Abstract
ObjectiveMissing 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.ResultsThe 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.
Highlights
A longitudinal study with a high number of follow-ups provides a unique opportunity to evaluate individual development over time, but it implies many challenges
This paper proposes three simple descriptive missing data indicators to characterize individual patterns that may arise in a longitudinal study with many follow-ups
In the Norwegian dataset (Table 1), smokers compared to non-smokers and participants with at least one parent of non-western origin had lower scores for all the missing data indicators
Summary
In the Norwegian dataset (Table 1), smokers compared to non-smokers and participants with at least one parent of non-western origin had lower scores for all the missing data indicators. Men scored lower than women on the Retention indicator. Neither Self-reported health nor Neck and shoulder pain last 4 weeks differed between the categories for any of the indicators. In the Dutch dataset (Table 1), gender was not related to any of the missing data indicators. Biological age and social desirability were inversely related to the Last response indicator.
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