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Int J Popul Data Sci ; 5(1): 1150, 2020 Aug 13.
Article in English | MEDLINE | ID: mdl-33644405

ABSTRACT

INTRODUCTION: When designing longitudinal cohort studies, investigators must make decisions about study duration (i.e. length of follow-up) and frequency of outcome measurement. This research explores these design decisions for longitudinal cohort studies constructed using routinely-collected administrative data. OBJECTIVES: To illustrate the effects of varying study duration and frequency of outcome measurement in longitudinal cohort studies conducted using routinely-collected administrative data using a numeric example. METHODS: Linked administrative data from Manitoba, Canada were used. The cohort included mothers who experienced the death of an infant between April 1, 1999 and March 31, 2012 and a matched (three:one) group of mothers who did not experience an infant death. A generalized linear model was used to test for differences between groups in the non-linear (i.e. quadratic) and linear trend over time for the number of healthcare contacts. Holding sample size constant, models were fit to the data for various combinations of study duration and measurement frequency. Regression coefficient estimates and their standard errors were compared. RESULTS: A total of 2576 mothers were included; 644 experienced an infant death and 1932 were matches. Thirteen combinations of measurement frequency (one, two, three, four periods/year) and study duration (one, two, three, four years) were investigated. As frequency increased from one to four periods/year, the standard errors of the regression coefficients for the group difference in the non-linear trend (i.e. group-time-time interaction) decreased up to 98.9%. As duration increased from one to fours years, the standard errors decreased up to 96.9%. As frequency and duration increased, the estimated regression coefficients trended toward zero. Similar results were observed for the linear trend model. CONCLUSION: Longitudinal cohort studies based on administrative data offer flexibility in time-related design elements, but present potential challenges. Recommendations about how to select and report design decisions in studies should be included in reporting guidelines.

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