On coordinating “simple” statistical analyses across multiple software packages: A case study from wave 1 of the Global Flourishing Study

R. Noah Padgett

No 6d2wf, OSF Preprints from Center for Open Science

Abstract: Statistical analyses can have a significant impact when the results are easy to communicate to a wide audience. This goal was a focus when designing the coordinated analyses of Wave 1 of the Global Flourishing Study. The methods, especially for the demographic variation analyses, are seemingly simple: to compute the mean or proportion of an outcome by subgroups. When described at a high level, these analyses feel like a topic that should be only of interest while in an introductory statistics course. The current work will challenge this belief as we describe our efforts to provide a rigorous methodology for these seemingly simple analyses that can be implemented across a range of popular statistical software packages. The descriptions of the methods are supplemented by a focused simulation study demonstrating the consistency of results of complex survey adjusted modified Poisson regression with missing data across statistical software packages R, Stata, and SAS.

Date: 2024-11-22
References: Add references at CitEc
Citations:

Downloads: (external link)
https://osf.io/download/673e63f7476ee5ffe48865e9/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:6d2wf

DOI: 10.31219/osf.io/6d2wf

Access Statistics for this paper

More papers in OSF Preprints from Center for Open Science
Bibliographic data for series maintained by OSF ().