Aliases: survey_total
Keywords:
### ** 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