Learn R Programming

tlm

Variables in regression models are frequently transformed to achieve homogeneity of variance, normality of errors, linearization of associations, or a more homogeneous distribution of predictors. This package is a tool to fit linear, logistic, and Poisson regression models with logarithmic or power transformations. The package also show how to report and interpret effects in the original scale of the variables.

Getting started

  • The last version released on CRAN can be installed within an R session by executing:
install.packages("tlm")
  • The package tlm is available on the Comprehensive R Archive Network (CRAN), with info at the related web page https://CRAN.R-project.org/package=tlm.

  • Once the package has been installed, a summary of the main functions is available by executing:

help(package = "tlm")
  • A comprehensive tutorial, including a number of detailed examples, is available by executing:
vignette("tlm")

References

The methodology used in the package is described in

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Version

Install

install.packages('tlm')

Monthly Downloads

306

Version

0.2.0

License

GPL (>= 3)

Maintainer

Jose Barrera-Gomez

Last Published

January 7th, 2025

Functions in tlm (0.2.0)

glucose

Glucose and Triglycerides Levels in Blood
summary.tlm

Summarizing the Model Fitting
MY

Expected Adjusted Median or Generalized Mean
effectInfo

Interpretation of Effects in Linear, Logistic and Poisson Models with Transformed Variables
effect

Effects Estimate in Linear, Logistic and Poisson Regression Models with Transformed Variables
tlm

Fitting, Reporting and Visualizing Linear, Logistic and Poisson Regression Models with Transformed Variables
cotinine

Birth Weight and Cord Serum Cotinine
feld1

Cat Allergen Concentrations
imt

Intima Media Thickness of the Carotid Artery
tlm-package

tlm: Effects under Linear, Logistic and Poisson Regression Models with Transformed Variables