Minimal sample size in balanced ANOVA models of crossed, nested, and mixed classifications

ANOVA , ANCOVA and Mixed Effects Models Week

A grouping or blocking of observations can be achieved by using categorical or dummy variables. Examples of categorical variables include gender, country of origin, job title and experimental treatment. This should be contrasted with ordinal variables, such as age class, highest degree attained or a score on a 5-point scale with values comprised between strongly agree and strongly disagree. The...

Power and Sample Size in Linear Mixed Effects Models

Sample Size Problems in Anova : Bayesian Point of View

In this paper we discuss the sample size problem for balanced one way ANOVA under a posterior Bayesian formulation of the problem. Using the distribution theory of appropriate quadratic forms we derive explicit sample sizes for prespeci ed posterior precisions. Comparisons with classical sample sizes are made. Instead of extensive tables, a mathematica program for sample size calculation is giv...

Sample Size Considerations for Multiple Comparison Procedures in ANOVA

Adequate sample sizes for omnibus ANOVA tests do not necessarily provide sufficient statistical power for post hoc multiple comparisons typically performed following a significant omnibus F test. Results reported support a comparison-of-most-interest approach for sample size determination in ANOVA based on effect sizes for multiple comparisons. Introduction The determination of an appropriate s...

Constrained statistical inference: sample-size tables for ANOVA and regression

Researchers in the social and behavioral sciences often have clear expectations about the order/direction of the parameters in their statistical model. For example, a researcher might expect that regression coefficient β1 is larger than β2 and β3. The corresponding hypothesis is H: β1 > {β2, β3} and this is known as an (order) constrained hypothesis. A major advantage of testing such a hypothes...