GLM: General Linear Model similar to SAS PROC GLM

View source: R/GLM.R

GLMR Documentation

General Linear Model similar to SAS PROC GLM

Description

GLM is the main function of this package.

Usage

GLM(Formula, Data, BETA=FALSE, EMEAN=FALSE, conf.level=0.95, eps=1e-8)

Arguments

Formula

a conventional formula for a linear model.

Data

a data.frame to be analyzed

BETA

if TRUE, coefficients (parameters) of REG will be returned. This is equivalent to SOLUTION option of SAS PROC GLM

EMEAN

if TRUE, least square means (or expected means) will be returned. This is equivalent to LSMEANS clause of SAS PROC GLM

conf.level

confidence level for the confidence limit of the least square mean

eps

Less than this value is considered as zero.

Details

It performs the core function of SAS PROC GLM. Least square means for the tnteraction term of three variables is not supported yet.

Value

The result is comparable to that of SAS PROC GLM.

ANOVA

ANOVA table for the model

Fitness

Some measures of goodness of fit such as R-square and CV

Type I

Type I sum of square table

Type II

Type II sum of square table

Type III

Type III sum of square table

Parameter

Parameter table with standard error, t value, p value. TRUE is 1, and FALSE is 0 in the Estimable column. This is returned only with BETA=TRUE option.

Expected Mean

Least square (or expected) mean table with confindence limit. This is returned only with EMEAN=TRUE option.

Author(s)

Kyun-Seop Bae k@acr.kr

Examples

GLM(uptake ~ Type*Treatment + conc, CO2[-1,]) # Making data unbalanced
GLM(uptake ~ Type*Treatment + conc, CO2[-1,], BETA=TRUE)
GLM(uptake ~ Type*Treatment + conc, CO2[-1,], EMEAN=TRUE)
GLM(uptake ~ Type*Treatment + conc, CO2[-1,], BETA=TRUE, EMEAN=TRUE)

sasLM documentation built on Sept. 5, 2022, 5:11 p.m.