Statistical, data manipulation, and presentation tools make R an ideal integrated package for research in the fields of health policy and healthcare management and evaluation. However, the technical documentation accompanying most data sets used by researchers in these fields does not include syntax examples for analysts to make the transition from another statistical package to R. This paper describes the steps required to import health policy data into R, to prepare that data for analysis using the two most common complex survey variance calculation techniques, and to produce the principal set of statistical estimates sought by health policy researchers. Using data from the Medical Expenditure Panel Survey Household Component (MEPS-HC), this paper outlines complex survey data analysis techniques in R, with side-by-side comparisons to the SAS, Stata, and SUDAAN statistical software packages.
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For attribution, please cite this work as
Damico, "The R Journal: Transitioning to R: Replicating SAS, Stata, and SUDAAN Analysis Techniques in Health Policy Data", The R Journal, 2009
BibTeX citation
@article{RJ-2009-018,
author = {Damico, Anthony},
title = {The R Journal: Transitioning to R: Replicating SAS, Stata, and SUDAAN Analysis Techniques in Health Policy Data},
journal = {The R Journal},
year = {2009},
note = {https://doi.org/10.32614/RJ-2009-018},
doi = {10.32614/RJ-2009-018},
volume = {1},
issue = {2},
issn = {2073-4859},
pages = {37-44}
}