# Summarize Results by Group Get adjusted totals and prevalences for provided variables, grouped by specified variables. ```r summarize_results_by_group( df, vars, group_vars, weight_col = NULL, id_col = NULL, strata_col = NULL, label = NULL ) ``` ## Arguments - `df`: data.frame with sample and weights (if using a survey design) - `vars`: string vector of variables to calculate prevalences for - `group_vars`: string vector of variables to group by - `weight_col`: string specifying the column with weights, "nhis" or nhis survey design, or NULL for unweighted - `id_col`: string specifying the column with IDs for cluster-aware standard error (SE) calculations - `strata_col`: string specifying the column with strata for cluster-aware SE calculations - `label`: string label for weighting method ## Returns data.frame with totals, means, and standard errors (if using a survey design) ## Details TODO: Merge into regular summarize_results function ## Examples ```r # Prepare the NHIS data calVars <- c( "SEX_A_R", "AGEP_A_R", "HISPALLP_A_R", "ORIENT_A_R", "HICOV_A_R", "EDUCP_A_R", "REGION_R", "EMPLASTWK_A_R", "HOUTENURE_A_R", "MARITAL_A_R" ) stuVars <- "DIBTYPE_A_R" vars_dummies <- c("AGEP_A_R","HISPALLP_A_R","EDUCP_A_R","REGION_R") nhis_keep_vars <- c("PPSU","PSTRAT","WTFA_A") nhis_imputed <- impute_data(nhis_processed, c(calVars, stuVars), nhis_keep_vars) nhis_dummied <- dummies(nhis_imputed, vars=paste0(vars_dummies, '_I')) factor_vars <- setdiff(names(nhis_dummied), nhis_keep_vars) nhis_dummied[factor_vars] <- lapply(nhis_dummied[factor_vars], as.factor) # Prepare the synthetic All of Us data aou_imputed <- impute_data(aou_synthetic, c(calVars, stuVars)) aou_dummied <- dummies(aou_imputed, vars=paste0(vars_dummies, '_I')) aou_dummied[] <- lapply(aou_dummied, as.factor) # Calculate IPW weights using NHIS data and applied to All of Us weights_df <- calculate_weights( nhis_dummied, aou_dummied, 'ipw', paste0(calVars, '_I'), paste0(stuVars, '_I'), weight='WTFA_A', strata='PSTRAT', psu='PPSU' ) # Get IPW results by group ipw_outcome_df <- summarize_results_by_group( weights_df, paste0(stuVars, '_I'), paste0(calVars, '_I'), weight_col='ipw_weight', label='AoU: IPW' ) ```

summarize_results_by_group function