Analysis of Variance and Designed Experiments

Functions

General Analysis of Variance

One-way analysis of variance anovaOneway

Analyzes a one-way classification model with covariates ancovar

Analysis of variance for fixed effects balanced factorial designs anovaFactorial

Nested random effects analysis of variance anovaNested

Analysis of variance for balanced fixed, random, or mixed models anovaBalanced

Designed Experiments

Analysis of balanced and unbalanced completely

randomized factorial experiments crdFactorial

Analysis of balanced and unbalanced randomized

complete block factorial experiments rcbdFactorial

Analysis of latin-square experiments latinSquare

Analysis of balanced and partially-balanced data from

lattice experiments lattice

Analysis of split-plot experiments splitPlot

Analysis of split-split-plot experiments splitSplitPlot

Analysis of strip-plot experiments stripPlot

Analysis of strip-split-plot experiments stripSplitPlot

Utilities

Bartlett’s and Levene’s tests of the homogeneity

of variance assumption in analysis of variance homogeneity

Multiple comparisons of means multipleComparisons

False discovery rates falseDiscoveryRates

Yates’ method for estimating missing observations in designed experiments yates