Calculate standard deviations with complex survey data
svysd extends the survey package by calculating standard
deviations with syntax similar to the original package, which provides
only a svyvar() function.
svysd(
formula,
design,
na.rm = FALSE,
digits = getOption("jtools-digits", default = 3),
...
)formula |
A formula (e.g., ~var1+var2) specifying the term(s) of interest. |
design |
The |
na.rm |
Logical. Should cases with missing values be dropped? |
digits |
An integer specifying the number of digits past the decimal to
report in the output. Default is 3. You can change the default number of
digits for all jtools functions with
|
... |
Additional arguments passed to |
An alternative is to simply do sqrt(svyvar(~term, design = design)).
However, if printing and sharing the output, this may be misleading since
the output will say "variance."
This function was designed independent of the survey package and is neither endorsed nor known to its authors.
Other survey package extensions:
svycor()
Other survey tools:
pf_sv_test(),
svycor(),
weights_tests(),
wgttest()
if (requireNamespace("survey")) {
library(survey)
data(api)
# Create survey design object
dstrat <- svydesign(id = ~1,strata = ~stype, weights = ~pw, data = apistrat,
fpc=~fpc)
# Print the standard deviation of some variables
svysd(~api00+ell+meals, design = dstrat)
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