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sasLM (version 0.10.5)

'SAS' Linear Model

Description

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 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

0.10.5

License

GPL-3

Maintainer

Kyun-Seop Bae

Last Published

October 2nd, 2024

Functions in sasLM (0.10.5)

Example Datasets

Estimate Linear Function

Number of observations

Lower Confidence Limit

Least Square Means

Standard Error of Kurtosis

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

Risk Difference between two groups

Odds Ratio of two groups

Inter-Quartile Range

Median without NA

Test with Random Effects

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

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

Risk Difference between two groups with strata by inverse variance method

Pocock (fixed) Bound for the cumulative Z-test with a final target alpha-value

Relative Risk of two groups with strata by inverse variance method

Standard Error of the Sample Mean

Mean without NA

F Test with Slice

Independent two groups t-test comparable to PROC TTEST

Odds Ratio of two groups with strata by CMH method

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

Odds Ratio of two groups with strata by inverse variance method

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

Partial Correlation test of multiple columns

Regression of Linear Least Square, similar to SAS PROC REG

Pairwise Difference

Univariate Descriptive Statistics

ANOVA with Type II SS

ANOVA with Type III SS

Standard Deviation

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

Upper Confidence Limit

Is it a correlation matrix?

Plot Confidence and Prediction Bands for Simple Linear Regression

Independent two groups t-test similar to PROC TTEST with summarized input

Standard Error of Skewness

Sum of Square with a Given Contrast Set

White's Model Specification Test

Test Type III SS using error term other than MSE

Relative Risk of the two groups

Correlation test by Fisher's Z transformation

Geometric Coefficient of Variation in percentage

Type III Expected Mean Square Formula

Geometric Mean without NA

Confidence interval with the last Z-value for the group sequential design

Convert some columns of a data.frame to factors

Score Confidence Interval for a Proportion or a Binomial Distribution

F-Test for the ratio of two groups' variances

Independent two means test similar to t.test with summarized input

Test for the difference of two groups' means

Get a Contrast Matrix for Type I SS

Get a Contrast Matrix for Type II SS

Simple Linear Regressions with Each Independent Variable

ANOVA with Type I SS

Diagnostic Plot for Regression

Estimability Check

Generalized type 2 inverse matrix, g2 inverse

Linear Regression with g2 inverse

Regression of Conventional Way with Rich Diagnostics

Estimate Linear Functions

Residual Diagnostic Plot for Regression

Get a Contrast Matrix for Type III SS

Beautify the output of knitr::kable

Table Summary 0 independent(x) variable

An example data for meta-analysis - aspirin in coronary heart disease

'SAS' Linear Model

Table Summary 2 independent(x) variables

Satterthwaite Approximation of Variance and Degree of Freedom

Sequential bounds for cumulative Z-test in Group Sequential Design

Table Summary 1 independent(x) variable

Table Summary 3 independent(x) variables

Correlation test of multiple numeric columns

Confidence Interval Estimation

F Test with a Set of Contrasts

An Example Data of Bioequivalence Study

Analysis BY variable

Plot Pairwise Differences

Collinearity Diagnostics

Coefficient of Variation in percentage

Expected Mean Square Formula

General Linear Model similar to SAS PROC GLM

Generalized inverse matrix of type 2 for linear regression

Cumulative Alpha for the Fixed Z-value

Exit Probability with cumulative Z-test in Group Sequential Design

Drift defined by Lan and DeMets for Group Sequential Design

Internal Functions