RMAOV31 1.0

This m-file is a three-factor analysis of variance design in which there are repeated measures on only one of the factors. In repeated measures designs, the same participants are used in all conditions. This is like an extreme matching. This allows for reduction of error variance due to subject factors. Fewer participants can be used in an repeated measures design. Repeated measures designs make it easier to see an effect of the independent variable on the dependent variable (if there is such an effect). There are two different error terms. One of the error terms involves subject-to-subject variability within each group or, in the case of the present design, within each cell formed by the two between-group factors. The other error term involves the variability within subjects. The within-subject variability can be divided into five components, which include the main effect of the RM factor and all of its interactions.Inputs: X - data matrix (Size of matrix must be n-by-5;dependent variable=column 1; independent variable 1=column 2; independent variable 2=column 3; independent variable 3 (within-factor)=column 4; subject=column 5). alpha - significance level (default = 0.05). Outputs: - Complete Analysis of Variance Table.

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Components,  Divided,  Factor,  Group,  Include,  Inputs,  Interactions,  Subjects,  Withinsubject
Users rating:	0/10