person(given = "Patrick",
family = "Schratz",
role = c("aut", "cre"),
email = "patrick.schratz@gmail.com",
comment = c(ORCID = "0000-0003-0748-6624"))
Simplified odds ratio calculation of GAM(M)s &
GLM(M)s.  Provides structured output (data frame) of all predictors
and their corresponding odds ratios and confident intervals for
further analyses.  It helps to avoid false references of predictors
and increments by specifying these parameters in a list instead of
using 'exp(coef(model))' (standard approach of odds ratio calculation
for GLMs) which just returns a plain numeric output.  For GAM(M)s,
odds ratio calculation is highly simplified with this package since it
takes care of the multiple 'predict()' calls of the chosen predictor
while holding other predictors constant.  Also, this package allows
odds ratio calculation of percentage steps across the whole predictor
distribution range for GAM(M)s.  In both cases, confident intervals
are returned additionally.  Calculated odds ratio of GAM(M)s can be
inserted into the smooth function plot.
ggplot2 (>= 3.0.0), mgcv, stats, stringr, tibble
cowplot, gam, grid, gtable, knitr, MASS, rmarkdown, scales,
testthat

Simplified odds ratio calculation of GAM(M)s &
GLM(M)s. Provides structured output (data frame) of all predictors and
their corresponding odds ratios and confident intervals for further
analyses.  It helps to avoid false references of predictors and
increments by specifying these parameters in a list instead of using
'exp(coef(model))' (standard approach of odds ratio calculation for
GLMs) which just returns a plain numeric output.  For GAM(M)s, odds
ratio calculation is highly simplified with this package since it
takes care of the multiple 'predict()' calls of the chosen predictor
while holding other predictors constant. Also, this package allows
odds ratio calculation of percentage steps across the whole predictor
distribution range for GAM(M)s.  In both cases, confident intervals
are returned additionally. Calculated odds ratio of GAM(M)s can be
inserted into the smooth function plot.