Longitudinal administration of neuropsychological instruments are often used to assess age-related changes in cognition. Informative loss to follow-up may bias the results of these studies. Herein, we use auxiliary data to adjust for informative loss to follow-up. In the Einstein Aging Study, memory was assessed annually in a community sample of adults age 70+, free of dementia at baseline, using the free recall from the Free and Cued Selective Reminding Test, and via telephone using the Memory Impairment Screen for Telephone (the auxiliary data). Joint linear mixed models were used to assess how the effect of the APOE ε4 genotype may be affected by informative missingness in the in-person data. A total of 620 EAS participants contributed 2085 person years of follow-up to the analyses. Memory decline rates estimated in joint models were 19% greater in ε4 negative participants and 27% greater in ε4 positive participants compared to traditional approaches; the effect of APOE ε4 on memory decline was 37% greater. Joint modeling methods can help address bias caused by informative missing data in the estimation of the effect of risk factors on cognitive change, and may be applicable to a broader range of outcomes in longitudinal aging studies.
Keywords: Apolipoprotein E4; Bias (Epidemiology); Longitudinal Studies; Memory; Models; Risk Factors; Statistical.