Most researchers using analysis of variance (ANOVA) use a fixed-effects model. However, a random- or mixed-effects model may be a more appropriate fit for many research designs. One benefit of the random- and mixed-effects models is that they yield more generalizable results. This paper focuses on the similarities and differences between the…

Research supported by the National Research Council of Canada, Grant APA-252-2057-B.

Marascuilo (1966) proposes a chi square analog of Scheffe's multiple comparisons procedure. With respect to pairwise comparisons among k independent correlation coefficients, a multiple range procedure will produce lower critical values than the corresponding chi square values, thereby increasing the power of the resulting tests. Basis of the…

An alternative is proposed to the usual Interaction and Nested Analysis of Variance (ANOVA) models by which a researcher will be able to investigate both interaction and nested questions in the same experiment without committing Type IV errors. (RC)

FANTAB is a computer program written in Fortran IV which helps design factorial analysis of variance tables and provides formulae for table entries. It is a computerization of a paper entitled: "Rules of Thumb for Writing the Anova Table" (Millman and Glass, 1967). FANTAB is appropriate for factorial models which have two, three, or four…

The standard statistical analysis of data classified in two ways (say into rows and columns) is through an analysis of variance that splits the total variation of the data into the main effect of rows, the main effect of columns, and the interaction between rows and columns. This paper presents an alternative Bayesian analysis of the same…

Linear models are available for describing dominance and composition judgements. These models include parameters for the scale values of the stimuli, response order bias, and interaction between stimuli, all of which may be evaluated with analysis of variance procedures. (Author)

The computation of F ratios from cell means and standard deviations is shown for a two-way analysis of variance. (JKS)

Procedures to estimate the magnitude of a treatment effect are examined for analysis of variance (ANOVA) designs which have repeated-measures. In particular, it is argued that the estimate of utility (strength of effect) for a within-subjects variable should be adjusted to reflect the underlying ANOVA model. (Author/JKS)

A major pitfall with fixed-effects analysis of variance in the nested design is illustrated. Under the null hypothesis of no intervention effect, the rejection rate for "F(sub fixed)" in the nested design is greater than the putative Type I error rate of the test, potentially to an extreme degree. (Author/TJH)