# reproduces part of the analysis using the survey package
check_with_survey <- function(input,
sampling_weights = NULL,
cluster = NULL,
strata = NULL) {
expect_warning(
res <- anthroplus_prevalence(
input$sex,
input$agemons,
input$oedema,
input$height,
input$weight,
sw = sampling_weights,
cluster = cluster,
strata = strata
), "excluded"
)
zscores <- anthroplus_zscores(
input$sex,
input$agemons,
input$oedema,
input$height,
input$weight
)
zscores <- cbind(zscores, input)
sw <- if (!is.null(sampling_weights)) {
zscores$sw <- sampling_weights
~sw
}
cluster <- if (!is.null(cluster)) {
zscores$cluster <- cluster
~cluster
} else {
~1
}
strata <- if (!is.null(strata)) {
zscores$strata <- strata
~strata
}
zscores <- zscores[zscores$agemons <= 228, ]
design <- survey::svydesign(
id = cluster, data = zscores,
weights = sw, strata = strata, nest = TRUE
)
expected <- survey::svyby(~zhfa, ~sex, design, survey::svymean,
na.rm = TRUE,
na.rm.all = TRUE,
drop.empty.groups = FALSE
)
expect_equal(rev(res$HA_r[2:3]), expected$zhfa)
expect_equal(rev(res$HA_se[2:3]), expected$se)
}
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