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 withget_contrasts()
,get_contr_data()
,set_contrasts()
,set_contrasts<-()
,set_contr_treat()
andset_contr_treat<-()
.Gets, sets and manipulates categorical variable contrast
names
withcontr_colnames()
,contr_colnames<-()
,contr_colpfx<-()
,helm_names()
andhelm_names<-()
.Compares related generalised linear models using various measures with
anova_tbl()
,comp_glm()
,summanov()
anduniv_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()
andglm_plotdata()
, and plots these in individual or faceted plots withggplot.glm_plotdata()
andvar_labs()
.Adds, modifies, removes or selects factors in data with
add_grps()
,drop_null()
,drop_zero()
,expl_fcts()
,fct_to_num()
, andgood_levels()
.Simulates Bernoulli and binomial proportion data sets with categorical explanatory variables with
bernoulli_data()
andbinom_data()
.Simplifies statistical analysis with
chsqfish()
andstarsig()
.Provides auxiliary print functions and prints objects derived from ParaAnita S3 methods with
announce()
,lf()
,print_all()
andprint_lf()
.Tidies up the R workspace with
rm_objects()
.Includes the dataset:
budworm
, from David Collett (1991). Modelling Binary Data. London: Chapman & Hall.