# summarise

0th

Percentile

##### Summarise multiple values to a single value.

Summarise multiple values to a single value.

##### Usage
summarise(.data, ...)
summarize(.data, ...)
##### Arguments
.data,

tbl A tbl_svy object

...

Name-value pairs of summary functions

##### Details

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 from srvyr 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.

• summarise
• summarize
##### Examples
# NOT RUN {
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))

# }

Documentation reproduced from package srvyr, version 0.3.5, License: GPL-2 | GPL-3

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