Learn R Programming

⚠️There's a newer version (0.10.5) of this package.Take me there.

sasLM (version 0.6.1)

'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).

Copy Link

Version

Install

install.packages('sasLM')

Monthly Downloads

729

Version

0.6.1

License

GPL-3

Maintainer

Kyun-Seop Bae

Last Published

July 14th, 2021

Functions in sasLM (0.6.1)

Internal Functions

Collinearity Diagnostics

F Test with a Set of Contrasts

Confidence Interval Estimation

Analysis BY variable

Correlation test of multiple numeric columns

Plot Pairwise Differences

Coefficient of Variation in percentage

General Linear Model similar to SAS PROC GLM

Generalized inverse matrix of type 2, g2 inverse

Analysis of Variance similar to SAS PROC ANOVA

Expected Mean Square Formula

Least Square Means

Lower Confidence Limit

Pairwise Difference

Estimate Linear Function

Partial Correlation test of multiple columns

Regression of Linear Least Square, similar to SAS PROC REG

Inter-Quartile Range

An Example Data of Bioequivalence Study

Mean without NA

'SAS' Linear Model

Standard Error of Skewness

Standard Deviation

Beautify the output of knitr::kable

Type III Expected Mean Square Formula

Standard Error of Kurtosis

Sum of Square with a Given Contrast Set

Number of observations

Standard Error of the Sample Mean

F Test with Slice

Convert some columns of a data.frame to factors

ANOVA with Type I SS

Satterthwaite Approximation of Pooled Variance and Degree of Freedom

Median without NA

Get a Contrast Matrix for Type III SS

ANOVA with Type III SS

ANOVA with Type II SS

Estimate Linear Functions

Test Type III SS using error term other than MSE

Simple Linear Regressions with Each Independent Variable

Geometric Coefficient of Variation in percentage

Estimability Check

Plot Confidence and Prediction Bands for Simple Linear Regression

Diagnostic Plot for Regression

Linear Regression with g2 inverse

Regression of Conventional Way with Rich Diagnostics

Table Summary 3 independent(x) variables

Table Summary 2 independent(x) variables

Upper Confidence Limit

Table Summary 0 independent(x) variable

Get a Contrast Matrix for Type II SS

Get a Contrast Matrix for Type I SS

Table Summary 1 independent(x) variable

Geometric Mean without NA

Is it a corrleation matrix?