TY - JOUR
T1 - Simple descriptive missing data indicators in longitudinal studies with attrition, intermittent missing data and a high number of follow-ups
AU - Wærsted, Morten
AU - Børnick, Taran Svenssen
AU - Twisk, Jos W. R.
AU - Veiersted, Kaj Bo
PY - 2018
Y1 - 2018
N2 - Objective: Missing data in longitudinal studies may constitute a source of bias. We suggest three simple missing data indicators for the initial phase of getting an overview of the missingness pattern in a dataset with a high number of follow-ups. Possible use of the indicators is exemplified in two datasets allowing wave nonresponse; a Norwegian dataset of 420 subjects examined at 21 occasions during 6.5 years and a Dutch dataset of 350 subjects with ten repeated measurements over a period of 35 years. Results: The indicators Last response (the timing of last response), Retention (the number of responded follow-ups), and Dispersion (the evenness of the distribution of responses) are introduced. The proposed indicators reveal different aspects of the missing data pattern, and may give the researcher a better insight into the pattern of missingness in a study with several follow-ups, as a starting point for analyzing possible bias. Although the indicators are positively correlated to each other, potential predictors of missingness can have a different relationship with different indicators leading to a better understanding of the missing data mechanism in longitudinal studies. These indictors may be useful descriptive tools when starting to look into a longitudinal dataset with many follow-ups.
AB - Objective: Missing data in longitudinal studies may constitute a source of bias. We suggest three simple missing data indicators for the initial phase of getting an overview of the missingness pattern in a dataset with a high number of follow-ups. Possible use of the indicators is exemplified in two datasets allowing wave nonresponse; a Norwegian dataset of 420 subjects examined at 21 occasions during 6.5 years and a Dutch dataset of 350 subjects with ten repeated measurements over a period of 35 years. Results: The indicators Last response (the timing of last response), Retention (the number of responded follow-ups), and Dispersion (the evenness of the distribution of responses) are introduced. The proposed indicators reveal different aspects of the missing data pattern, and may give the researcher a better insight into the pattern of missingness in a study with several follow-ups, as a starting point for analyzing possible bias. Although the indicators are positively correlated to each other, potential predictors of missingness can have a different relationship with different indicators leading to a better understanding of the missing data mechanism in longitudinal studies. These indictors may be useful descriptive tools when starting to look into a longitudinal dataset with many follow-ups.
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85042127539&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/29433533
U2 - https://doi.org/10.1186/s13104-018-3228-6
DO - https://doi.org/10.1186/s13104-018-3228-6
M3 - Article
C2 - 29433533
SN - 1756-0500
VL - 11
JO - BMC Research Notes
JF - BMC Research Notes
IS - 1
M1 - 123
ER -