sjstats (version 0.17.6)

svy_md: Weighted statistics for tests and variables

Description

Weighted statistics for variables

wtd_sd(), wtd_se(), wtd_mean() and wtd_median() compute weighted standard deviation, standard error, mean or median for a variable or for all variables of a data frame. svy_md() computes the median for a variable in a survey-design (see svydesign). wtd_cor() computes a weighted correlation for a two-sided alternative hypothesis.

Weighted tests

wtd_ttest() computes a weighted t-test, while wtd_mwu() computes a weighted Mann-Whitney-U test or a Kruskal-Wallis test (for more than two groups). wtd_chisqtest() computes a weighted Chi-squared test for contigency tables.

Usage

svy_md(x, design)
survey_median(x, design)
wtd_chisqtest(data, ...)
# S3 method for default
wtd_chisqtest(data, x, y, weights, ...)
# S3 method for formula
wtd_chisqtest(formula, data, ...)
wtd_cor(data, ...)
# S3 method for default
wtd_cor(data, x, y, weights, ci.lvl = 0.95, ...)
# S3 method for formula
wtd_cor(formula, data, ci.lvl = 0.95, ...)
wtd_mean(x, weights = NULL)
wtd_median(x, weights = NULL)
wtd_mwu(data, ...)
# S3 method for default
wtd_mwu(data, x, grp, weights, ...)
# S3 method for formula
wtd_mwu(formula, data, ...)
wtd_sd(x, weights = NULL)
wtd_se(x, weights = NULL)
wtd_ttest(data, ...)
# S3 method for default
wtd_ttest(data, x, y = NULL, weights, mu = 0,
  paired = FALSE, ci.lvl = 0.95, alternative = c("two.sided", "less",
  "greater"), ...)
# S3 method for formula
wtd_ttest(formula, data, mu = 0, paired = FALSE,
  ci.lvl = 0.95, alternative = c("two.sided", "less", "greater"), ...)

Arguments

x

(Numeric) vector or a data frame. For svy_md(), wtd_ttest(), wtd_mwu() and wtd_chisqtest() the bare (unquoted) variable name, or a character vector with the variable name.

design

An object of class svydesign, providing a specification of the survey design.

data

A data frame.

...

For wtd_ttest() and wtd_mwu(), currently not used. For wtd_chisqtest(), further arguments passed down to chisq.test.

y

Optional, bare (unquoted) variable name, or a character vector with the variable name.

weights

Bare (unquoted) variable name, or a character vector with the variable name of the numeric vector of weights. If weights = NULL, unweighted statistic is reported.

formula

A formula of the form lhs ~ rhs1 + rhs2 where lhs is a numeric variable giving the data values and rhs1 a factor with two levels giving the corresponding groups and rhs2 a variable with weights.

ci.lvl

Confidence level of the interval.

grp

Bare (unquoted) name of the cross-classifying variable, where x is grouped into the categories represented by grp, or a character vector with the variable name.

mu

A number indicating the true value of the mean (or difference in means if you are performing a two sample test).

paired

Logical, whether to compute a paired t-test.

alternative

A character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.

Value

The weighted (test) statistic.

Examples

# NOT RUN {
# weighted sd and se ----

wtd_sd(rnorm(n = 100, mean = 3), runif(n = 100))

data(efc)
wtd_sd(efc[, 1:3], runif(n = nrow(efc)))
wtd_se(efc[, 1:3], runif(n = nrow(efc)))

# svy_md ----

# median for variables from weighted survey designs
library(survey)
data(nhanes_sample)

des <- svydesign(
  id = ~SDMVPSU,
  strat = ~SDMVSTRA,
  weights = ~WTINT2YR,
  nest = TRUE,
  data = nhanes_sample
)

svy_md(total, des)
svy_md("total", des)

# weighted t-test ----

efc$weight <- abs(rnorm(nrow(efc), 1, .3))
wtd_ttest(efc, e17age, weights = weight)
wtd_ttest(efc, e17age, c160age, weights = weight)
wtd_ttest(e17age ~ e16sex + weight, efc)

# weighted Mann-Whitney-U-test ----

wtd_mwu(c12hour ~ c161sex + weight, efc)

# weighted Chi-squared-test ----

wtd_chisqtest(efc, c161sex, e16sex, weights = weight, correct = FALSE)
wtd_chisqtest(c172code ~ c161sex + weight, efc)

# }