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mixlm (version 1.2.2)

Mixed Model ANOVA and Statistics for Education

Description

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'.

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Version

Install

install.packages('mixlm')

Monthly Downloads

960

Version

1.2.2

License

GPL (>= 2)

Maintainer

Kristian Hovde Liland

Last Published

November 13th, 2017

Functions in mixlm (1.2.2)

lm

Fitting Linear Models
spearson

Standardized Pearson residuals
t_test

Text book versions of t-tests and z-tests.
best.subsets

F-test based best subset selection.
confusion

Confusion matrix.
is.balanced

Balance cheking of models.
PRESS

Prediction fits
fparse

Effects of formulas.
glm

Fitting Generalized Linear Models
CIgrandMean

Confidence interval for the grand mean of a linear model
anova.lmm

Analysis of variance (sequential SS)
anova_reg

Analysis of variance for regression.
print.summary.lmm

Summarizing Linear Model Fits
prop.test.ordinary

Test of Equal or Given Proportions in text-book version
plotprops

Property plots for relevant component analysis
AnovaMix

Mixed model least squares analysis of variance (mixed ANOVA).
print.AnovaMix

Print method for objects of class(AnovaMix)
Anova.lmm

Analysis of variance with SS type II or III (including mixed models).
rparse

Removes function r() from formulas.
simple.glht

Pairwise comparison with multiple testing compensation.
effect.labels

Create new effect labels for lm
forward

F-test based model effect selection for linear models.
tally

Tally of discrete numbers