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srvyr

srvyr brings parts of dplyr's syntax to survey analysis, using the survey package.

srvyr focuses on calculating summary statistics from survey data, such as the mean, total or quantile. It allows for the use of many dplyr verbs, such as summarize, group_by, and mutate, the convenience of pipe-able functions, rlang's style of non-standard evaluation and more consistent return types than the survey package.

You can try it out:

install.packages("srvyr")
# or for development version
# devtools::install_github("gergness/srvyr")

Example usage

First, describe the variables that define the survey's stucture with the function as_survey()with the bare column names of the names that you would use in functions from the survey package like survey::svydesign(), survey::svrepdesign() or survey::twophase().

library(srvyr, warn.conflicts = FALSE)
data(api, package = "survey")

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

Now many of the dplyr verbs are available.

  • mutate() adds or modifies a variable.
dstrata <- dstrata %>%
  mutate(api_diff = api00 - api99)
  • summarise() calculates summary statistics such as mean, total, quantile or ratio.
dstrata %>% 
  summarise(api_diff = survey_mean(api_diff, vartype = "ci"))
#> # A tibble: 1 x 3
#>   api_diff api_diff_low api_diff_upp
#>      <dbl>        <dbl>        <dbl>
#> 1     32.9         28.8         37.0
  • group_by() and then summarise() creates summaries by groups.
dstrata %>% 
  group_by(stype) %>%
  summarise(api_diff = survey_mean(api_diff, vartype = "ci"))
#> # A tibble: 3 x 4
#>   stype api_diff api_diff_low api_diff_upp
#>   <fct>    <dbl>        <dbl>        <dbl>
#> 1 E        38.6         33.1          44.0
#> 2 H         8.46         1.74         15.2
#> 3 M        26.4         20.4          32.4
  • Functions from the survey package are still available:
my_model <- survey::svyglm(api99 ~ stype, dstrata)
summary(my_model)
#> 
#> Call:
#> svyglm(formula = api99 ~ stype, dstrata)
#> 
#> Survey design:
#> Called via srvyr
#> 
#> Coefficients:
#>             Estimate Std. Error t value Pr(>|t|)    
#> (Intercept)   635.87      13.34  47.669   <2e-16 ***
#> stypeH        -18.51      20.68  -0.895    0.372    
#> stypeM        -25.67      21.42  -1.198    0.232    
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> 
#> (Dispersion parameter for gaussian family taken to be 16409.56)
#> 
#> Number of Fisher Scoring iterations: 2

What people are saying about srvyr

[srvyr] lets us use the survey library’s functions within a data analysis pipeline in a familiar way.

-- Kieran Healy, in Data Visualization: A practical introduction

  1. Yay!

--Thomas Lumley, in the Biased and Inefficent blog

Contributing

I do appreciate bug reports, suggestions and pull requests! I started this as a way to learn about R package development, and am still learning, so you'll have to bear with me. Please review the Contributor Code of Conduct, as all participants are required to abide by its terms.

If you're unfamiliar with contributing to an R package, I recommend the guides provided by Rstudio's tidyverse team, such as Jim Hester's blog post or Hadley Wickham's R packages book.

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Version

Install

install.packages('srvyr')

Monthly Downloads

5,358

Version

0.3.1

License

GPL-2 | GPL-3

Issues

Pull Requests

Stars

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Maintainer

Greg Freedman

Last Published

March 10th, 2018

Functions in srvyr (0.3.1)

dplyr_single

Single table verbs from dplyr
as_survey_twophase

Create a tbl_svy survey object using two phase design
srvyr-se-deprecated

Deprecated SE versions of main srvyr verbs
summarise_all

Manipulate multiple columns.
survey_mean

Calculate the mean and its variation using survey methods
survey_quantile

Calculate the quantile and its variation using survey methods
tbl_svy

tbl_svy object.
survey_ratio

Calculate the ratio and its variation using survey methods
tbl_vars

List variables produced by a tbl.
collect

Force computation of a database query
current_svy

Get the survey data for the current context
as_survey

Create a tbl_svy from a data.frame
as_survey_design

Create a tbl_svy survey object using sampling design
%>%

Pipe operator
rlang-tidyeval

Tidy eval helpers from rlang
srvyr

svrvyr: A package for 'dplyr'-Like Syntax for Summary Statistics of Survey Data.
unweighted

Calculate the an unweighted summary statistic from a survey
summarise

Summarise multiple values to a single value.
survey_total

Calculate the total and its variation using survey methods
svychisq

Chisquared tests of association for survey data.
as_tibble

Coerce survey variables to a data frame (tibble)
cascade

Summarise multiple values into cascading groups
group_by

Group a (survey) dataset by one or more variables.
groups

Get/set the grouping variables for tbl.
get_var_est

Get the variance estimates for a survey estimate
as_survey_rep

Create a tbl_svy survey object using replicate weights
set_survey_vars

Set the variables for the current survey variable