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sasLM (version 0.6.0)

'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

0.6.0

License

GPL-3

Maintainer

Kyun-Seop Bae

Last Published

June 15th, 2021

Functions in sasLM (0.6.0)

Collinearity Diagnostics

F Test with a Set of Contrasts

Plot Pairwise Differences

Internal Functions

Correlation test of multiple numeric columns

Confidence Interval Estimation

Analysis BY variable

Coefficient of Variation in percentage

Analysis of Variance similar to SAS PROC ANOVA

An Example Data of Bioequivalence Study

Lower Confidence Limit

Estimate Linear Function

Expected Mean Square Formula

Median without NA

Mean without NA

Standard Deviation

Inter-Quartile Range

Type III Expected Mean Square Formula

Standard Error of Skewness

Least Square Means

Regression of Linear Least Square, similar to SAS PROC REG

Get a Contrast Matrix for Type III SS

'SAS' Linear Model

General Linear Model similar to SAS PROC GLM

Number of observations

Generalized inverse matrix of type 2, g2 inverse

Get a Contrast Matrix for Type I SS

ANOVA with Type I SS

Beautify the output of knitr::kable

Convert some columns of a data.frame to factors

Standard Error of Kurtosis

Sum of Square with a Given Contrast Set

F Test with Slice

ANOVA with Type II SS

Standard Error of the Sample Mean

ANOVA with Type III SS

Estimate Linear Functions

Linear Regression with g2 inverse

Table Summary 2 independent(x) variables

Get a Contrast Matrix for Type II SS

Table Summary 3 independent(x) variables

Partial Correlation test of multiple columns

Test Type III SS using error term other than MSE

Upper Confidence Limit

Pairwise Difference

Satterthwaite Approximation of Pooled Variance and Degree of Freedom

Estimability Check

Simple Linear Regressions with Each Independent Variable

Plot Confidence and Prediction Bands for Simple Linear Regression

Is it a corrleation matrix?

Diagnostic Plot for Regression

Regression of Conventional Way with Rich Diagnostics

Table Summary 0 independent(x) variable

Table Summary 1 independent(x) variable