
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.
Statistics and Probability, Other Psychology, Physical Sciences and Mathematics, Psychology, Other Statistics and Probability, Quantitative Psychology, Social and Behavioral Sciences
Statistics and Probability, Other Psychology, Physical Sciences and Mathematics, Psychology, Other Statistics and Probability, Quantitative Psychology, Social and Behavioral Sciences
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