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sasLM (version 0.5.0)

'SAS' Linear Model

Description

This is a core implementation of 'SAS' procedures for linear models - GLM, REG, and ANOVA. 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).

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Version

Install

install.packages('sasLM')

Monthly Downloads

1,004

Version

0.5.0

License

GPL-3

Maintainer

Kyun-Seop Bae

Last Published

February 15th, 2021

Functions in sasLM (0.5.0)

Collinearity Diagnostics

Analysis BY variable

Expected Mean Square Formula

General Linear Model similar to SAS PROC GLM

Correlation test of multiple numeric columns

Confidence Interval Estimation

Analysis of Variance similar to SAS PROC ANOVA

Internal Functions

Generalized inverse matrix of type 2, g2 inverse

Partial Correlation test of multiple columns

An Example Data of Bioequivalence Study

Standard Error of Kurtosis

Simple Linear Regressions with Each Independent Variable

Get a Contrast Matrix for Type II SS

Table Summary 0 independent(x) variable

Get a Contrast Matrix for Type I SS

Linear Regression with g2 inverse

Mean without NA

Inter-Quartile Range

Regression of Linear Least Square, similar to SAS PROC REG

Standard Deviation

Standard Error of the Sample Mean

Number of observations

Test Type III SS using error term other than MSE

Pairwise Difference by Least Significant Difference

Upper Confidence Limit

Satterthwaite Approximation of Pooled Variance and Degree of Freedom

Convert some columns of a data.frame to factors

ANOVA with Type I SS

Lower Confidence Limit

ANOVA with Type II SS

Standard Error of Skewness

ANOVA with Type III SS

Least Square Means

Type III Expected Mean Square Formula

Plot Confidence and Prediction Bands for Simple Linear Regression

Table Summary 3 independent(x) variables

Diagnostic Plot for Regression

Beautify the output of knitr::kable

Sum of Square with a Given Contrast Set

Is it a corrleation matrix?

Table Summary 2 independent(x) variables

Regression of Conventional Way with Rich Diagnostics

Table Summary 1 independent(x) variable

Get a Contrast Matrix for Type III SS

Estimate Linear Contrast

'SAS' Linear Model