614:
7600:quality control
7567:
7549:Clinical trials
7526:
7501:
7485:
7473:Hazard function
7467:
7421:
7383:
7367:
7330:
7326:BreuschâGodfrey
7314:
7291:
7231:
7206:Factor analysis
7152:
7133:Graphical model
7105:
7072:
7039:
7025:
7005:
6959:
6926:
6888:
6851:
6850:
6819:
6763:
6750:
6742:
6734:
6718:
6703:
6682:Rank statistics
6676:
6655:Model selection
6643:
6601:Goodness of fit
6595:
6572:
6546:
6518:
6471:
6416:
6405:Median unbiased
6333:
6244:
6177:Order statistic
6139:
6118:
6085:
6059:
6011:
5966:
5909:
5907:Data collection
5888:
5800:
5755:
5729:
5707:
5667:
5619:
5536:Continuous data
5526:
5513:
5495:
5490:
5460:
5455:
5433:
5415:
5392:Crossover study
5383:
5381:Latin hypercube
5317:PlackettâBurman
5296:
5293:
5292:
5284:
5187:
5179:
5120:
5112:
5029:
5022:
5017:
4987:
4982:
4945:
4916:
4878:
4815:
4801:quality control
4768:
4750:Clinical trials
4727:
4702:
4686:
4674:Hazard function
4668:
4622:
4584:
4568:
4531:
4527:BreuschâGodfrey
4515:
4492:
4432:
4407:Factor analysis
4353:
4334:Graphical model
4306:
4273:
4240:
4226:
4206:
4160:
4127:
4089:
4052:
4051:
4020:
3964:
3951:
3943:
3935:
3919:
3904:
3883:Rank statistics
3877:
3856:Model selection
3844:
3802:Goodness of fit
3796:
3773:
3747:
3719:
3672:
3617:
3606:Median unbiased
3534:
3445:
3378:Order statistic
3340:
3319:
3286:
3260:
3212:
3167:
3110:
3108:Data collection
3089:
3001:
2956:
2930:
2908:
2868:
2820:
2737:Continuous data
2727:
2714:
2696:
2691:
2613:10.2307/2333423
2592:
2564:
2545:
2523:
2497:
2476:
2453:
2430:
2407:
2377:10.2307/2684574
2348:
2325:
2302:
2271:
2270:
2264:
2262:
2259:
2219:10.2307/2984159
2209:. A (General).
2185:10.2307/2284277
2156:10.2307/2681737
2135:
2117:
2113:
2112:
2059:
2052:
2007:
2003:
1966:
1962:
1957:
1953:
1944:
1940:
1935:
1931:
1926:
1922:
1914:
1912:
1910:
1886:
1885:
1881:
1874:
1850:
1839:
1830:
1828:
1820:
1819:
1806:
1797:
1795:
1787:
1786:
1779:
1756:10.2307/2682986
1736:
1729:
1724:
1666:
1659:
1656:
1622:
1620:Generalizations
1610:
1581:
1571:
1570:
1568:
1565:
1564:
1543:
1531:
1521:
1520:
1518:
1515:
1514:
1512:
1498:
1469:
1459:
1458:
1456:
1453:
1452:
1431:
1419:
1409:
1408:
1406:
1403:
1402:
1400:
1371:
1369:
1366:
1365:
1357:
1349:
1338:
1329:
1318:
1303:
1294:
1282:
1271:
1264:
1204:
1195:
1191:
1182:
1178:
1160:
1156:
1154:
1151:
1150:
1144:
1048:
1041:
1034:
1027:
1019:
914:
906:
890:
883:
865:
858:
850:
843:
834:
827:
813:
806:
798:
778:
766:
743:
740:
739:
735:
726:
717:
708:
692:
672:
669:
668:
666:
659:
624:
621:
620:
603:
600:
599:
582:
579:
578:
573:
566:
559:
552:
536:
529:
522:
506:
499:
480:Number of runs
471:Name of design
456:
451:
439:
426:
414:
406:
398:
386:
369:
360:
335:
288:
243:
234:treatment group
154:Male and female
150:
133:
112:
75:
64:
58:
55:
45:Please help to
44:
28:
24:
17:
12:
11:
5:
8072:
8062:
8061:
8044:
8043:
8041:
8040:
8035:
8029:
8027:
8023:
8022:
8020:
8019:
8014:
8012:Beck's theorem
8009:
8004:
7999:
7993:
7991:
7987:
7986:
7984:
7983:
7978:
7973:
7968:
7963:
7958:
7953:
7948:
7943:
7938:
7933:
7928:
7923:
7917:
7915:
7913:Configurations
7909:
7908:
7906:
7905:
7904:
7903:
7895:
7894:
7893:
7885:
7884:
7883:
7878:
7868:
7867:
7866:
7864:Steiner system
7861:
7850:
7848:
7844:
7843:
7841:
7840:
7835:
7829:
7827:
7826:Representation
7823:
7822:
7815:
7814:
7807:
7800:
7792:
7783:
7782:
7780:
7779:
7767:
7755:
7741:
7728:
7725:
7724:
7721:
7720:
7717:
7716:
7714:
7713:
7708:
7703:
7698:
7693:
7687:
7685:
7679:
7678:
7676:
7675:
7670:
7665:
7660:
7655:
7650:
7645:
7640:
7635:
7630:
7624:
7622:
7616:
7615:
7613:
7612:
7607:
7602:
7593:
7588:
7583:
7577:
7575:
7569:
7568:
7566:
7565:
7560:
7555:
7546:
7544:Bioinformatics
7540:
7538:
7528:
7527:
7515:
7514:
7511:
7510:
7507:
7506:
7503:
7502:
7500:
7499:
7493:
7491:
7487:
7486:
7484:
7483:
7477:
7475:
7469:
7468:
7466:
7465:
7460:
7455:
7450:
7444:
7442:
7433:
7427:
7426:
7423:
7422:
7420:
7419:
7414:
7409:
7404:
7399:
7393:
7391:
7385:
7384:
7382:
7381:
7376:
7371:
7363:
7358:
7353:
7352:
7351:
7349:partial (PACF)
7340:
7338:
7332:
7331:
7329:
7328:
7323:
7318:
7310:
7305:
7299:
7297:
7296:Specific tests
7293:
7292:
7290:
7289:
7284:
7279:
7274:
7269:
7264:
7259:
7254:
7248:
7246:
7239:
7233:
7232:
7230:
7229:
7228:
7227:
7226:
7225:
7210:
7209:
7208:
7198:
7196:Classification
7193:
7188:
7183:
7178:
7173:
7168:
7162:
7160:
7154:
7153:
7151:
7150:
7145:
7143:McNemar's test
7140:
7135:
7130:
7125:
7119:
7117:
