Academic Article


  • 2018

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.

Øya, Elisabeth; Afanou, Komlavi Anani; Malla, Nabin; Uhlig, Silvio; Rolen, Elin; Skaar, Ida; Straumfors, Anne; Winberg, Jan-Olof; Bang, Berit; Schwarze, Per E; Eduard, Wijnand; Holme, Jørn Andreas
Indoor Air 28(1): 28–39
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