How Big of a Problem is Analytic Error in Secondary Analyses of Survey Data?

ABSTRACT: Secondary analyses of survey data collected from large probability samples of persons or establishments further scientific progress in many fields. The complex design features of these samples improve data collection efficiency, but also require analysts to account for these features when conducting analysis. Unfortunately, many secondary analysts from fields outside of statistics, biostatistics, and survey methodology do not have adequate training in this area, and as a result may apply incorrect statistical methods when analyzing these survey data sets. This in turn could lead to the publication of incorrect inferences based on the survey data that effectively negate the resources dedicated to these surveys. In this article, we build on the results of a preliminary meta-analysis of 100 p

SUBMITTER: West BT 

PROVIDER: S-EPMC4927119 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature