# srvyr v0.2.1

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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, lazyeval'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")
```

To create a `tbl_svy`

object (the core concept behind the srvyr package), use the function `as_survey_design()`

with the bare column names of the names you would use in `survey::svydesign()`

object.

```
library(survey)
data(api)
dstrata <- apistrat %>%
as_survey_design(strata = stype, weights = pw)
```

Now many of the dplyr verbs are available.

Use

`mutate()`

if you want to add or modify 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")))`

Use

`group_by()`

if you want to summarise by groups.`dstrata %>% group_by(stype) %>% summarise(api_diff = survey_mean(api_diff, vartype = "ci")))`

You can still use functions from the survey package if you'd like to:

```
svyglm(api99 ~ stype, dstrata)
```

If you'd like to contribute, please let me know! I started this as a way to learn about R package development, so you'll have to bear with me as I learn, but I would appreciate bug reports, pull requests or other suggestions!

## Functions in srvyr

Name | Description | |

as_survey | Create a tbl_svy from a data.frame | |

as_survey_design | Create a tbl_svy survey object using sampling design | |

as_tibble | Coerce survey variables to a data frame (tibble) | |

cascade | Summarise multiple values into cascading groups | |

as_survey_rep | Create a tbl_svy survey object using replicate weights | |

as_survey_twophase | Create a tbl_svy survey object using two phase design | |

survey_total | Calculate the total and its variation using survey methods | |

svychisq | Chisquared tests of association for survey data. | |

tbl_svy | tbl_svy object. | |

tbl_vars | List variables produced by a tbl. | |

groups | Get/set the grouping variables for tbl. | |

%>% | Pipe operator | |

survey_quantile | Calculate the quantile and its variation using survey methods | |

survey_ratio | Calculate the ratio and its variation using survey methods | |

dplyr_single | Single table verbs from dplyr | |

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

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

summarise | Summarise multiple values to a single value. | |

unweighted | Calculate the an unweighted summary statistic from a survey | |

summarise_all | Summarise and mutate multiple columns. | |

survey_mean | Calculate the mean and its variation using survey methods | |

No Results! |

## Last month downloads

## Details

Type | Package |

Date | 2017-4-25 |

URL | 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 | 2017-04-26 11:54:25 UTC; greg |

Repository | CRAN |

Date/Publication | 2017-04-26 16:36:26 UTC |

imports | dplyr (>= 0.5) , lazyeval , magrittr , survey , tibble |

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

depends | R (>= 3.1.2) |

Contributors |

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