calc_hcd_mean: Calculate Mean Perceived Health Care Discrimination Score

In AOUSDOHtools: Analyzing AOU SDOH Survey Data

Calculate Mean Perceived Health Care Discrimination Score

Description

This function creates a numeric score (range 1-5) that reflects the mean level of perceived discrimination in health care based on responses to seven specific survey items. Higher scores indicate greater perceived discrimination in health care.

Usage

calc_hcd_mean(survey_df)

Arguments

survey_df

A data frame containing survey data with at least three columns: 'person_id', 'question_concept_id', and 'answer_concept_id'.

Value

A data frame with two columns: 'person_id' and 'hcd_mean', where 'hcd_mean' represents the mean level of perceived discrimination in health care. Participants who did not respond to all 7 items will have an NA value for 'hcd_mean'.

Examples

# Create a sample survey data frame
survey_df <- data.frame(
  person_id = rep(1:3, each = 7),
  question_concept_id = rep(c(40192383, 40192394, 40192423, 40192425,
                              40192497, 40192503, 40192505), times = 3),
  answer_concept_id = sample(c(40192465, 40192481, 40192429, 40192382, 40192515),
                             21, replace = TRUE)
)

# Compute mean perceived health care discrimination scores
hcd_mean_scores <- calc_hcd_mean(survey_df)
head(hcd_mean_scores)

AOUSDOHtools documentation built on April 3, 2025, 8:11 p.m.