7107:
7106:
7082:
7081:
7078:
7077:
7074:
7073:
7071:
7070:
7065:
7060:
7055:
7049:
7047:
7041:
7040:
7038:
7037:
7021:
7015:
7013:
7007:
7006:
7004:
7003:
6998:
6993:
6988:
6983:
6981:Semiparametric
6978:
6973:
6967:
6965:
6961:
6960:
6958:
6957:
6952:
6947:
6942:
6936:
6934:
6928:
6927:
6925:
6924:
6919:
6914:
6909:
6904:
6898:
6896:
6890:
6889:
6887:
6886:
6881:
6876:
6871:
6865:
6863:
6853:
6852:
6849:
6848:
6843:
6837:
6829:
6828:
6825:
6824:
6821:
6820:
6818:
6817:
6816:
6815:
6805:
6800:
6795:
6794:
6793:
6788:
6777:
6775:
6769:
6768:
6765:
6764:
6762:
6761:
6756:
6755:
6754:
6746:
6738:
6722:
6719:(MannâWhitney)
6714:
6713:
6712:
6699:
6698:
6697:
6686:
6684:
6678:
6677:
6675:
6674:
6673:
6672:
6667:
6662:
6652:
6647:
6644:(ShapiroâWilk)
6639:
6634:
6629:
6624:
6619:
6611:
6605:
6603:
6597:
6596:
6594:
6593:
6585:
6576:
6564:
6558:
6556:Specific tests
6552:
6551:
6548:
6547:
6545:
6544:
6539:
6534:
6528:
6526:
6520:
6519:
6517:
6516:
6511:
6510:
6509:
6499:
6498:
6497:
6487:
6481:
6479:
6473:
6472:
6470:
6469:
6468:
6467:
6462:
6452:
6447:
6442:
6437:
6432:
6426:
6424:
6418:
6417:
6415:
6414:
6409:
6408:
6407:
6402:
6401:
6400:
6395:
6380:
6379:
6378:
6373:
6368:
6363:
6352:
6350:
6341:
6335:
6334:
6332:
6331:
6326:
6321:
6320:
6319:
6309:
6304:
6303:
6302:
6292:
6291:
6290:
6285:
6280:
6270:
6265:
6260:
6259:
6258:
6253:
6248:
6232:
6231:
6230:
6225:
6220:
6210:
6209:
6208:
6203:
6193:
6192:
6191:
6181:
6180:
6179:
6169:
6164:
6159:
6153:
6151:
6141:
6140:
6128:
6127:
6124:
6123:
6120:
6119:
6117:
6116:
6111:
6106:
6101:
6095:
6093:
6087:
6086:
6084:
6083:
6078:
6073:
6067:
6065:
6061:
6060:
6058:
6057:
6052:
6047:
6042:
6037:
6032:
6027:
6021:
6019:
6013:
6012:
6010:
6009:
6007:Standard error
6004:
5999:
5994:
5993:
5992:
5987:
5976:
5974:
5968:
5967:
5965:
5964:
5959:
5954:
5949:
5944:
5939:
5937:Optimal design
5934:
5929:
5923:
5921:
5911:
5910:
5898:
5897:
5894:
5893:
5890:
5889:
5887:
5886:
5881:
5876:
5871:
5866:
5861:
5856:
5851:
5846:
5841:
5836:
5831:
5826:
5821:
5816:
5810:
5808:
5802:
5801:
5799:
5798:
5793:
5792:
5791:
5786:
5776:
5771:
5765:
5763:
5757:
5756:
5754:
5753:
5748:
5743:
5737:
5735:
5734:Summary tables
5731:
5730:
5728:
5727:
5721:
5719:
5713:
5712:
5709:
5708:
5706:
5705:
5704:
5703:
5698:
5693:
5683:
5677:
5675:
5669:
5668:
5666:
5665:
5660:
5655:
5650:
5645:
5640:
5635:
5629:
5627:
5621:
5620:
5618:
5617:
5612:
5607:
5606:
5605:
5600:
5595:
5590:
5585:
5580:
5575:
5570:
5568:Contraharmonic
5565:
5560:
5549:
5547:
5538:
5528:
5527:
5515:
5514:
5512:
5511:
5506:
5500:
5497:
5496:
5489:
5488:
5481:
5474:
5466:
5457:
5456:
5454:
5453:
5448:
5443:
5431:
5426:
5420:
5417:
5416:
5414:
5413:
5408:
5403:
5395:
5394:
5389:
5378:
5373:
5368:
5363:
5357:
5349:
5348:
5343:
5338:
5333:
5325:
5324:
5319:
5314:
5309:
5301:
5299:
5286:
5285:
5283:
5282:
5277:
5271:
5270:
5258:
5246:
5241:
5233:
5232:
5224:
5219:
5211:
5210:
5205:
5200:
5194:
5192:
5181:
5180:
5178:
5177:
5172:
5167:
5160:
5155:
5150:
5145:
5140:
5135:
5127:
5125:
5114:
5113:
5111:
5110:
5105:
5100:
5095:
5090:
5085:
5078:Optimal design
5073:
5072:
5067:
5062:
5050:
5045:
5040:
5034:
5032:
5024:
5023:
5016:
5015:
5008:
5001:
4993:
4984:
4983:
4981:
4980:
4968:
4956:
4942:
4929:
4926:
4925:
4922:
4921:
4918:
4917:
4915:
4914:
4909:
4904:
4899:
4894:
4888:
4886:
4880:
4879:
4877:
4876:
4871:
4866:
4861:
4856:
4851:
4846:
4841:
4836:
4831:
4825:
4823:
4817:
4816:
4814:
4813:
4808:
4803:
4794:
4789:
4784:
4778:
4776:
4770:
4769:
4767:
4766:
4761:
4756:
4747:
4745:Bioinformatics
4741:
4739:
4729:
4728:
4716:
4715:
4712:
4711:
4708:
4707:
4704:
4703:
4701:
4700:
4694:
4692:
4688:
4687:
4685:
4684:
4678:
4676:
4670:
4669:
4667:
4666:
4661:
4656:
4651:
4645:
4643:
4634:
4628:
4627:
4624:
4623:
4621:
4620:
4615:
4610:
4605:
4600:
4594:
4592:
4586:
4585:
4583:
4582:
4577:
4572:
4564:
4559:
4554:
4553:
4552:
4550:partial (PACF)
4541:
4539:
4533:
4532:
4530:
4529:
4524:
4519:
4511:
4506:
4500:
4498:
4497:Specific tests
4494:
4493:
4491:
4490:
4485:
4480:
4475:
4470:
4465:
4460:
4455:
4449:
4447:
4440:
4434:
4433:
4431:
4430:
4429:
4428:
4427:
4426:
4411:
4410:
4409:
4399:
4397:Classification
4394:
4389:
4384:
4379:
4374:
4369:
4363:
4361:
4355:
4354:
4352:
4351:
4346:
4344:McNemar's test
4341:
4336:
4331:
4326:
4320:
4318:
4308:
4307:
4283:
4282:
4279:
4278:
4275:
4274:
4272:
4271:
4266:
4261:
4256:
4250:
4248:
4242:
4241:
4239:
4238:
4222:
