## ----setup, include=FALSE----------------------------------------------------- library(knitr) library(tidyr) library(dplyr) library(whomds) opts_chunk$set(warning=FALSE, message=FALSE, eval=FALSE, out.width = "80%", fig.align = "center", collapse = TRUE, comment = "#>", survey.lonely.psu = "adjust") ## ----join-example------------------------------------------------------------- # library(tidyverse) # new_score <- read_csv("Data_final.csv") %>% # select(c("ID", "rescaled")) # merged_data <- original_data %>% # left_join(new_score) %>% # rename("DisabilityScore" = "rescaled") ## ----table-weightedpct-example1, eval=TRUE------------------------------------ #Remove NAs from column used for argument by_vars df_adults_noNA <- df_adults %>% filter(!is.na(disability_cat)) table_weightedpct( df = df_adults_noNA, vars_ids = "PSU", vars_strata = "strata", vars_weights = "weight", formula_vars = paste0("EF", 1:12), formula_vars_levels = 1:5, by_vars = "disability_cat", spread_key = NULL, spread_value = "prop", arrange_vars = NULL, willfilter = NULL ) ## ----table-weightedpct-example2, eval=TRUE------------------------------------ table_weightedpct( df = df_adults_noNA, vars_ids = "PSU", vars_strata = "strata", vars_weights = "weight", formula_vars = paste0("EF", 1:12), formula_vars_levels = 1:5, by_vars = "disability_cat", spread_key = "disability_cat", spread_value = "prop", arrange_vars = NULL, willfilter = NULL ) ## ----table-weightedpct-example3, eval=TRUE------------------------------------ table_weightedpct( df = df_adults_noNA, vars_ids = "PSU", vars_strata = "strata", vars_weights = "weight", formula_vars = paste0("EF", 1:12), formula_vars_levels = 1:5, by_vars = "disability_cat", spread_key = "disability_cat", spread_value = "prop", arrange_vars = NULL, willfilter = TRUE, resp == 5 ) ## ----table-weightedpct-example4, eval=TRUE------------------------------------ table_weightedpct( df = df_adults_noNA, vars_ids = "PSU", vars_strata = "strata", vars_weights = "weight", formula_vars = paste0("EF", 1:12), formula_vars_levels = 1:5, by_vars = c("disability_cat", "sex"), spread_key = "disability_cat", spread_value = "prop", arrange_vars = NULL, willfilter = TRUE, resp == 5 ) ## ----table-weightedpct-example5, eval=TRUE------------------------------------ table_weightedpct( df = df_adults_noNA, vars_ids = "PSU", vars_strata = "strata", vars_weights = "weight", formula_vars = paste0("EF", 1:12), formula_vars_levels = 1:5, by_vars = c("disability_cat", "sex"), spread_key = "resp", spread_value = "prop", arrange_vars = NULL, willfilter = FALSE, disability_cat, sex, item, problems = `4`+`5` ) ## ----table-weightedpct-example5b, eval=TRUE----------------------------------- table_weightedpct( df = df_adults_noNA, vars_ids = "PSU", vars_strata = "strata", vars_weights = "weight", formula_vars = paste0("EF", 1:12), formula_vars_levels = 1:5, by_vars = c("disability_cat", "sex"), spread_key = "resp", spread_value = "prop", arrange_vars = NULL, willfilter = FALSE, disability_cat, sex, item, problems = `4`+`5` ) %>% pivot_wider(names_from = disability_cat, values_from = problems) ## ----table-unweightedpctn-example, eval=TRUE---------------------------------- table_unweightedpctn(df_adults_noNA, vars_demo = c("sex", "age_cat", "work_cat", "edu_cat"), group_by_var = "disability_cat", spread_by_group_by_var = TRUE) ## ----table-basicstats-example, eval=TRUE-------------------------------------- table_basicstats(df_adults_noNA, "HHID", "age_cat") ## ----plot-pop-pyramid, eval=TRUE, echo=FALSE---------------------------------- include_graphics("Images/pop_pyramid.png") ## ----plot-distribution, eval=TRUE, echo=FALSE--------------------------------- include_graphics("Images/distribution.png") ## ----plot-density, eval=TRUE, echo=FALSE-------------------------------------- include_graphics("Images/density.png")