R: Quickly Create Elegant Regression Results Tables and Plots when Modelling

# Quickly Create Elegant Regression Results Tables and Plots when Modelling

## Documentation for package ‘finalfit’ version 1.1.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

B C D E F G H L M O P R S W

## -- B --

boot_compare | Compare bootstrapped distributions
boot_predict | Bootstrap simulation for model prediction

## -- C --

check_recode | Check accurate recoding of variables
coefficient_plot | Produce a coefficient table and plot
colon_s | Chemotherapy for Stage B/C colon cancer
coxphmulti | Cox proprotional hazards multivariable models: 'finalfit' model wrapper
coxphuni | Cox proprotional hazards univariable models: 'finalfit' model wrapper
crrmulti | Competing risks multivariable regression: 'finalfit' model wrapper
crruni | Competing risks univariable regression: 'finalfit' model wrapper

## -- D --

dependent_label | Make a label for the dependent variable

## -- E --

extract_variable_label | Extract variable labels from dataframe

## -- F --

ff_column_totals | Add column totals to 'summary_factorlist()' output
ff_expand | Summarise with mode and mean/median and expand given factors
ff_formula | Generate formula as character string
ff_glimpse | Descriptive statistics for dataframe
ff_interaction | Make an interaction variable and add to dataframe
ff_label | Label a variable
ff_merge | Merge a 'summary_factorlist()' table with any number of model results tables.
ff_metrics | Generate common metrics for regression model results
ff_metrics.coxph | Generate common metrics for regression model results
ff_metrics.coxphlist | Generate common metrics for regression model results
ff_metrics.glm | Generate common metrics for regression model results
ff_metrics.glmerMod | Generate common metrics for regression model results
ff_metrics.glmlist | Generate common metrics for regression model results
ff_metrics.lm | Generate common metrics for regression model results
ff_metrics.lmerMod | Generate common metrics for regression model results
ff_metrics.lmlist | Generate common metrics for regression model results
ff_mode | Return the most frequent level in a factor
ff_newdata | Generate newdata for simulations
ff_parse_formula | Parse a formula to finalfit grammar
ff_percent_only | Include only percentages for factors in 'summary_factorlist' output
ff_permute | Permuate explanatory variables to produce multiple output tables for common regression models
ff_plot | Produce a table and plot
ff_relabel | Relabel variables in a data frame
ff_relabel_df | Relabel variables from data frame after tidyverse functions
ff_remove_p | Remove p-value from output
ff_remove_ref | Remove regression reference level row from table
ff_row_totals | Add row totals to 'summary_factorlist()' output
ff_stratify_helper | Help making stratified summary_factorlist tables
finalfit | Final output tables for common regression models
finalfit.coxph | Final output tables for common regression models
finalfit.glm | Final output tables for common regression models
finalfit.lm | Final output tables for common regression models
finalfit_column_totals | Add column totals to 'summary_factorlist()' output
finalfit_expand | Summarise with mode and mean/median and expand given factors
finalfit_formula | Generate formula as character string
finalfit_glimpse | Descriptive statistics for dataframe
finalfit_interaction | Make an interaction variable and add to dataframe
finalfit_label | Label a variable
finalfit_merge | Merge a 'summary_factorlist()' table with any number of model results tables.
finalfit_mode | Return the most frequent level in a factor
finalfit_newdata | Generate newdata for simulations
finalfit_percent_only | Include only percentages for factors in 'summary_factorlist' output
finalfit_permute | Permuate explanatory variables to produce multiple output tables for common regression models
finalfit_plot | Produce a table and plot
finalfit_relabel | Relabel variables in a data frame
finalfit_relabel_df | Relabel variables from data frame after tidyverse functions
finalfit_remove_p | Remove p-value from output
finalfit_remove_ref | Remove regression reference level row from table
finalfit_row_totals | Add row totals to 'summary_factorlist()' output
fit2df | Extract model fit results to dataframe (generic): 'finalfit' model extractors
fit2df.coxme | Extract model fit results to dataframe (generic): 'finalfit' model extractors
fit2df.coxph | Extract model fit results to dataframe (generic): 'finalfit' model extractors
fit2df.coxphlist | Extract model fit results to dataframe (generic): 'finalfit' model extractors
fit2df.crr | Extract model fit results to dataframe (generic): 'finalfit' model extractors
fit2df.crrlist | Extract model fit results to dataframe (generic): 'finalfit' model extractors
fit2df.glm | Extract model fit results to dataframe (generic): 'finalfit' model extractors
fit2df.glmboot | Extract model fit results to dataframe (generic): 'finalfit' model extractors
fit2df.glmerMod | Extract model fit results to dataframe (generic): 'finalfit' model extractors
fit2df.glmlist | Extract model fit results to dataframe (generic): 'finalfit' model extractors
fit2df.lm | Extract model fit results to dataframe (generic): 'finalfit' model extractors
fit2df.lmerMod | Extract model fit results to dataframe (generic): 'finalfit' model extractors
fit2df.lmlist | Extract model fit results to dataframe (generic): 'finalfit' model extractors
fit2df.mipo | Extract model fit results to dataframe (generic): 'finalfit' model extractors
fit2df.stanfit | Extract model fit results to dataframe (generic): 'finalfit' model extractors
fit2df.svyglmlist | Extract model fit results to dataframe (generic): 'finalfit' model extractors
format_n_percent | Format n and percent as a character

## -- G --

glmmixed | Mixed effects binomial logistic regression models: 'finalfit' model wrapper
glmmulti | Binomial logistic regression multivariable models: 'finalfit' model wrapper
glmmulti_boot | Binomial logistic regression multivariable models with bootstrapped confidence intervals: 'finalfit' model wrapper
glmuni | Binomial logistic regression univariable models: 'finalfit' model wrapper

## -- H --

hr_plot | Produce a hazard ratio table and plot

## -- L --

labels_to_column | Labels to column names
labels_to_level | Labels to level
lmmixed | Mixed effects linear regression models: 'finalfit' model wrapper
lmmulti | Linear regression multivariable models: 'finalfit' model wrapper
lmuni | Linear regression univariable models: 'finalfit' model wrapper

## -- M --

metrics_hoslem | Hosmer-Lemeshow goodness of fit test
missing_compare | Compare missing data
missing_glimpse | Summary of missing values
missing_pairs | Missing values pairs plot
missing_pattern | Characterise missing data for 'finalfit' models
missing_plot | Missing values occurrence plot
missing_predictorMatrix | Create predictorMatrix for use with mice

## -- O --

or_plot | Produce an odds ratio table and plot

## -- P --

p_tidy | Round p-values but keep trailing zeros

## -- R --

rm_duplicates | Remove duplicates and replace
rm_empty_block | Remove rows where all specified variables are missing
round_tidy | Round values but keep trailing zeros

## -- S --

summary_df | Summarise with mode for factors and mean/median for numeric variables
summary_factorlist | Summarise a set of factors (or continuous variables) by a dependent variable
summary_factorlist_stratified | Summarise a set of factors (or continuous variables) by a dependent variable
surv_plot | Plot survival curves with number-at-risk table
svyglmmulti | Multivariable survey-weighted generalised linear models
svyglmuni | Univariable survey-weighted generalised linear models

## -- W --

wcgs | Western Collaborative Group Study