## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set(echo = TRUE, results = TRUE, warning = FALSE, message = FALSE, comment = "", collapse = FALSE, class.source = "bg-success", class.output = "bg-warning") ## ----setup-------------------------------------------------------------------- library(healthequal) require(dplyr) ## ----------------------------------------------------------------------------- data(OrderedSample) head(OrderedSample, n = 4) ## ----------------------------------------------------------------------------- data(NonorderedSample) head(NonorderedSample, n = 4) ## ----------------------------------------------------------------------------- data(OrderedSampleMultipleind) head(OrderedSampleMultipleind, n = 4) ## ----------------------------------------------------------------------------- data(NonorderedSampleMultipleind) head(NonorderedSampleMultipleind, n = 4) ## ----------------------------------------------------------------------------- ?healthequal::OrderedSample ?healthequal::NonorderedSample ?healthequal::OrderedSampleMultipleind ?healthequal::NonorderedSampleMultipleind ?healthequal::IndividualSample ## ----------------------------------------------------------------------------- ?aci ## ----------------------------------------------------------------------------- with(OrderedSample, aci(est = estimate, subgroup_order = subgroup_order, pop = population)) ## ----------------------------------------------------------------------------- ?sii ## ----------------------------------------------------------------------------- with(IndividualSample, aci(est = sba, subgroup_order = subgroup_order, weight = weight, psu = psu, strata = strata)) ## ----------------------------------------------------------------------------- with(NonorderedSample, bgv(est = estimate, se = se, pop = population)) ## ----------------------------------------------------------------------------- head(NonorderedSampleMultipleind, n = 4) unique(NonorderedSampleMultipleind$indicator) ## ----------------------------------------------------------------------------- library(dplyr) measures <- NonorderedSampleMultipleind %>% dplyr::group_by(indicator) %>% dplyr::summarize(covar(est = estimate, se = se, pop = population, scaleval = indicator_scale)) as.data.frame(measures) ## ----------------------------------------------------------------------------- multiplemeasures <- NonorderedSampleMultipleind %>% dplyr::group_by(indicator, dimension) %>% dplyr::summarize( covar = covar(est = estimate, se = se, pop = population, scaleval = indicator_scale), bgv = bgv(est = estimate, se = se, pop = population)) # It is possible to extract the measures separately multiplemeasures$covar multiplemeasures$bgv