4216:
4214:
4208:
4207:
4205:
4204:
4199:
4194:
4189:
4184:
4182:Semiparametric
4179:
4174:
4168:
4166:
4162:
4161:
4159:
4158:
4153:
4148:
4143:
4137:
4135:
4129:
4128:
4126:
4125:
4120:
4115:
4110:
4105:
4099:
4097:
4091:
4090:
4088:
4087:
4082:
4077:
4072:
4066:
4064:
4054:
4053:
4050:
4049:
4044:
4038:
4030:
4029:
4026:
4025:
4022:
4021:
4019:
4018:
4017:
4016:
4006:
4001:
3996:
3995:
3994:
3989:
3978:
3976:
3970:
3969:
3966:
3965:
3963:
3962:
3957:
3956:
3955:
3947:
3939:
3923:
3920:(MannâWhitney)
3915:
3914:
3913:
3900:
3899:
3898:
3887:
3885:
3879:
3878:
3876:
3875:
3874:
3873:
3868:
3863:
3853:
3848:
3845:(ShapiroâWilk)
3840:
3835:
3830:
3825:
3820:
3812:
3806:
3804:
3798:
3797:
3795:
3794:
3786:
3777:
3765:
3759:
3757:Specific tests
3753:
3752:
3749:
3748:
3746:
3745:
3740:
3735:
3729:
3727:
3721:
3720:
3718:
3717:
3712:
3711:
3710:
3700:
3699:
3698:
3688:
3682:
3680:
3674:
3673:
3671:
3670:
3669:
3668:
3663:
3653:
3648:
3643:
3638:
3633:
3627:
3625:
3619:
3618:
3616:
3615:
3610:
3609:
3608:
3603:
3602:
3601:
3596:
3581:
3580:
3579:
3574:
3569:
3564:
3553:
3551:
3542:
3536:
3535:
3533:
3532:
3527:
3522:
3521:
3520:
3510:
3505:
3504:
3503:
3493:
3492:
3491:
3486:
3481:
3471:
3466:
3461:
3460:
3459:
3454:
3449:
3433:
3432:
3431:
3426:
3421:
3411:
3410:
3409:
3404:
3394:
3393:
3392:
3382:
3381:
3380:
3370:
3365:
3360:
3354:
3352:
3342:
3341:
3329:
3328:
3325:
3324:
3321:
3320:
3318:
3317:
3312:
3307:
3302:
3296:
3294:
3288:
3287:
3285:
3284:
3279:
3274:
3268:
3266:
3262:
3261:
3259:
3258:
3253:
3248:
3243:
3238:
3233:
3228:
3222:
3220:
3214:
3213:
3211:
3210:
3208:Standard error
3205:
3200:
3195:
3194:
3193:
3188:
3177:
3175:
3169:
3168:
3166:
3165:
3160:
3155:
3150:
3145:
3140:
3138:Optimal design
3135:
3130:
3124:
3122:
3112:
3111:
3099:
3098:
3095:
3094:
3091:
3090:
3088:
3087:
3082:
3077:
3072:
3067:
3062:
3057:
3052:
3047:
3042:
3037:
3032:
3027:
3022:
3017:
3011:
3009:
3003:
3002:
3000:
2999:
2994:
2993:
2992:
2987:
2977:
2972:
2966:
2964:
2958:
2957:
2955:
2954:
2949:
2944:
2938:
2936:
2935:Summary tables
2932:
2931:
2929:
2928:
2922:
2920:
2914:
2913:
2910:
2909:
2907:
2906:
2905:
2904:
2899:
2894:
2884:
2878:
2876:
2870:
2869:
2867:
2866:
2861:
2856:
2851:
2846:
2841:
2836:
2830:
2828:
2822:
2821:
2819:
2818:
2813:
2808:
2807:
2806:
2801:
2796:
2791:
2786:
2781:
2776:
2771:
2769:Contraharmonic
2766:
2761:
2750:
2748:
2739:
2729:
2728:
2716:
2715:
2713:
2712:
2707:
2701:
2698:
2697:
2690:
2689:
2682:
2675:
2667:
2661:
2660:
2625:
2607:(1â2): 70â79.
2596:
2590:
2568:
2562:
2549:
2543:
2527:
2521:
2501:
2495:
2482:
2481:
2480:
2474:
2457:
2451:
2428:
2411:
2405:
2389:
2371:(4): 362â363.
2360:
2346:
2329:
2323:
2306:
2300:
2285:
2257:
2239:
2213:(3): 181â211.
2201:Anscombe, F.J.
2197:
2168:
2134:
2131:
2130:
2129:
2111:
2110:
2050:
2001:
1960:
1951:
1938:
1929:
1920:
1908:
1879:
1872:
1837:
1804:
1777:
1726:
1725:
1723:
1720:
1719:
1718:
1713:
1708:
1703:
1701:Optimal design
1698:
1693:
1688:
1683:
1678:
1672:
1671:
1655:
1652:
1651:
1650:
1645:
1640:
1635:
1629:
1621:
1618:
1617:
1616:
1608:
1587:
1584:
1578:
1575:
1550:
1547:
1542:
1537:
1534:
1528:
1525:
1510:
1504:
1496:
1475:
1472:
1466:
1463:
1438:
1435:
1430:
1425:
1422:
1416:
1413:
1398:
1392:
1378:
1375:
1356:
1353:
1352:
1351:
1347:
1336:
1331:
1327:
1316:
1311:
1305:
1301:
1296:
1292:
1287:
1280:
1269:
1262:
1253:
1252:
1240:
1237:
1234:
1231:
1228:
1222:
1219:
1216:
1213:
1210:
1207:
1203:
1198:
1194:
1190:
1185:
1181:
1177:
1174:
1171:
1166:
1163:
1159:
1143:
1140:
1130:
1129:
1126:
1123:
1120:
1116:
1115:
1112:
1109:
1106:
1102:
1101:
1098:
1095:
1092:
1088:
1087:
1084:
1081:
1078:
1074:
1073:
1068:
1063:
1058:
1046:
1039:
1032:
1025:
1018:
1015:
1012:
1011:
1008:
1004:
1003:
1000:
996:
995:
992:
988:
987:
984:
980:
979:
976:
972:
971:
968:
964:
963:
960:
956:
955:
952:
948:
947:
944:
940:
939:
936:
932:
931:
928:
924:
923:
920:
916:
915:
912:
907:
904:
893:
892:
888:
881:
872:
866:
863:
856:
851:
848:
841:
836:
832:
825:
811:
804:
797:
794:
777:
774:
773:
772:
764:
760:
759:
758:
747:
733:
728:
724:
719:
715:
710:
706:
695:
694:
690:
676:
664:
657:
652:
647:
640:
639:
628:
618:
607:
597:
586:
575:
574:
571:
564:
557:
550:
545:
542:
538:
537:
534:
527:
520:
515:
512:
508:
507:
504:
497:
492:
489:
485:
484:
478:
472:
455:
452:
450:
447:
438:
435:
425:
422:
413:
410:
405:
402:
397:
394:
385:
384:Implementation
382:
377:
376:
368:
365:
359:
