summary.aov {stats} R Documentation

## Summarize an Analysis of Variance Model

### Description

Summarize an analysis of variance model.

### Usage

## S3 method for class 'aov'
summary(object, intercept = FALSE, split,
expand.split = TRUE, keep.zero.df = TRUE, ...)

## S3 method for class 'aovlist'
summary(object, ...)


### Arguments

 object An object of class "aov" or "aovlist". intercept logical: should intercept terms be included? split an optional named list, with names corresponding to terms in the model. Each component is itself a list with integer components giving contrasts whose contributions are to be summed. expand.split logical: should the split apply also to interactions involving the factor? keep.zero.df logical: should terms with no degrees of freedom be included? ... Arguments to be passed to or from other methods, for summary.aovlist including those for summary.aov.

### Value

An object of class c("summary.aov", "listof") or "summary.aovlist" respectively.

For fits with a single stratum the result will be a list of ANOVA tables, one for each response (even if there is only one response): the tables are of class "anova" inheriting from class "data.frame". They have columns "Df", "Sum Sq", "Mean Sq", as well as "F value" and "Pr(>F)" if there are non-zero residual degrees of freedom. There is a row for each term in the model, plus one for "Residuals" if there are any.

For multistratum fits the return value is a list of such summaries, one for each stratum.

### Note

The use of expand.split = TRUE is little tested: it is always possible to set it to FALSE and specify exactly all the splits required.

aov, summary, model.tables, TukeyHSD

### Examples

## For a simple example see example(aov)

# Cochran and Cox (1957, p.164)
# 3x3 factorial with ordered factors, each is average of 12.
CC <- data.frame(
y = c(449, 413, 326, 409, 358, 291, 341, 278, 312)/12,
P = ordered(gl(3, 3)), N = ordered(gl(3, 1, 9))
)
CC.aov <- aov(y ~ N * P, data = CC , weights = rep(12, 9))
summary(CC.aov)

# Split both main effects into linear and quadratic parts.
summary(CC.aov, split = list(N = list(L = 1, Q = 2),
P = list(L = 1, Q = 2)))

# Split only the interaction
summary(CC.aov, split = list("N:P" = list(L.L = 1, Q = 2:4)))

# split on just one var
summary(CC.aov, split = list(P = list(lin = 1, quad = 2)))
summary(CC.aov, split = list(P = list(lin = 1, quad = 2)),
expand.split = FALSE)

[Package stats version 4.2.0 Index]