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Compact Letter Display (CLD) is a statistical method to clarify the output of multiple hypothesis testing when using the ANOVA and Tukey's range tests. CLD can also be applied following the Duncan's new multiple range test (which is similar to Tukey's range test).
Duncan modeled the consequences of two or more means being equal using additive loss functions within and across the pairwise comparisons. If one assumes the same loss function across the pairwise comparisons, one needs to specify only one constant K, and this indicates the relative seriousness of type I to type II errors in each pairwise ...
GraphPad Prism is a commercial scientific 2D graphing and statistics software for Windows and Mac OS desktop computers. Software features include nonlinear regression , with functionalities including the removal of outliers, comparisons of models, comparisons of curves, and interpolation of standard curves.
Their method was a general one, which considered all kinds of pairwise comparisons. [7] Tukey's and Scheffé's methods allow any number of comparisons among a set of sample means. On the other hand, Dunnett's test only compares one group with the others, addressing a special case of multiple comparisons problem—pairwise comparisons of ...
As a result of two explicit pairwise comparisons – i.e. explicitly performed by the decision-maker – five of the six undominated pairs have been ranked. The decision-maker may cease ranking whenever she likes (before all undominated pairs are ranked), but let's suppose she continues and ranks the remaining pair (v) as a2 + b1 + c2 > a1 + b2 ...
Pairwise comparison may refer to: Pairwise comparison (psychology) Round-robin voting This page was last edited on 14 ... Add languages ...
Product One-way Two-way MANOVA GLM Mixed model Post-hoc Latin squares; ADaMSoft: Yes Yes No No No No No Alteryx: Yes Yes Yes Yes Yes Analyse-it: Yes Yes No
Tukey's procedure is only applicable for pairwise comparisons. It assumes independence of the observations being tested, as well as equal variation across observations ( homoscedasticity ).