356:
334:
331:
294:theory of the
287:
284:
242:
239:
238:
237:
199:
193:
176:patients in a
149:
146:
132:
129:
111:
108:
85:theory of the
77:
76:
31:
29:
22:
15:
9:
6:
4:
3:
2:
8071:
8060:
8057:
8056:
8054:
8039:
8036:
8034:
8031:
8030:
8028:
8024:
8018:
8015:
8013:
8010:
8008:
8005:
8003:
8000:
7998:
7995:
7994:
7992:
7988:
7982:
7979:
7977:
7974:
7972:
7969:
7967:
7964:
7962:
7959:
7957:
7954:
7952:
7949:
7947:
7944:
7942:
7939:
7937:
7934:
7932:
7929:
7927:
7924:
7922:
7919:
7918:
7916:
7914:
7910:
7902:
7899:
7898:
7896:
7892:
7889:
7888:
7887:Graph theory
7886:
7882:
7879:
7877:
7874:
7873:
7872:
7869:
7865:
7862:
7860:
7857:
7856:
7855:
7854:Combinatorics
7852:
7851:
7849:
7845:
7839:
7836:
7834:
7831:
7830:
7828:
7824:
7820:
7813:
7808:
7806:
7801:
7799:
7794:
7793:
7790:
7778:
7777:
7768:
7766:
7765:
7756:
7754:
7753:
7748:
7742:
7740:
7739:
7730:
7729:
7726:
7712:
7709:
7707:
7706:Geostatistics
7704:
7702:
7699:
7697:
7694:
7692:
7689:
7688:
7686:
7684:
7680:
7674:
7673:Psychometrics
7671:
7669:
7666:
7664:
7661:
7659:
7656:
7654:
7651:
7649:
7646:
7644:
7641:
7639:
7636:
7634:
7631:
7629:
7626:
7625:
7623:
7621:
7617:
7611:
7608:
7606:
7603:
7601:
7597:
7594:
7592:
7589:
7587:
7584:
7582:
7579:
7578:
7576:
7574:
7570:
7564:
7561:
7559:
7556:
7554:
7550:
7547:
7545:
7542:
7541:
7539:
7537:
7536:Biostatistics
7533:
7529:
7525:
7520:
7516:
7498:
7497:Log-rank test
7495:
7494:
7492:
7488:
7482:
7479:
7478:
7476:
7474:
7470:
7464:
7461:
7459:
7456:
7454:
7451:
7449:
7446:
7445:
7443:
7441:
7437:
7434:
7432:
7428:
7418:
7415:
7413:
7410:
7408:
7405:
7403:
7400:
7398:
7395:
7394:
7392:
7390:
7386:
7380:
7377:
7375:
7372:
7370:
7368:(BoxâJenkins)
7364:
7362:
7359:
7357:
7354:
7350:
7347:
7346:
7345:
7342:
7341:
7339:
7337:
7333:
7327:
7324:
7322:
7321:DurbinâWatson
7319:
7317:
7311:
7309:
7306:
7304:
7303:DickeyâFuller
7301:
7300:
7298:
7294:
7288:
7285:
7283:
7280:
7278:
7277:Cointegration
7275:
7273:
7270:
7268:
7265:
7263:
7260:
7258:
7255:
7253:
7252:Decomposition
7250:
7249:
7247:
7243:
7240:
7238:
7234:
7224:
7221:
7220:
7219:
7216:
7215:
7214:
7211:
7207:
7204:
7203:
7202:
7199:
7197:
7194:
7192:
7189:
7187:
7184:
7182:
7179:
7177:
7174:
7172:
7169:
7167:
7164:
7163:
7161:
7159:
7155:
7149:
7146:
7144:
7141:
7139:
7136:
7134:
7131:
7129:
7126:
7124:
7123:Cohen's kappa
7121:
7120:
7118:
7116:
7112:
7108:
7104:
7100:
7096:
7092:
7087:
7083:
7069:
7066:
7064:
7061:
7059:
7056:
7054:
7051:
7050:
7048:
7046:
7042:
7036:
7032:
7028:
7022:
7020:
7017:
7016:
7014:
7012:
7008:
7002:
6999:
6997:
6994:
6992:
6989:
6987:
6984:
6982:
6979:
6977:
6976:Nonparametric
6974:
6972:
6969:
6968:
6966:
6962:
6956:
6953:
6951:
6948:
6946:
6943:
6941:
6938:
6937:
6935:
6933:
6929:
6923:
6920:
6918:
6915:
6913:
6910:
6908:
6905:
6903:
6900:
6899:
6897:
6895:
6891:
6885:
6882:
6880:
6877:
6875:
6872:
6870:
6867:
6866:
6864:
6862:
6858:
6854:
6847:
6844:
6842:
6839:
6838:
6834:
6830:
6814:
6811:
6810:
6809:
6806:
6804:
6801:
6799:
6796:
6792:
6789:
6787:
6784:
6783:
6782:
6779:
6778:
6776:
6774:
6770:
6760:
6757:
6753:
6747:
6745:
6739:
6737:
6731:
6730:
6729:
6726:
6725:Nonparametric
6723:
6721:
6715:
6711:
6708:
6707:
6706:
6700:
6696:
6695:Sample median
6693:
6692:
6691:
6688:
6687:
6685:
6683:
6679:
6671:
6668:
6666:
6663:
6661:
6658:
6657:
6656:
6653:
6651:
6648:
6646:
6640:
6638:
6635:
6633:
6630:
6628:
6625:
6623:
6620:
6618:
6616:
6612:
6610:
6607:
6606:
6604:
6602:
6598:
6592:
6590:
6586:
6584:
6582:
6577:
6575:
6570:
6566:
6565:
6562:
6559:
6557:
6553:
6543:
6540:
6538:
6535:
6533:
6530:
6529:
6527:
6525:
6521:
6515:
6512:
6508:
6505:
6504:
6503:
6500:
6496:
6493:
6492:
6491:
6488:
6486:
6483:
6482:
6480:
6478:
6474:
6466:
6463:
6461:
6458:
6457:
6456:
6453:
6451:
6448:
6446:
6443:
6441:
6438:
6436:
6433:
6431:
6428:
6427:
6425:
6423:
6419:
6413:
6410:
6406:
6403:
6399:
6396:
6394:
6391:
6390:
6389:
6386:
6385:
6384:
6381:
6377:
6374:
6372:
6369:
6367:
6364:
6362:
6359:
6358:
6357:
6354:
6353:
6351:
6349:
6345:
6342:
6340:
6336:
6330:
6327:
6325:
6322:
6318:
6315:
6314:
6313:
6310:
6308:
6305:
6301:
6300:loss function
6298:
6297:
6296:
6293:
6289:
6286:
6284:
6281:
6279:
6276:
6275:
6274:
6271:
6269:
6266:
6264:
6261:
6257:
6254:
6252:
6249:
6247:
6241:
6238:
6237:
6236:
6233:
6229:
6226:
6224:
6221:
6219:
6216:
6215:
6214:
6211:
6207:
6204:
6202:
6199:
6198:
6197:
6194:
6190:
6187:
6186:
6185:
6182:
6178:
6175:
6174:
6173:
