ParaAnita

R Functions for Binary and Binomial Data Analysis

Author: Mark C. Eisler

eMail: Mark.Eisler@bristol.ac.uk

ORCID = 0000-0001-6843-3345

Installation

You can install the development version of ParaAnita from GitHub with:

# install.packages("devtools")
devtools::install_github("Mark-Eis/ParaAnita")

ParaAnita Package Description: –

The ParaAnita R package includes functions intended to address and simplify a number of issues commonly encountered during binary (Bernoulli) and binomial data analysis using generalised linear models. More specifically, ParaAnita does the following: –

• Creates contingency tables with contingency_table(), xcontingency_table().

• Summarises binary (Bernoulli) and binomial proportion data in contingency tables with as_binom_contingency(), binom_contingency().

• Calculates odds ratios, their confidence intervals and associated probabilities with odds_ratio().

• Gets, sets or removes the contrasts attribute for selected categorical variables (factors) within data with get_contrasts(), get_contr_data(), set_contrasts(), set_contrasts<-(), set_contr_treat() and set_contr_treat<-().

• Gets, sets and manipulates categorical variable contrast names with contr_colnames(), contr_colnames<-(), contr_colpfx<-(), helm_names() and helm_names<-().

• Compares related generalised linear models using various measures with anova_tbl(), comp_glm(), summanov() and univ_anova().

• Collates model results and standard errors, with optional grouping of levels of selected categorical variables, in a format convenient for plotting with glm_plotlist() and glm_plotdata(), and plots these in individual or faceted plots with ggplot.glm_plotdata() and var_labs().

• Adds, modifies, removes or selects factors in data with add_grps(), drop_null(), drop_zero(), expl_fcts(), fct_to_num(), and good_levels().

• Simulates Bernoulli and binomial proportion data sets with categorical explanatory variables with bernoulli_data() and binom_data().

• Simplifies statistical analysis with chsqfish() and starsig().

• Provides auxiliary print functions and prints objects derived from ParaAnita S3 methods with announce(), lf(), print_all() and print_lf().

• Tidies up the R workspace with rm_objects().

• Includes the dataset: budworm, from David Collett (1991). Modelling Binary Data. London: Chapman & Hall.