Handling an Inconsistently Coded Categorical Variable in a Longitudinal Dataset
Getting frequencies from a vector with an optional multiplier
Transforming a mapping (transition) table to two associative lists
Summary plots for cat2cat results
Pruning which could be useful after the mapping process
Resolve the frequencies
Adjusted summary for linear regression when based on replicated datase...
Validate if the trans table contains all proper mappings
Applying frequencies to the object returned by the get_mappings func...
Automatic mapping in a panel dataset
Manual mapping for an aggregated panel dataset
The internal function used in the cat2cat one
Function to check cat2cat ml models performance
Make a combination of weights from different methods
Add default cat2cat columns to a data.frame
Unifying an inconsistently coded categorical variable between two different time points in accordance with a mapping table. The main rule is to replicate the observation if it could be assigned to a few categories. Then using frequencies or statistical methods to approximate the probabilities of being assigned to each of them. This procedure was invented and implemented in the paper by Nasinski, Majchrowska, and Broniatowska (2020) <doi:10.24425/cejeme.2020.134747>.
Useful links