6170:
6168:
6165:
6163:
6160:
6158:
6155:
6154:
6152:
6150:
6146:
6142:
6138:
6133:
6129:
6115:
6112:
6110:
6107:
6105:
6102:
6100:
6097:
6096:
6094:
6092:
6088:
6082:
6079:
6077:
6074:
6072:
6069:
6068:
6066:
6062:
6056:
6053:
6051:
6048:
6046:
6043:
6041:
6038:
6036:
6033:
6031:
6028:
6026:
6023:
6022:
6020:
6018:
6014:
6008:
6005:
6003:
6002:Questionnaire
6000:
5998:
5995:
5991:
5988:
5986:
5983:
5982:
5981:
5978:
5977:
5975:
5973:
5969:
5963:
5960:
5958:
5955:
5953:
5950:
5948:
5945:
5943:
5940:
5938:
5935:
5933:
5930:
5928:
5925:
5924:
5922:
5920:
5916:
5912:
5908:
5903:
5899:
5885:
5882:
5880:
5877:
5875:
5872:
5870:
5867:
5865:
5862:
5860:
5857:
5855:
5852:
5850:
5847:
5845:
5842:
5840:
5837:
5835:
5832:
5830:
5829:Control chart
5827:
5825:
5822:
5820:
5817:
5815:
5812:
5811:
5809:
5807:
5803:
5797:
5794:
5790:
5787:
5785:
5782:
5781:
5780:
5777:
5775:
5772:
5770:
5767:
5766:
5764:
5762:
5758:
5752:
5749:
5747:
5744:
5742:
5739:
5738:
5736:
5732:
5726:
5723:
5722:
5720:
5718:
5714:
5702:
5699:
5697:
5694:
5692:
5689:
5688:
5687:
5684:
5682:
5679:
5678:
5676:
5674:
5670:
5664:
5661:
5659:
5656:
5654:
5651:
5649:
5646:
5644:
5641:
5639:
5636:
5634:
5631:
5630:
5628:
5626:
5622:
5616:
5613:
5611:
5608:
5604:
5601:
5599:
5596:
5594:
5591:
5589:
5586:
5584:
5581:
5579:
5576:
5574:
5571:
5569:
5566:
5564:
5561:
5559:
5556:
5555:
5554:
5551:
5550:
5548:
5546:
5542:
5539:
5537:
5533:
5529:
5525:
5520:
5516:
5510:
5507:
5505:
5502:
5501:
5498:
5494:
5487:
5482:
5480:
5475:
5473:
5468:
5467:
5464:
5452:
5449:
5447:
5444:
5442:
5437:
5432:
5430:
5427:
5425:
5422:
5421:
5418:
5412:
5409:
5407:
5404:
5402:
5401:
5397:
5396:
5393:
5390:
5388:
5387:
5382:
5379:
5377:
5374:
5372:
5369:
5367:
5364:
5361:
5358:
5356:
5355:
5351:
5350:
5347:
5344:
5342:
5339:
5337:
5334:
5332:
5331:
5327:
5326:
5323:
5320:
5318:
5315:
5313:
5310:
5308:
5307:
5303:
5302:
5300:
5298:
5291:
5287:
5281:
5278:
5276:
5275:Compare means
5273:
5272:
5269:
5267:
5263:
5259:
5257:
5255:
5251:
5247:
5245:
5242:
5240:
5239:
5235:
5234:
5231:
5228:
5225:
5223:
5220:
5218:
5217:
5216:Random effect
5213:
5212:
5209:
5206:
5204:
5201:
5199:
5196:
5195:
5193:
5191:
5186:
5182:
5176:
5173:
5171:
5168:
5166:
5165:
5161:
5159:
5158:Orthogonality
5156:
5154:
5151:
5149:
5146:
5144:
5141:
5139:
5136:
5134:
5133:
5129:
5128:
5126:
5124:
5119:
5115:
5109:
5106:
5104:
5101:
5099:
5096:
5094:
5093:Randomization
5091:
5089:
5086:
5084:
5080:
5079:
5075:
5074:
5071:
5068:
5066:
5063:
5061:
5058:
5054:
5051:
5049:
5046:
5044:
5041:
5039:
5036:
5035:
5033:
5031:
5025:
5021:
5014:
5009:
5007:
5002:
5000:
4995:
4994:
4991:
4979:
4978:
4969:
4967:
4966:
4957:
4955:
4954:
4949:
4943:
4941:
4940:
4931:
4930:
4927:
4913:
4910:
4908:
4907:Geostatistics
4905:
4903:
4900:
4898:
4895:
4893:
4890:
4889:
4887:
4885:
4881:
4875:
4874:Psychometrics
4872:
4870:
4867:
4865:
4862:
4860:
4857:
4855:
4852:
4850:
4847:
4845:
4842:
4840:
4837:
4835:
4832:
4830:
4827:
4826:
4824:
4822:
4818:
4812:
4809:
4807:
4804:
4802:
4798:
4795:
4793:
4790:
4788:
4785:
4783:
4780:
4779:
4777:
4775:
4771:
4765:
4762:
4760:
4757:
4755:
4751:
4748:
4746:
4743:
4742:
4740:
4738:
4737:Biostatistics
4734:
4730:
4726:
4721:
4717:
4699:
4698:Log-rank test
4696:
4695:
4693:
4689:
4683:
4680:
4679:
4677:
4675:
4671:
4665:
4662:
4660:
4657:
4655:
4652:
4650:
4647:
4646:
4644:
4642:
4638:
4635:
4633:
4629:
4619:
4616:
4614:
4611:
4609:
4606:
4604:
4601:
4599:
4596:
4595:
4593:
4591:
4587:
4581:
4578:
4576:
4573:
4571:
4569:(BoxâJenkins)
4565:
4563:
4560:
4558:
4555:
4551:
4548:
4547:
4546:
4543:
4542:
4540:
4538:
4534:
4528:
4525:
4523:
4522:DurbinâWatson
4520:
4518:
4512:
4510:
4507:
4505:
4504:DickeyâFuller
4502:
4501:
4499:
4495:
4489:
4486:
4484:
4481:
4479:
4478:Cointegration
4476:
4474:
4471:
4469:
4466:
4464:
4461:
4459:
4456:
4454:
4453:Decomposition
4451:
4450:
4448:
4444:
4441:
4439:
4435:
4425:
4422:
4421:
4420:
4417:
4416:
4415:
4412:
4408:
4405:
4404:
4403:
4400:
4398:
4395:
4393:
4390:
4388:
4385:
4383:
4380:
4378:
4375:
4373:
4370:
4368:
4365:
4364:
4362:
4360:
4356:
4350:
4347:
4345:
4342:
4340:
4337:
4335:
4332:
4330:
4327:
4325:
4324:Cohen's kappa
4322:
4321:
4319:
4317:
4313:
4309:
4305:
4301:
4297:
4293:
4288:
4284:
4270:
4267:
4265:
4262:
4260:
4257:
4255:
4252:
4251:
4249:
4247:
4243:
4237:
4233:
4229:
4223:
4221:
4218:
4217:
4215:
4213:
4209:
4203:
4200:
4198:
4195:
4193:
4190:
4188:
4185:
