memisc: Management of Survey Data and Presentation of Analysis Results¶
The R package memisc, which is available at CRAN, provides tools for the management of survey data, as well as the creation of tables of summary statistics and model estimates.
One of the aims of this package is to make life easier for useRs who deal with survey data sets. It provides an infrastructure for the management of survey data including value labels, definable missing values, recoding of variables, production of code books, and import of (subsets of) SPSS and Stata files. Further, it provides functionality to produce tables and data frames of arbitrary descriptive statistics and (almost) publication-ready tables of regression model estimates. Also some convenience tools for graphics, programming, and simulation are provided.
Development occurs on GitHub, where both releases and the development tree can be found.
Documentation¶
Recent news¶
- 22 November 2019
- New memisc release 0.99.20.1 improves compatibility with RStudio and “tidyverse”
- 23 March 2019
- New memisc release 0.99.17.1 facilitates checking your data
- 18 January 2016
- memisc 0.99 published on CRAN
- 07 March 2015
- memisc 0.97 released
Examples¶
Below are examples of output created with memisc.
voteint — 'Vote intention'
"Which party are you going to vote for in the general election next Tuesday?"
| Storage mode: | double |
| Measurement: | nominal |
| Valid range: | 1-9 |
| Values and labels | N | Percent | |||||||
| 1 | 'Cons' | 49 | 27 | . | 8 | 24 | . | 5 | |
| 2 | 'Lab' | 26 | 14 | . | 8 | 13 | . | 0 | |
| 3 | 'LibDem' | 21 | 11 | . | 9 | 10 | . | 5 | |
| 4 | 'Other' | 19 | 10 | . | 8 | 9 | . | 5 | |
| 9 | 'NoVote' | 61 | 34 | . | 7 | 30 | . | 5 | |
| 97 | M | 'DK' | 6 | 3 | . | 0 | |||
| 98 | M | 'Refused' | 7 | 3 | . | 5 | |||
| 99 | M | 'N.a.' | 11 | 5 | . | 5 | |||
An example of a codebook for a
survey questionnaire item
produced with memisc
| Model 1 | Model 4 | Model 5 | |||||||
| Intercept | −1 | . | 401*** | −0 | . | 213 | −1 | . | 687*** |
| (0 | . | 271) | (0 | . | 126) | (0 | . | 294) | |
| Occup. class: Other white collar/Upper white collar | 1 | . | 368*** | 1 | . | 287*** | |||
| (0 | . | 373) | (0 | . | 381) | ||||
| Occup. class: Blue collar/Upper white collar | 2 | . | 448*** | 2 | . | 385*** | |||
| (0 | . | 327) | (0 | . | 337) | ||||
| Occup. class: Farmer/Upper white collar | 1 | . | 826*** | 2 | . | 039*** | |||
| (0 | . | 413) | (0 | . | 426) | ||||
| Religion: Catholic/Protestant | 0 | . | 877*** | 0 | . | 685* | |||
| (0 | . | 243) | (0 | . | 292) | ||||
| Religion: Other,none/Protestant | 0 | . | 975** | 1 | . | 191** | |||
| (0 | . | 347) | (0 | . | 441) | ||||
| Nagelkerke R-sq. | 0 | . | 2 | 0 | . | 1 | 0 | . | 3 |
| Deviance | 404 | . | 2 | 537 | . | 7 | 393 | . | 1 |
| AIC | 412 | . | 2 | 543 | . | 7 | 405 | . | 1 |
| N | 344 | 402 | 344 | ||||||
An example of a table of model estimates produced
with memisc
