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sasLM (version 0.9.2)

'SAS' Linear Model

Description

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

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Version

Install

install.packages('sasLM')

Monthly Downloads

730

Version

0.9.2

License

GPL-3

Maintainer

Kyun-Seop Bae

Last Published

October 5th, 2022

Functions in sasLM (0.9.2)

Lower Confidence Limit

Odds Ratio and Score CI of two groups with strata by MN method

Odds Ratio of two groups with strata by inverse variance method

Odds Ratio of two groups

Number of observations

Pairwise Difference

Partial Correlation test of multiple columns

Odds Ratio and Score CI of two groups without strata by MN method

Odds Ratio of two groups with strata by CMH method

Relative Risk and Score CI of two groups with strata by MN method

Regression of Linear Least Square, similar to SAS PROC REG

Relative Risk of two groups

Risk Difference between two groups

Risk Difference between two groups with strata by inverse variance method

Risk Difference and Score CI between two groups without strata by MN method

Inter-Quartile Range

Relative Risk and Score CI of two groups without strata by MN method

Risk Difference and Score CI between two groups with strata by MN method

Standard Error of the Sample Mean

Standard Error of Skewness

Score CI of a proportion

Convert some columns of a data.frame to factors

F Test with Slice

Beautify the output of knitr::kable

Sum of Square with a Given Contrast Set

ANOVA with Type I SS

Upper Confidence Limit

Relative Risk of two groups with strata by inverse variance method

Geometric Coefficient of Variation in percentage

Geometric Mean without NA

Residual Diagnostic Plot for Regression

Test Type III SS using error term other than MSE

Is it a corrleation matrix?

Type III Expected Mean Square Formula

Univariate Descriptive Statistics

Simple Linear Regressions with Each Independent Variable

Correlation test by Fisher's Z transformation

Regression of Conventional Way with Rich Diagnostics

Linear Regression with g2 inverse

Get a Contrast Matrix for Type I SS

Satterthwaite Approximation of Variance and Degree of Freedom

'SAS' Linear Model

Table Summary 3 independent(x) variables

Get a Contrast Matrix for Type II SS

Plot Confidence and Prediction Bands for Simple Linear Regression

Table Summary 2 independent(x) variables

Diagnostic Plot for Regression

Get a Contrast Matrix for Type III SS

Table Summary 0 independent(x) variable

Table Summary 1 independent(x) variable

Estimate Linear Functions

ANOVA with Type III SS

Standard Deviation

Estimability Check

ANOVA with Type II SS

Plot Pairwise Differences

Expected Mean Square Formula

An Example Data of Bioequivalence Study

Coefficient of Variation in percentage

F Test with a Set of Contrasts

Analysis BY variable

Collinearity Diagnostics

Correlation test of multiple numeric columns

Confidence Interval Estimation

Internal Functions

Least Square Means

Mean without NA

Median without NA

General Linear Model similar to SAS PROC GLM

Estimate Linear Function

Standard Error of Kurtosis

Generalized inverse matrix of type 2, g2 inverse