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Evaluation of supplemental samples in longitudinal research with non-normal missing data

Overview of attention for article published in Behavior Research Methods, August 2018
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Title
Evaluation of supplemental samples in longitudinal research with non-normal missing data
Published in
Behavior Research Methods, August 2018
DOI 10.3758/s13428-018-1070-3
Pubmed ID
Authors

Jessica A. M. Mazen, Xin Tong, Laura K. Taylor

Abstract

Missing data is a commonly encountered problem in longitudinal research. Methodological articles provide advice on ways to handle missing data at the analysis stage, however, there is less guidance for researchers who wish to use supplemental samples (i.e., the addition of new participants to the original sample after missing data appear at the second or later measurement occasions) to handle attrition. The purpose of this study is to evaluate the effects of using supplemental samples when analyzing longitudinal data that are non-normally distributed. We distinguish between two supplemental approaches: a refreshment approach where researchers select additional participants using the same criteria as the initial participants (i.e., random selection from the population of interest) and a replacement approach where researchers identify auxiliary variables that explain missingness and select new participants based on those attributes. Overall, simulation results suggest that the addition of refreshment samples, but not replacement samples, is an effective way to respond to attrition in longitudinal research. Indeed, use of refreshment samples may reduce bias of parameter estimates and increase efficiency and statistical power, whereas use of replacement samples results in biased parameter estimates. Our findings may be utilized by researchers considering using supplemental samples and provide guidance for selecting an appropriate supplemental sample approach.

Twitter Demographics

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Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 20%
Unknown 4 80%
Readers by discipline Count As %
Social Sciences 1 20%
Unknown 4 80%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 June 2019.
All research outputs
#11,920,525
of 13,444,619 outputs
Outputs from Behavior Research Methods
#992
of 1,157 outputs
Outputs of similar age
#230,608
of 266,964 outputs
Outputs of similar age from Behavior Research Methods
#37
of 46 outputs
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