Generate regression results tables and plots in final format for publication. Explore models and export directly to PDF and 'Word' using 'RMarkdown'.
The finalfit
package provides functions that help you quickly create elegant final results tables and plots when modelling in R. These can easily be exported as Word documents, PDFs, or html files.
Its design follows Hadley Wickham's tidy tool manifesto.
In addition, it provides functions for identifying and handling missing data, together with a number of functions to bootstrap simulate regression model results.
You can install finalfit
from CRAN:
install.packages("finalfit")
It is recommended that this package is used together with dplyr
which can be installed via:
install.packages("dplyr")
The package documentation is maintained independently at finalfit.org.
or_plot()
bug fixff_remove_ref()
added. #12glmmixed()
and lmmixed()
now support random gradient models, and all complex lme4
specifications.ff_plot()
addedcoefficient_plot()
addedvariable_type()
addedshinyfit
started.ff_relabel()
added.finalfit()
for not-allowed colons (:) in factor levels. #10ff_glimpse()
re-written to remove psych
dependencymissing_glimpse()
added: single data frame describing all variables and missing valuesff_interaction()
added: create variable for an interaction between two factorsff_label()
added: easily add label to variable in dataframeff_newdata()
modified to take dataframe without requirement for dependent and explanatory argumentssummary_factorlist()
modified to allow user to change number of unique factor levels at which a variable a continuous variable is converted to a factor (cont_cut
). #9fit2df()
and its internal function extract_fit
modified to take confint_type
and confint_level
.missing_predictorMatrix()
added for use with mice
lmuni()
, lmmulti()
, lmmixed()
, glmuni()
, glmmulti()
, glmmixed()
, coxphuni()
, coxphmulti()
metrics_hoslem()
is the first of a number of 'metrics' functions which will be introduced.