Summarise multiple values to a single value.
1 2 3 4 
.data, 
tbl A 
... 
Namevalue pairs of summary functions 
.dots 
Used to work around nonstandard evaluation. See

Summarise for tbl_svy
objects accepts several specialized functions.
Each of the functions a variable (or two, in the case of
survey_ratio
), from the data.frame and default to providing the measure
and its standard error.
The argument vartype
can choose one or more measures of uncertainty,
se
for standard error, ci
for confidence interval, var
for variance, and cv
for coefficient of variation. level
specifies the level for the confidence interval.
The other arguments correspond to the analagous function arguments from the survey package.
The available functions are:
survey_mean
Calculate the survey mean of the entire population or by groups
.
Based on svymean
.
survey_total
Calculate the survey total of the entire population or by groups
.
Based on svytotal
.
survey_ratio
Calculate the ratio of 2 variables in the entire population or by groups
.
Based on svyratio
.
survey_quantile
Calculate quantiles in the entire population or by groups
. Based on
svyquantile
.
survey_median
Calculate the median in the entire population or by groups
.
svyquantile
.
unweighted
Calculate an unweighted estimate as you would on a regular tbl_df
.
Based on dplyr's summarise
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18  library(survey)
data(api)
dstrata < apistrat %>%
as_survey_design(strata = stype, weights = pw)
dstrata %>%
summarise(api99 = survey_mean(api99),
api00 = survey_mean(api00),
api_diff = survey_mean(api00  api99))
dstrata_grp < dstrata %>%
group_by(stype)
dstrata_grp %>%
summarise(api99 = survey_mean(api99),
api00 = survey_mean(api00),
api_diff = survey_mean(api00  api99))

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