weighted_sd: Weighted statistics for tests and variables

View source: R/wtd_sd.R

survey_medianR Documentation

Weighted statistics for tests and variables

Description

Weighted statistics for variables

weighted_sd(), weighted_se(), weighted_mean() and weighted_median() compute weighted standard deviation, standard error, mean or median for a variable or for all variables of a data frame. survey_median() computes the median for a variable in a survey-design (see svydesign). weighted_correlation() computes a weighted correlation for a two-sided alternative hypothesis.

Weighted tests

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

Usage

survey_median(x, design)

weighted_chisqtest(data, ...)

## Default S3 method:
weighted_chisqtest(data, x, y, weights, ...)

## S3 method for class 'formula'
weighted_chisqtest(formula, data, ...)

weighted_correlation(data, ...)

## Default S3 method:
weighted_correlation(data, x, y, weights, ci.lvl = 0.95, ...)

## S3 method for class 'formula'
weighted_correlation(formula, data, ci.lvl = 0.95, ...)

weighted_mean(x, weights = NULL)

weighted_median(x, weights = NULL)

weighted_mannwhitney(data, ...)

## Default S3 method:
weighted_mannwhitney(data, x, grp, weights, ...)

## S3 method for class 'formula'
weighted_mannwhitney(formula, data, ...)

weighted_sd(x, weights = NULL)

wtd_sd(x, weights = NULL)

weighted_se(x, weights = NULL)

weighted_ttest(data, ...)

## Default S3 method:
weighted_ttest(
  data,
  x,
  y = NULL,
  weights,
  mu = 0,
  paired = FALSE,
  ci.lvl = 0.95,
  alternative = c("two.sided", "less", "greater"),
  ...
)

## S3 method for class 'formula'
weighted_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 survey_median(), weighted_ttest(), weighted_mannwhitney() and weighted_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 weighted_ttest() and weighted_mannwhitney(), currently not used. For weighted_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.

Note

weighted_chisq() is a convenient wrapper for crosstable_statistics. For a weighted one-way Anova, use means_by_group() with weights-argument.

weighted_ttest() assumes unequal variance between the two groups.

Examples

# weighted sd and se ----
weighted_sd(rnorm(n = 100, mean = 3), runif(n = 100))

data(efc)
weighted_sd(efc[, 1:3], runif(n = nrow(efc)))
weighted_se(efc[, 1:3], runif(n = nrow(efc)))

# survey_median ----
# median for variables from weighted survey designs
if (require("survey")) {
  data(nhanes_sample)

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

  survey_median(total, des)
  survey_median("total", des)
}

# weighted t-test ----
efc$weight <- abs(rnorm(nrow(efc), 1, .3))
weighted_ttest(efc, e17age, weights = weight)
weighted_ttest(efc, e17age, c160age, weights = weight)
weighted_ttest(e17age ~ e16sex + weight, efc)

# weighted Mann-Whitney-U-test ----
weighted_mannwhitney(c12hour ~ c161sex + weight, efc)

# weighted Chi-squared-test ----
weighted_chisqtest(efc, c161sex, e16sex, weights = weight, correct = FALSE)
weighted_chisqtest(c172code ~ c161sex + weight, efc)

# weighted Chi-squared-test for given probabilities ----
weighted_chisqtest(c172code ~ weight, efc, p = c(.33, .33, .34))

sjPlot/sjstats documentation built on Nov. 20, 2022, 3:47 p.m.