# srvyr v0.3.1

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

Use piping, verbs like 'group_by' and 'summarize', and other
'dplyr' inspired syntactic style when calculating summary statistics on survey
data using functions from the 'survey' package.

## Readme

# 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

- 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.

## Functions in srvyr

Name | Description | |

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 | |

No Results! |

## Vignettes of srvyr

Name | ||

acs_m.RData | ||

extending-srvyr.Rmd | ||

save_acs_data.R | ||

srvyr-database.Rmd | ||

srvyr-vs-survey.Rmd | ||

No Results! |

## Last month downloads

## Details

Type | Package |

Date | 2018-03-10 |

URL | http://gdfe.co/srvyr, https://github.com/gergness/srvyr |

BugReports | https://github.com/gergness/srvyr/issues |

License | GPL-2 | GPL-3 |

LazyData | TRUE |

VignetteBuilder | knitr |

RoxygenNote | 6.0.1 |

NeedsCompilation | no |

Packaged | 2018-03-10 18:31:00 UTC; greg |

Repository | CRAN |

Date/Publication | 2018-03-10 18:45:40 UTC |

suggests | convey , dbplyr , ggplot2 , knitr , Matrix , MonetDBLite , pander , rmarkdown , RSQLite , survival , testthat , vardpoor |

imports | dplyr (>= 0.7) , magrittr , rlang , survey , tibble |

depends | R (>= 3.1.2) |

Contributors | Thomas Lumley |

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```