stats (version 3.3)

model.tables: Compute Tables of Results from an Aov Model Fit

Description

Computes summary tables for model fits, especially complex aov fits.

Usage

model.tables(x, ...)
## S3 method for class 'aov':
model.tables(x, type = "effects", se = FALSE, cterms, \dots)
## S3 method for class 'aovlist':
model.tables(x, type = "effects", se = FALSE, \dots)

Arguments

x

a model object, usually produced by aov

type

type of table: currently only "effects" and "means" are implemented. Can be abbreviated.

se

should standard errors be computed?

cterms

A character vector giving the names of the terms for which tables should be computed. The default is all tables.

...

further arguments passed to or from other methods.

Value

• An object of class "tables.aov", as list which may contain components
• tables
  A list of tables for each requested term.
• n
  The replication information for each term.
• se
  Standard error information.

Warning

The implementation is incomplete, and only the simpler cases have been tested thoroughly.

Weighted aov fits are not supported.

Details

For type = "effects" give tables of the coefficients for each term, optionally with standard errors.

For type = "means" give tables of the mean response for each combinations of levels of the factors in a term.

The "aov" method cannot be applied to components of a "aovlist" fit.

See Also

aov, proj, replications, TukeyHSD, se.contrast

Examples

options(contrasts = c("contr.helmert", "contr.treatment"))
npk.aov <- aov(yield ~ block + N*P*K, npk)
model.tables(npk.aov, "means", se = TRUE)

## as a test, not particularly sensible statistically
npk.aovE <- aov(yield ~  N*P*K + Error(block), npk)
model.tables(npk.aovE, se = TRUE)
model.tables(npk.aovE, "means")

Run the code above in your browser using DataCamp Workspace