Mixed Model ANOVA and Statistics for Education
Analysis of variance (sequential SS)
Analysis of variance with SS type II or III (including mixed models).
Analysis of variance for regression.
Mixed model least squares analysis of variance (mixed ANOVA).
F-test based best subset selection.
Confidence interval for the grand mean of a linear model
Confusion matrix.
Contrast matrix for weighted effect coding
Create new effect labels for lm
F-test based model effect selection for linear models.
Effects of formulas.
Fitting Generalized Linear Models
Balance cheking of models.
Fitting Linear Models
Property plots for relevant component analysis
Prediction fits
Print method for objects of class(AnovaMix)
Summarizing Linear Model Fits
Test of Equal or Given Proportions in text-book version
Removes function r() from formulas.
Pairwise comparison with multiple testing compensation.
Standardized Pearson residuals
Text book versions of t-tests and z-tests.
Tally of discrete numbers
The main functions perform mixed models analysis by least squares or REML by adding the function r() to formulas of lm() and glm(). A collection of text-book statistics for higher education is also included, e.g. modifications of the functions lm(), glm() and associated summaries from the package 'stats'.