A Primer on the Data Cleaning Pipeline, "The statistical & methodological questions around data integration, or merging multiple data sources, have grown. Specifically, the science of the 'data cleaning pipeline' contains 4 stages that allow an analyst to perform downstream tasks, predictive analyses, or statistical analyses on 'cleaned data.' This article provides a review of this emerging field, introducing terminology and commonly used methods." https://academic.oup.com/jssam/article-abstract/11/3/553/7187091 #AAPOR #JSSAM #MRX

"Estimates of change from panel surveys can be subject to measurement error, most commonly overreporting of change. For this reason, many panel surveys use a technique called proactive dependent interviewing, which reminds respondents of their answer in the previous wave, and has been shown to reduce the capturing of spurious change." https://academic.oup.com/jssam/article-abstract/8/4/706/5532310?redirectedFrom=fulltext #MRX #JSSAM

"For the GESIS Panel, the optimal cut-off points for the web hover around approximately two weeks after the invitation, while for the mail mode, the point is about three weeks after the invitation. Naturally, these cut-off points will not be exactly the same for every (panel) survey that uses web and mail modes... However, the method that we propose can be used for each survey that has multiple-mode data collection." #mrx #jssam https://academic.oup.com/jssam/article/10/1/161/6237202?login=false

~Five reasons why researchers might want to integrate self-reports + passive data: 1) verification, 2) contextualization, e.g., asking about the purpose of passively detected trip, 3) quantifying relationships, e.g., quantifying the association between self-reported stress and passively measured sleep duration, 4) building composite measures, & 5) triggering measurement, e.g., asking questions contingent on passively measured events or participant locations.~
https://academic.oup.com/jssam/article-abstract/10/4/863/6375741 #mrx #jssam