Development and assessment of analytic methods to improve the measurement of cognition in longitudinal studies of aging through the use of substudies with comprehensive neuropsychological testing.

INTRODUCTION: The Health and Retirement Study International Partner Surveys (HRS IPS) have rich longitudinal data, but the brevity of cognitive batteries is a limitation. METHODS: We used data from a substudy of the English Longitudinal Study of Ageing (ELSA) administering detailed cognitive assessments with the Harmonized Cognitive Assessment Protocol (ELSA‐HCAP) (N = 1273) to inform approaches for estimating cognition in ELSA (N = 11,213). We compared two novel approaches: confirmatory factor analysis (CFA)‐ and regression‐based prediction. RESULTS: Compared to estimates from the full HCAP battery, estimated cognitive functioning derived using regression models or CFA had high correlations (regression: r = 0.85 [95% confidence interval [CI]: 0.83 to 0.87]; CFA: r = 0.83 [95% CI: 0.81 to 0.85]) and reasonable mean squared error (regression: 0.25 [0.22 to 0.27]; CFA: 0.29 [0.26 to 0.32]) in held‐out data. The use of additional items from waves 7 to 9 improved performance. DISCUSSION: Both approaches are recommended for future research; the similarity in approaches may be due to the brevity of available cognitive assessments in ELSA. Highlights: Estimates of cognitive functioning informed by English Longitudinal Study of Ageing‐Harmonized Cognitive Assessment Protocol (ELSA‐HCAP) data had an adequate performance.Standard errors were smaller for associations with example risks when using measures informed by ELSA‐HCAP.Performance was better when including additional cognitive measures available in waves 7 to 9.Conceptual advantages to the confirmatory factor analysis (CFA) approach were not important in practice due to the brevity of the ELSA cognitive battery. [ABSTRACT FROM AUTHOR]