10 Must-Have R Packages for Social Scientists

Political scientist Drew Conway (he of the awesome live-tweeting social analysis demo) lists his top 10 must-have packages for social scientists using R. They are:

1. Zelig, for a uniform regression methodology
2. ggplot2, for graphics
3. Statnet and igraph, for social network analysis
4. plyr, for data manipulation
5. Amelia II, for missing data imputation
6. nlme, for nonlinear mixed-effects models
7. SNOW and Rmpi for parallel computing (what, no love for foreach?)
8. xtable/apsrtable for print-ready tables
9. plm, for analysis of panel data, and
10. sqldfm, for using SQL to process R data

Check out the full article for Drew's discussion of each package and why it makes the top 10 for social scientists. 

Zero Intelligence Agents: Must-Have R Packages for Social Scientists

Comments

[Barry]

What our social scientists want is two packages, namely:

require(spss)

and:

require(spoonfeedingandclickyinterfaceplease)

But seriously (what, me serious?) are there R packages to do what AMOS for SPSS does? And that do Multi-level modelling as SAS 9.2 does? I say SAS 9.2 because we had a request from a user for 9.2 because 9.1 didn't have enough levels or something... Anyway, those are the things our social scientists seem to use. I know nothing about them. I must be doing anti-social science. Or 'science' as we call it. I knew I couldn't be serious for long.

[Frank]

@Barry- See lmer,nlme, and Winbugs4r (and of course, win bugs) for multilevel modelling (also see the Multi-level modeling book by Gelman and Hill). RE: Amos, there are several R packages for structural equation modelling, such search the cran site.

[Ali]

Barry: For SEM, take a look at OpenMX:

http://openmx.psyc.virginia.edu/wiki/main-page