4183:
4180:
4178:
4177:Nonparametric
4175:
4173:
4170:
4169:
4167:
4163:
4157:
4154:
4152:
4149:
4147:
4144:
4142:
4139:
4138:
4136:
4134:
4130:
4124:
4121:
4119:
4116:
4114:
4111:
4109:
4106:
4104:
4101:
4100:
4098:
4096:
4092:
4086:
4083:
4081:
4078:
4076:
4073:
4071:
4068:
4067:
4065:
4063:
4059:
4055:
4048:
4045:
4043:
4040:
4039:
4035:
4031:
4015:
4012:
4011:
4010:
4007:
4005:
4002:
4000:
3997:
3993:
3990:
3988:
3985:
3984:
3983:
3980:
3979:
3977:
3975:
3971:
3961:
3958:
3954:
3948:
3946:
3940:
3938:
3932:
3931:
3930:
3927:
3926:Nonparametric
3924:
3922:
3916:
3912:
3909:
3908:
3907:
3901:
3897:
3896:Sample median
3894:
3893:
3892:
3889:
3888:
3886:
3884:
3880:
3872:
3869:
3867:
3864:
3862:
3859:
3858:
3857:
3854:
3852:
3849:
3847:
3841:
3839:
3836:
3834:
3831:
3829:
3826:
3824:
3821:
3819:
3817:
3813:
3811:
3808:
3807:
3805:
3803:
3799:
3793:
3791:
3787:
3785:
3783:
3778:
3776:
3771:
3767:
3766:
3763:
3760:
3758:
3754:
3744:
3741:
3739:
3736:
3734:
3731:
3730:
3728:
3726:
3722:
3716:
3713:
3709:
3706:
3705:
3704:
3701:
3697:
3694:
3693:
3692:
3689:
3687:
3684:
3683:
3681:
3679:
3675:
3667:
3664:
3662:
3659:
3658:
3657:
3654:
3652:
3649:
3647:
3644:
3642:
3639:
3637:
3634:
3632:
3629:
3628:
3626:
3624:
3620:
3614:
3611:
3607:
3604:
3600:
3597:
3595:
3592:
3591:
3590:
3587:
3586:
3585:
3582:
3578:
3575:
3573:
3570:
3568:
3565:
3563:
3560:
3559:
3558:
3555:
3554:
3552:
3550:
3546:
3543:
3541:
3537:
3531:
3528:
3526:
3523:
3519:
3516:
3515:
3514:
3511:
3509:
3506:
3502:
3501:loss function
3499:
3498:
3497:
3494:
3490:
3487:
3485:
3482:
3480:
3477:
3476:
3475:
3472:
3470:
3467:
3465:
3462:
3458:
3455:
3453:
3450:
3448:
3442:
3439:
3438:
3437:
3434:
3430:
3427:
3425:
3422:
3420:
3417:
3416:
3415:
3412:
3408:
3405:
3403:
3400:
3399:
3398:
3395:
3391:
3388:
3387:
3386:
3383:
3379:
3376:
3375:
3374:
3371:
3369:
3366:
3364:
3361:
3359:
3356:
3355:
3353:
3351:
3347:
3343:
3339:
3334:
3330:
3316:
3313:
3311:
3308:
3306:
3303:
3301:
3298:
3297:
3295:
3293:
3289:
3283:
3280:
3278:
3275:
3273:
3270:
3269:
3267:
3263:
3257:
3254:
3252:
3249:
3247:
3244:
3242:
3239:
3237:
3234:
3232:
3229:
3227:
3224:
3223:
3221:
3219:
3215:
3209:
3206:
3204:
3203:Questionnaire
3201:
3199:
3196:
3192:
3189:
3187:
3184:
3183:
3182:
3179:
3178:
3176:
3174:
3170:
3164:
3161:
3159:
3156:
3154:
3151:
3149:
3146:
3144:
3141:
3139:
3136:
3134:
3131:
3129:
3126:
3125:
3123:
3121:
3117:
3113:
3109:
3104:
3100:
3086:
3083:
3081:
3078:
3076:
3073:
3071:
3068:
3066:
3063:
3061:
3058:
3056:
3053:
3051:
3048:
3046:
3043:
3041:
3038:
3036:
3033:
3031:
3030:Control chart
3028:
3026:
3023:
3021:
3018:
3016:
3013:
3012:
3010:
3008:
3004:
2998:
2995:
2991:
2988:
2986:
2983:
2982:
2981:
2978:
2976:
2973:
2971:
2968:
2967:
2965:
2963:
2959:
2953:
2950:
2948:
2945:
2943:
2940:
2939:
2937:
2933:
2927:
2924:
2923:
2921:
2919:
2915:
2903:
2900:
2898:
2895:
2893:
2890:
2889:
2888:
2885:
2883:
2880:
2879:
2877:
2875:
2871:
2865:
2862:
2860:
2857:
2855:
2852:
2850:
2847:
2845:
2842:
2840:
2837:
2835:
2832:
2831:
2829:
2827:
2823:
2817:
2814:
2812:
2809:
2805:
2802:
2800:
2797:
2795:
2792:
2790:
2787:
2785:
2782:
2780:
2777:
2775:
2772:
2770:
2767:
2765:
2762:
2760:
2757:
2756:
2755:
2752:
2751:
2749:
2747:
2743:
2740:
2738:
2734:
2730:
2726:
2721:
2717:
2711:
2708:
2706:
2703:
2702:
2699:
2695:
2688:
2683:
2681:
2676:
2674:
2669:
2668:
2665:
2657:
2653:
2648:
2643:
2639:
2635:
2631:
2626:
2622:
2618:
2614:
2610:
2606:
2602:
2597:
2593:
2591:0-19-853256-3
2587:
2583:
2582:
2577:
2573:
2569:
2565:
2563:0-387-96991-8
2559:
2555:
2550:
2546:
2544:981-256-360-1
2540:
2536:
2532:
2528:
2524:
2522:0-486-65685-3
2518:
2513:
2512:
2506:
2502:
2498:
2496:0-9616255-2-X
2492:
2488:
2483:
2477:
2471:
2467:
2463:
2458:
2454:
2448:
2444:
2440:
2435:
2434:
2431:
2425:
2421:
2417:
2412:
2408:
2406:0-88275-105-0
2402:
2398:
2394:
2390:
2386:
2382:
2378:
2374:
2370:
2366:
2361:
2357:
2353:
2349:
2347:0-387-95470-8
2343:
2338:
2337:
2330:
2326:
2324:0-387-98578-6
2320:
2315:
2314:
2307:
2303:
2297:
2293:
2292:
2286:
2281:
2275:
2260:
2254:
2250:
2249:
2244:
2240:
2236:
2232:
2228:
2224:
2220:
2216:
2212:
2208:
2207:
2202:
2198:
2194:
2190:
2186:
2182:
2178:
2174:
2169:
2165:
2161:
2157:
2153:
2149:
2145:
2141:
2137:
2136:
2128:
2125:from the
2124:
2115:
2114:
2106:
2102:
2097:
2092:
2088:
2084:
2080:
2076:
2072:
2068:
2064:
2057:
2055:
2046:
2042:
2038:
2034:
2029:
2024:
2021:(1): 69â100.
