# calculate_group_frequency: Calculate group frequency for all unique combinations In AJFOWLER/comorbidgroupr: Identify Groups of Comorbid Diseases Associated with Outcomes

## Description

Generate an ordered data.frame of different disease combinations on the basis of the most frequent or most strongly associated with outcomes.

## Usage

 ```1 2 3 4 5 6 7 8``` ```calculate_group_frequency( unique_combinations, all_diseases, outcome_positions, min_freq = 0, tots, use_outcome = FALSE ) ```

## Arguments

 `unique_combinations` List of unique combinations of disease positions for a given number of combinations, generated using `unique_combos`. `all_diseases` List of positions associated with each disease, generated using `get_disease_counts()`. `outcome_positions` Numeric vector where each element refers to a record that suffered a particular outcome. `min_freq` Number between 0 and 1; minimum proportion of code combinations to be included in the stem. If `outcome_column` is passed, `min_freq` is the minimum event rate per combination to be considered. `tots` Numeric, total length of `comorbid_column` initially profiled to calculate frequency proportions to compare against `min_freq`. `use_outcome` Logical if to use outcome variable for stem generation.

## Value

data.frame ordered from lowest to highest proportion of those suffering outcomes (if `outcome_positions` entered) or number of records associated with that combination (if no `outcome_positions` entered).

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```disease_counts = list(c(1), c(1,4), c(1,2,3,4), c(1)) unique_pos = structure(c(1, 1, 1, 2, 2, 3, 2, 3, 4, 3, 4, 4), .Dim = c(6L, 2L)) calculate_group_frequency(unique_combinations = unique_pos, all_diseases = disease_counts, outcome_positions = 0, tots = 4) calculate_group_frequency(unique_combinations = unique_pos, all_diseases = disease_counts, outcome_positions = c(0,1,1,0), tots = 4) ```

AJFOWLER/comorbidgroupr documentation built on April 8, 2021, 3:51 a.m.