Usually, the first step in multiple linear regression is to perform simple linear regressions with each 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 do not necessarily mean incorrectness. However, many want the same results as '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. The 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. The 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