srvyr: survey_mean – R documentation

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survey_mean

Calculate the mean and its variation using survey methods

Description

Calculate means and proportions from complex survey data. A wrapper around svymean, or if proportion = TRUE, svyciprop. survey_mean should always be called from summarise.

Usage

survey_mean(
  x,
  na.rm = FALSE,
  vartype = c("se", "ci", "var", "cv"),
  level = 0.95,
  proportion = FALSE,
  prop_method = c("logit", "likelihood", "asin", "beta", "mean"),
  deff = FALSE,
  df = NULL,
  ...
)

survey_prop(
  vartype = c("se", "ci", "var", "cv"),
  level = 0.95,
  proportion = FALSE,
  prop_method = c("logit", "likelihood", "asin", "beta", "mean"),
  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`	(For vartype = "ci" only) A single number or vector of numbers indicating the confidence level
`proportion`	Use methods to calculate the proportion that may have more accurate confidence intervals near 0 and 1. Based on `svyciprop`.
`prop_method`	Type of proportion method to use if proportion is `TRUE`. See `svyciprop` for details.
`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 (except in `svyciprop`.
`...`	Ignored

Examples

library(survey)
data(api)

dstrata <- apistrat %>%
  as_survey_design(strata = stype, weights = pw)

dstrata %>%
  summarise(api99_mn = survey_mean(api99),
            api_diff = survey_mean(api00 - api99, vartype = c("ci", "cv")))

dstrata %>%
  group_by(awards) %>%
  summarise(api00 = survey_mean(api00))

# Leave x empty to calculate the proportion in each group
dstrata %>%
  group_by(awards) %>%
  summarise(pct = survey_mean())

# Setting proportion = TRUE uses a different method for calculating confidence intervals
dstrata %>%
  summarise(high_api = survey_mean(api00 > 875, proportion = TRUE, vartype = "ci"))

# level takes a vector for multiple levels of confidence intervals
dstrata %>%
  summarise(api99 = survey_mean(api99, vartype = "ci", level = c(0.95, 0.65)))

# Note that the default degrees of freedom in srvyr is different from
# survey, so your confidence intervals might not be exact matches. To
# Replicate survey's behavior, use df = Inf
dstrata %>%
  summarise(srvyr_default = survey_mean(api99, vartype = "ci"),
            survey_defualt = survey_mean(api99, vartype = "ci", df = Inf))

comparison <- survey::svymean(~api99, dstrata)
confint(comparison) # survey's default
confint(comparison, df = survey::degf(dstrata)) # srvyr's default

srvyr

'dplyr'-Like Syntax for Summary Statistics of Survey Data

v1.0.1

GPL-2 | GPL-3

Authors

Greg Freedman Ellis [aut, cre], Thomas Lumley [ctb], Tomasz Żółtak [ctb], Ben Schneider [aut, ctb], Pavel N. Krivitsky [ctb]

Initial release

2021-03-28