2020:
2016:
2012:
2005:
1997:
1993:
1988:
1983:
1979:
1975:
1971:
1964:
1955:
1948:
1942:
1933:
1924:
1911:
1905:
1901:
1897:
1893:
1889:
1883:
1875:
1869:
1865:
1861:
1857:
1856:
1848:
1846:
1844:
1842:
1827:
1823:
1817:
1815:
1813:
1811:
1809:
1794:
1790:
1784:
1782:
1773:
1769:
1765:
1761:
1757:
1753:
1749:
1745:
1741:
1734:
1732:
1727:
1717:
1716:Blockmodeling
1714:
1712:
1709:
1707:
1704:
1702:
1699:
1697:
1694:
1692:
1689:
1687:
1684:
1682:
1679:
1677:
1674:
1673:
1669:
1663:
1658:
1649:
1646:
1644:
1641:
1639:
1636:
1633:
1632:Latin squares
1630:
1627:
1624:
1623:
1614:
1607:
1603:
1585:
1582:
1573:
1545:
1540:
1535:
1532:
1523:
1509:
1506:Estimate for
1505:
1502:
1495:
1491:
1473:
1470:
1461:
1433:
1428:
1423:
1420:
1411:
1397:
1394:Estimate for
1393:
1373:
1363:
1360:Estimate for
1359:
1358:
1346:
1342:
1335:
1332:
1326:
1322:
1315:
1312:
1309:
1306:
1300:
1297:
1291:
1288:
1286:
1279:
1275:
1268:
1261:
1258:
1257:
1256:
1201:
1196:
1192:
1188:
1183:
1179:
1175:
1172:
1169:
1164:
1161:
1157:
1149:
1148:
1147:
1139:
1137:
1127:
1124:
1121:
1118:
1117:
1113:
1110:
1107:
1104:
1103:
1099:
1096:
1093:
1090:
1089:
1085:
1082:
1079:
1076:
1075:
1072:
1069:
1067:
1064:
1062:
1059:
1057:
1054:
1053:
1050:
1045:
1038:
1031:
1024:
1009:
1006:
1005:
1001:
998:
997:
993:
990:
989:
985:
982:
981:
977:
974:
973:
969:
966:
965:
961:
958:
957:
953:
950:
949:
945:
942:
941:
937:
934:
933:
929:
926:
925:
921:
918:
917:
911:
908:
903:
900:
899:
896:
887:
880:
876:
873:
870:
867:
862:
855:
852:
847:
840:
837:
831:
824:
820:
817:
816:
815:
810:
803:
793:
789:
785:
782:
771:
767:
761:
745:
738:
737:
732:
729:
723:
720:
714:
711:
705:
702:
701:
700:
693:
674:
663:
656:
653:
651:
648:
645:
642:
641:
626:
619:
605:
598:
584:
577:
576:
570:
563:
556:
549:
546:
543:
541:4-factor RBD
540:
539:
533:
526:
519:
516:
513:
511:3-factor RBD
510:
509:
503:
496:
493:
490:
488:2-factor RBD
487:
486:
483:
479:
477:
473:
470:
469:
463:
461:
446:
444:
434:
432:
421:
419:
409:
401:
393:
391:
381:
380:randomizing.
374:
373:
372:
364:
351:
347:
339:
330:
328:
324:
319:
311:
307:
305:
301:
297:
293:
283:
279:
275:
273:
272:Randomization
267:
265:
255:
247:
235:
231:
230:control group
227:
223:
219:
215:
211:
207:
203:
200:
197:
194:
191:
187:
183:
179:
175:
171:
167:
166:
161:
160:
155:
152:
151:
145:
144:interaction.
142:
138:
128:
125:
121:
117:
107:
105:
101:
100:Ronald Fisher
96:
92:
88:
84:
73:
70:
62:
52:
48:
42:
41:
35:
30:
21:
20:
8026:Applications
7900:
7859:Block design
7774:
7762:
7743:
7736:
7648:Econometrics
7598: /
7581:Chemometrics
7558:Epidemiology
7551: /
7524:Applications
7366:ARIMA model
7313:Q-statistic
7262:Stationarity
7158:Multivariate
7101: /
7097: /
7095:Multivariate
7093: /
7033: /
7029: /
6803:Bayes factor
6702:Signed rank
6614:
6588:
6580:
6568:
6263:Completeness
6099:Cohort study
6024:
5997:Opinion poll
5932:Missing data
5919:Study design
5874:Scatter plot
5796:Scatter plot
5789:Spearman's Ï
5751:Grouped data
5398:
5384:
5366:Latin square
5352:
5328:
5304:
5265:
5261:
5254:multivariate
5253:
5249:
5236:
5214:
5163:
5162:
5130:
5122:
5076:
4975:
4963:
4944:
4937:
4849:Econometrics
4799: /
4782:Chemometrics
4759:Epidemiology
4752: /
4725:Applications
4567:ARIMA model
4514:Q-statistic
4463:Stationarity
4359:Multivariate
4302: /
4298: /
4296:Multivariate
4294: /
4234: /
4230: /
4004:Bayes factor
3903:Signed rank
3815:
3789:
3781:
3769:
3464:Completeness
3300:Cohort study
3225:
3198:Opinion poll
3133:Missing data
3120:Study design
3075:Scatter plot
2997:Scatter plot
2990:Spearman's Ï
2952:Grouped data
2637:
2633:
2604:
2600:
2580:
2553:
2534:
2510:
2486:
2465:
2442:
2419:
2396:
2368:
2364:
2335:
2312:
2290:
2263:. Retrieved
2247:
2243:Bailey, R. A
2210:
2204:
2176:
2172:
2150:(4): 35â36.
2147:
2143:
2140:Addelman, S.
2133:Bibliography
2070:
2066:
2018:
2014:
2004:
1977:
1973:
1963:
1954:
1941:
1932:
1923:
1913:, retrieved
1891:
1882:
1854:
1829:. Retrieved
1825:
1796:. Retrieved
1792:
1747:
1743:
1681:Block design
1612:
1605:
1601:
1507:
1500:
1493:
1489:
1395:
1361:
1344:
1340:
1333:
1324:
1320:
1313:
1307:
1298:
1289:
1284:
1277:
1273:
1266:
1259:
1254:
1145:
1135:
1133:
1070:
1065:
1060:
1055:
1043:
1036:
1029:
1022:
1020:
909:
901:
894:
885:
878:
874:
868:
860:
853:
845:
838:
829:
822:
818:
808:
801:
799:
790:
786:
783:
779:
769:
762:
730:
721:
712:
703:
698:
688:
661:
654:
649:
646:-factor RBD
643:
568:
561:
554:
547:
531:
524:
517:
501:
494:
481:
475:
457:
440:
427:
415:
407:
399:
387:
378:
370:
361:
344:
323:S. Bernstein
320:
316:
289:
280:
276:
268:
260:
236:block design
226:block design
213:
209:
205:
202:Intervention
201:
195:
189:
185:
181:
178:double blind
173:
169:
163:
157:
153:
141:interactions
134:
124:Latin square
113:
90:
80:
65:
59:January 2018
56:
37:
7897:Statistics
7776:WikiProject
7691:Cartography
7653:Jurimetrics
7605:Reliability
7336:Time domain
7315:(LjungâBox)
7237:Time-series
7115:Categorical
7099:Time-series
7091:Categorical
7026:(Bernoulli)
6861:Correlation
6841:Correlation
6637:JarqueâBera
6609:Chi-squared
6371:M-estimator
6324:Asymptotics
6268:Sufficiency
6035:Interaction
5947:Replication
5927:Effect size
5884:Violin plot
5864:Radar chart
5844:Forest plot
5834:Correlogram
5784:Kendall's Ï
5341:BoxâBehnken
5222:Mixed model
5153:Confounding
5148:Interaction
5138:Effect size
5108:Sample size
4977:WikiProject
4892:Cartography
4854:Jurimetrics
4806:Reliability
4537:Time domain
4516:(LjungâBox)
4438:Time-series
4316:Categorical
4300:Time-series
4292:Categorical
4227:(Bernoulli)
4062:Correlation
4042:Correlation
3838:JarqueâBera
3810:Chi-squared
3572:M-estimator
3525:Asymptotics
3469:Sufficiency
3236:Interaction
3148:Replication
3128:Effect size
3085:Violin plot
3065:Radar chart
3045:Forest plot
3035:Correlogram
2985:Kendall's Ï
1343:(of factor
1323:(of factor
437:Replication
304:variability
292:statistical
218:randomizing
83:statistical
51:introducing
7926:Fano plane
7891:Hypergraph
7643:Demography
7361:ARMA model
7166:Regression
6743:(Friedman)
6704:(Wilcoxon)
6642:Normality
6632:Lilliefors
6579:Student's
6455:Resampling
6329:Robustness
6317:divergence
6307:Efficiency
6245:(monotone)
6240:Likelihood
6157:Population
5990:Stratified
5942:Population
5761:Dependence
5717:Count data
5648:Percentile
5625:Dispersion
5558:Arithmetic
5493:Statistics
5297:randomized
5295:Completely
5266:covariance
5028:Scientific
4844:Demography
4562:ARMA model
4367:Regression
3944:(Friedman)
3905:(Wilcoxon)
3843:Normality
3833:Lilliefors
3780:Student's
3656:Resampling
3530:Robustness
3518:divergence
3508:Efficiency
3446:(monotone)
3441:Likelihood
3358:Population
3191:Stratified
3143:Population
2962:Dependence
2918:Count data
2849:Percentile
2826:Dispersion
2759:Arithmetic
2694:Statistics
2601:Biometrika
2265:2010-02-22
2028:2010.14078
1947:Rootzén H.
