Calculate totals from complex survey data. A wrapper around svytotal. survey_total should always be called from summarise.

survey_total(
  x,
  na.rm = FALSE,
  vartype = c("se", "ci", "var", "cv"),
  level = 0.95,
  deff = FALSE,
  df = NULL,
  ...
)

Arguments

x

A variable or expression, or empty

na.rm

A logical value to indicate whether missing values should be dropped

vartype

Report variability as one or more of: standard error ("se", default), confidence interval ("ci"), variance ("var") or coefficient of variation ("cv").

level

A single number or vector of numbers indicating the confidence level

deff

A logical value to indicate whether the design effect should be returned.

df

(For vartype = "ci" only) A numeric value indicating the degrees of freedom for t-distribution. The default (NULL) uses degf, but Inf is the usual survey package's default.

...

Ignored

Examples

library(survey) data(api) dstrata <- apistrat %>% as_survey_design(strata = stype, weights = pw) dstrata %>% summarise(enroll_tot = survey_total(enroll), tot_meals = survey_total(enroll * meals / 100, vartype = c("ci", "cv")))
#> # A tibble: 1 × 6 #> enroll_tot enroll_tot_se tot_meals tot_meals_low tot_meals_upp tot_meals_cv #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 3687178. 117319. 1753775. 1528167. 1979384. 0.0652
dstrata %>% group_by(awards) %>% summarise(api00 = survey_total(enroll))
#> # A tibble: 2 × 3 #> awards api00 api00_se #> <fct> <dbl> <dbl> #> 1 No 1627217. 147847. #> 2 Yes 2059960. 143734.
# Leave x empty to calculate the total in each group dstrata %>% group_by(awards) %>% summarise(pct = survey_total())
#> # A tibble: 2 × 3 #> awards pct pct_se #> <fct> <dbl> <dbl> #> 1 No 2236. 216. #> 2 Yes 3958. 216.
# level takes a vector for multiple levels of confidence intervals dstrata %>% summarise(enroll = survey_total(enroll, vartype = "ci", level = c(0.95, 0.65)))
#> # A tibble: 1 × 5 #> enroll enroll_low95 enroll_upp95 enroll_low65 enroll_upp65 #> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 3687178. 3455815. 3918540. 3577271. 3797084.
# Note that the default degrees of freedom in srvyr is different from # survey, so your confidence intervals might not exactly match. To # replicate survey's behavior, use df = Inf dstrata %>% summarise(srvyr_default = survey_total(api99, vartype = "ci"), survey_defualt = survey_total(api99, vartype = "ci", df = Inf))
#> # A tibble: 1 × 6 #> srvyr_default srvyr_default_low srvyr_default_upp survey_defualt #> <dbl> <dbl> <dbl> <dbl> #> 1 3898472. 3775136. 4021807. 3898472. #> # … with 2 more variables: survey_defualt_low <dbl>, survey_defualt_upp <dbl>
comparison <- survey::svytotal(~api99, dstrata) confint(comparison) # survey's default
#> 2.5 % 97.5 % #> api99 3775894 4021049
confint(comparison, df = survey::degf(dstrata)) # srvyr's default
#> 2.5 % 97.5 % #> api99 3775136 4021807