R: Utilities for Streamlined Data Import, Imputation and Modelling

# Utilities for Streamlined Data Import, Imputation and Modelling

## Documentation for package ‘basecamb’ version 1.1.5

- DESCRIPTION file
- Package README

## Help Pages

.scale_variable | Scaling a variable
apply_data_dictionary | Clean column names, types and levels
apply_function_to_imputed_data | Apply function to dataframes in a mice object
assign_factorial_levels | Assign custom values for key levels in factorial columns
assign_types_names | Assign tidy types and names to a data.frame
build_model_formula | Build formula for statistical models
cox.zph.mids | Test cox proportional odds assumption on models using multiple imputation.
deconstruct_formula | Deconstruct formula
filter_nth_entry | Filter dataframe for nth entry
fit_mult_impute_obs_outcome | Fit a model on multiply imputed data using only observations with non-missing outcome(s)
or_model_summary | Summarise a logistic regression model on the odds ratio scale
parse_date_columns | Parse values in date columns as Dates
quantile_group | Stratify a numeric vector into quantile groups
remove_duplicates | Remove duplicate rows from data.frame
remove_missing_from_mids | Remove missing cases from a mids object
scale_continuous_predictors | Scale continuous predictors
setduplicates | Identify duplicate values in a vector representing a set
stratified_boxcox | Box-Cox transformation for stratified data