View source: R/survey_statistics.r
survey_old_quantile | R Documentation |
Calculate quantiles from complex survey data. A wrapper
around oldsvyquantile
, which is a version of the function
from before version 4.1 of the survey package, available for backwards compatibility.
survey_old_quantile
and survey_old_median
should always be
called from summarise
. See Thomas Lumley's blogpost
<https://notstatschat.rbind.io/2021/07/20/what-s-new-in-the-survey-package/>
for more details.
survey_old_quantile( x, quantiles, na.rm = FALSE, vartype = c("se", "ci", "var", "cv"), level = 0.95, q_method = "linear", f = 1, interval_type = c("Wald", "score", "betaWald", "probability", "quantile"), ties = c("discrete", "rounded"), df = NULL, ... ) survey_old_median( x, na.rm = FALSE, vartype = c("se", "ci"), level = 0.95, q_method = "linear", f = 1, interval_type = c("Wald", "score", "betaWald", "probability", "quantile"), ties = c("discrete", "rounded"), df = NULL, ... )
x |
A variable or expression |
quantiles |
A vector of quantiles to calculate |
na.rm |
A logical value to indicate whether missing values should be dropped |
vartype |
NULL to report no variability (default), otherwise one or more of: standard error ("se") confidence interval ("ci") (variance and coefficient of variation not available). |
level |
A single number indicating the confidence level (only one level allowed) |
q_method |
See "method" in |
f |
See |
interval_type |
See |
ties |
See |
df |
A number indicating the degrees of freedom for t-distribution. The
default, Inf uses the normal distribution (matches the survey package).
Also, has no effect for |
... |
Ignored |
library(survey) data(api) dstrata <- apistrat %>% as_survey_design(strata = stype, weights = pw) dstrata %>% summarise(api99 = survey_old_quantile(api99, c(0.25, 0.5, 0.75)), api00 = survey_old_median(api00, vartype = c("ci"))) dstrata %>% group_by(awards) %>% summarise(api00 = survey_old_median(api00))
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