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https://github.com/anestistouloumis/geer

Solving generalized estimating equations with or without an adjustment vector

https://github.com/anestistouloumis/geer

Science Score: 26.0%

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Repository

Solving generalized estimating equations with or without an adjustment vector

Basic Info
  • Host: GitHub
  • Owner: AnestisTouloumis
  • Language: C++
  • Default Branch: master
  • Size: 138 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created almost 3 years ago · Last pushed 10 months ago
Metadata Files
Readme

README.md

R-CMD-check <!-- badges: end --> <!-- badges: start --> Codecov test coverage <!-- badges: end -->

Installation

You can install the development version of geer:

``` r

install.packages('devtools')

devtools::install_github("AnestisTouloumis/geer") ```

The source code for the development version of geer is available on github at:

To use geer, you should load the package as follows:

``` r library("geer")

> Loading required package: gnm

```

Usage

This package provides a generalized estimating equations (GEE) solver for fitting marginal regression models with or without an adjustment vector.

There are two core functions to fit GEE models:

  • geewa for fitting GEE models with correlated responses. Options for estimation process include the ordinary GEE, bias-reduced or -corrected GEE and penalized GEE,
  • geewa_binary for fitting GEE models with correlated binary responses. Options for estimation process include the ordinary GEE, bias-reduced or -corrected GEE and penalized GEE.

The main arguments in both functions are:

  • an optional data frame (data),
  • a model formula (formula),
  • a cluster identifier variable (id),
  • an optional vector that identifies the order of the observations within each cluster (repeated).

There are also five useful utility functions:

  • confint for obtaining Wald–type confidence intervals for the regression parameters using the standard errors of the sandwich or of the bias-corrected or of the model–based covariance matrix. The default option is the sandwich covariance matrix,
  • waldts for assessing the goodness-of-fit of two nested GEE models based on a Wald test statistic,
  • score_test for assessing the goodness-of-fit of two nested GEE models based on a score test statistic,
  • vcov for obtaining the sandwich, bias-corrected or model–based covariance matrix of the regression parameters,
  • gee_criteria for reporting commonly used criteria to select variables and/or association structure for GEE models.

Owner

  • Name: Anestis Touloumis
  • Login: AnestisTouloumis
  • Kind: user
  • Location: Brighton, UK
  • Company: University of Brighton

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Dependencies

DESCRIPTION cran
  • R >= 2.10 depends
  • Rcpp >= 1.0.9 imports
  • brglm2 * imports
  • testthat >= 3.0.0 suggests
.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v3 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
  • r-lib/actions/setup-tinytex v2 composite