repMeasAnova: Repeated measures ANOVA
In RcmdrPlugin.aRnova: R Commander Plug-in for Repeated-Measures ANOVA

Description Usage Arguments Details Value Author(s) See Also

View source: R/aRnova.R

Dialog box to (i) select the within-subject variables corresponding to the factors defined in repMeasAnovaSetup, (ii) select the between-suject factors, (iii) set options and (iv) launch the repeated measures anova.

1	repMeasAnova(.withinfactors, .withinlevels)

`.withinfactors`	list of within-subject factors
`.withinlevels`	list of within-subject variables

Options:

'SS type' type of sum of squares, default: type = 2. See Details in Anova
'Effect size' compute and prints effect size (partial eta squared)
'Summary statistics for groups' prints summary statistics for groups formed by all combinations of factors
'Pairwise comparisons of means' performs post-hoc Tukey's HSD test on significant (p < .05) or close to significant (p < 0.1) effects.

On OK, the following operations are carried out:

Generates a dataset containing complete cases and converted from 'wide' to 'long' format (extension .cplt.lg), with the following columns added:
- 'id' (factor) identifies the subjects.
- 'DV' (numeric) the measure or dependent variable.
- 'trial' (int) variable that differentiates multiple measures ('DV') from the same subject ('id').
- '<factorA>' (factor) levels of the within-suject factor A (one column per within subject factor)
- '<factorA.factorB:...>' (factor) factor that differentiates multiple measures from groups or subjects with same factors levels
This 'long' dataset is useful for ploting means and post-hoc analysis
Computes repeated measure ANOVA using Anova
Computes effect sizes (partial eta squared)
Prints a summary of marginal statistics (count, min, max, mean, ds)
runs post-hoc analysis on significant or close to significant effects