1915:2023-12-11
1831:2023-12-11
1798:2023-12-11
1750:(1): 1â7.
1722:References
1604:for which
1492:for which
418:confounded
137:confounded
34:references
7876:Incidence
7024:Logistic
6791:posterior
6717:Rank sum
6465:Jackknife
6460:Bootstrap
6278:Bootstrap
6213:Parameter
6162:Statistic
5957:Statistic
5869:Run chart
5854:Pie chart
5849:Histogram
5839:Fan chart
5814:Bar chart
5696:L-moments
5583:Geometric
5306:Factorial
5190:inference
5170:Covariate
5132:Treatment
5118:Treatment
4225:Logistic
3992:posterior
3918:Rank sum
3666:Jackknife
3661:Bootstrap
3479:Bootstrap
3414:Parameter
3363:Statistic
3158:Statistic
3070:Run chart
3055:Pie chart
3050:Histogram
3040:Fan chart
3015:Bar chart
2897:L-moments
2784:Geometric
2274:cite book
2087:0146-0404
2073:(8): 11.
2045:1076-9986
1764:0003-1305
1583:⋅
1577:¯
1549:¯
1541:−
1533:⋅
1527:¯
1474:⋅
1465:¯
1437:¯
1429:−
1424:⋅
1415:¯
1377:¯
1355:Estimates
1173:μ
1056:Treatment
746:⋮
675:⋯
627:⋮
606:⋮
585:⋮
443:replicate
420:effects.
196:Elevation
8053:Category
7990:Theorems
7901:Blocking
7871:Geometry
7738:Category
7431:Survival
7308:Johansen
7031:Binomial
6986:Isotonic
6573:(normal)
6218:location
6025:Blocking
5980:Sampling
5859:QâQ plot
5824:Box plot
5806:Graphics
5701:Skewness
5691:Kurtosis
5663:Variance
5593:Heronian
5588:Harmonic
5429:Category
5424:Glossary
5230:Bayesian
5208:Bayesian
5164:Blocking
5143:Contrast
5123:blocking
5083:Bayesian
5070:Blinding
5060:validity
5057:external
5053:Internal
4939:Category
4632:Survival
4509:Johansen
4232:Binomial
4187:Isotonic
3774:(normal)
3419:location
3226:Blocking
3181:Sampling
3060:QâQ plot
3025:Box plot
3007:Graphics
2902:Skewness
2892:Kurtosis
2864:Variance
2794:Heronian
2789:Harmonic
2578:(1987).
2507:(1988).
2464:(2005).
2441:(2008).
2418:(2008).
2395:(1979).
2245:(2008).
2105:32645134
1654:See also
1513: :
1401: :
1364: :
182:blocking
148:Examples
91:blocking
81:In the
7764:Commons
7711:Kriging
7596:Process
7553:studies
7412:Wavelet
7245:General
6412:Plug-in
6206:L space
5985:Cluster
5686:Moments
5504:Outline
5322:Taguchi
5290:Designs
5048:Control
4965:Commons
4912:Kriging
4797:Process
4754:studies
4613:Wavelet
4446:General
3613:Plug-in
3407:L space
3186:Cluster
2887:Moments
2705:Outline
2656:2238364
2621:2333423
2385:2684574
2356:1994124
2235:0030181
2227:2984159
2193:2284277
2164:2681737
2096:7425741
1996:4515556
1772:2682986
1071:Block 3
1066:Block 2
1061:Block 1
776:Example
449:Example
333:Example
290:In the
190:females
165:placebo
110:History
47:improve
7847:Fields
7633:Census
7223:Normal
7171:Manova
6991:Robust
6741:2-way
6733:1-way
6571:-test
6242:
5819:Biplot
5610:Median
5603:Lehmer
5545:Center
5362:(GRBD)
5262:Ancova
5250:Manova
5185:Models
5030:method
4834:Census
4424:Normal
4372:Manova
4192:Robust
3942:2-way
3934:1-way
3772:-test
3443:
3020:Biplot
2811:Median
2804:Lehmer
2746:Center
2654:
2619:
2588:
2560:
2541:
2519:
2493:
2472:
2449:
2426:
2403:
2383:
2354:
2344:
2321:
2298:
2255:
2233:
2225:
2191:
2162:
2103:
2093:
2085:
2043:
1994:
1906:
1870:
1770:
1762:
1362:μ
1308:μ
1255:where
1224:
788:time.
174:female
162:, and
36:, but
7257:Trend
6786:prior
6728:anova
6617:-test
6591:-test
6583:-test
6490:Power
6435:Pivot
6228:shape
6223:scale
5673:Shape
5653:Range
5598:Heinz
5573:Cubic
5509:Index
5354:Block
4458:Trend
3987:prior
3929:anova
3818:-test
3792:-test
3784:-test
3691:Power
3636:Pivot
3429:shape
3424:scale
2874:Shape
2854:Range
2799:Heinz
2774:Cubic
2710:Index
2652:JSTOR
2617:JSTOR
2381:JSTOR
2223:JSTOR
2189:JSTOR
2160:JSTOR
2023:arXiv
1768:JSTOR
1563:with
1451:with
1142:Model
699:with
454:Table
186:males
104:ANOVA
7981:Dual
7490:Test
6690:Sign
6542:Wald
5615:Mode
5553:Mean
5188:and
5121:and
5055:and
4691:Test
3891:Sign
3743:Wald
2816:Mode
2754:Mean
2586:ISBN
2558:ISBN
2539:ISBN
2517:ISBN
2491:ISBN
2470:ISBN
2447:ISBN
2424:ISBN
2401:ISBN
2342:ISBN
2319:ISBN
2296:ISBN
2280:link
2253:ISBN
2101:PMID
2083:ISSN
2041:ISSN
1904:ISBN
1868:ISBN
1760:ISSN
1276:and
800:Let
188:and
172:and
170:male
159:drug
6670:BIC
6665:AIC
3871:BIC
3866:AIC
2642:doi
2609:doi
2373:doi
2215:doi
2211:111
2181:doi
2152:doi
2091:PMC
2075:doi
2033:doi
1982:doi
1896:doi
1860:doi
1752:doi
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