Usually, the first step to multiple linear regression is simple linear regressions with a single independent variable.

This is a core implementation of 'SAS' procedures for linear models - GLM, REG, ANOVA, TTEST, FREQ, and UNIVARIATE. Some R packages provide type II and type III SS. However, the results of nested and complex designs are often different from those of 'SAS.' Different results does not necessarily mean incorrectness. However, many wants the same results to SAS. This package aims to achieve that.
Reference: Littell RC, Stroup WW, Freund RJ (2002, ISBN:0-471-22174-0).

Kyun-Seop Bae

sasLM

'SAS' Linear Model

lr0 function

<dl> <dt>Formula</dt>
<dd>a conventional formula for a linear model. Intercept will always be added.</dd> <dt>Data</dt>
<dd>a <code>data.frame</code> to be analyzed</dd></dl>

Arguments

Author

Simple Linear Regressions with Each Independent Variable — lr0

<dl>

 <dt>Formula</dt>
<dd>a conventional formula for a linear model. Intercept will always be added.</dd>

 <dt>Data</dt>
<dd>a <code>data.frame</code> to be analyzed</dd>

</dl>

lr0: Simple Linear Regressions with Each Independent Variable

Description

Usage

Value

Arguments

Author

Details

Examples