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Longitudinal cohort studies (with three or more measurement occasions) enable researchers to examine between- and within-individual variation, providing an improved understanding of disease evolution.
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Alternative longitudinal study designs, such as the accelerated cohort, two-method measurement approach, and multiform design, increase efficiency of longitudinal designs by reducing time to research output and participant burden, while maintaining statistical power.
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Longitudinally collected
Alternative Design and Analytical Techniques for Longitudinal Rheumatology Studies: Improved Understanding of Outcomes
Section snippets
Key points
Alternative longitudinal designs using primary data
Planned missing data (PMD) designs with primary data collection include accelerated cohort, two-method, and multiform designs. These designs are efficient because they rely on strategically placed missing data, meaning that participants do not have the same measurement schedule.3, 6 Missing data in PMD designs are missing completely at random; accordingly, their absence does not result in biased study conclusions.13, 15 By reducing response burden on participants, PMD designs can potentially
Alternative longitudinal design using secondary data
Administrative data are collected for managing and monitoring the health care system and not for research purposes. Examples of administrative data are records of physician billing claims, hospitalizations, and emergency department visits. These data are usually collected by the government to produce official statistics.26 However, they are a potentially valuable resource for observational, longitudinal studies about chronic diseases. Rheumatologists are familiar with the use of administrative
Alternative longitudinal analytical methods
In this section, we discuss several examples of newer (but less commonly used) longitudinal models that enable researchers to make full use of all available data. These models are used in longitudinal cohort studies to address long-term therapeutic outcomes (marginal structural modeling); recurrent events, such as flares of disease (recurrent event modeling); and progression through various stages of disease (multistate modeling). All of these models have in common the ability to evaluate
Summary
We have shown in this review how alternative PMD designs are used to accelerate the time to research output, collect more information, and maintain or sometimes increase statistical power. We have also shown how advanced statistical models are used to provide estimations of unbiased treatment effects through adjustments of time-varying covariates, mediators, and confounders.45 Methods that use all available disease course data allowing the modeling of recurrent events or multistate events were
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Applying planned missingness designs to longitudinal panel studies in developmental science: An overview
2021, New Directions for Child and Adolescent DevelopmentUsing Registry Data to Understand Disease Evolution in Inflammatory Myositis and Other Rheumatic Diseases
2020, Current Rheumatology Reports
Disclosure: None of the authors has pertinent conflicts of interest.