Man pages for basecamb
Utilities for Streamlined Data Import, Imputation and Modelling
| 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... |
| deconstruct_formula | Deconstruct formula |
| dot-find_NA_coercions | Locate NA values introduced during apply_data_dictionary() |
| dot-parse_string_to_named_vector | Parse a string to create a named list |
| dot-scale_variable | Scaling a variable |
| filter_nth_entry | Filter dataframe for nth entry |
| fit_mult_impute_obs_outcome | Fit a model on multiply imputed data using only observations... |
| 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 |
