You Say Tomato, I Say Radish: Can Brief Cognitive Assessments in the U.S. Health Retirement Study Be Harmonized With Its International Partner Studies?

Abstract

Objectives: To characterize the extent to which brief cognitive assessments administered in the population-representative U.S. Health and Retirement Study (HRS) and its International Partner Studies can be considered to be measuring a single, unidimensional latent cognitive function construct.

Methods: Cognitive function assessments were administered in face-to-face interviews in 12 studies in 26 countries (N = 155,690), including the U.S. HRS and selected International Partner Studies. We used the time point of the first cognitive assessment for each study to minimize differential practice effects across studies and documented cognitive test item coverage across studies. Using confirmatory factor analysis models, we estimated single-factor general cognitive function models and bifactor models representing memory-specific and nonmemory-specific cognitive domains for each study. We evaluated model fits and factor loadings across studies.

Results: Despite relatively sparse and inconsistent cognitive item coverage across studies, all studies had some cognitive test items in common with other studies. In all studies, the bifactor models with a memory-specific domain fit better than single-factor general cognitive function models. The data fit the models at reasonable thresholds for single-factor models in 6 of the 12 studies and for the bifactor models in all 12 of the 12 studies.

Discussion: The cognitive assessments in the U.S. HRS and its International Partner Studies reflect comparable underlying cognitive constructs. We discuss the assumptions underlying our methods, present alternatives, and future directions for cross-national harmonization of cognitive aging data.

Keywords: Cognitive function; Health survey; International comparison; Item response theory; Statistical harmonization.

Figure 1.

(A) A unidimensional factor analysis model in which common variation across observed cognitive tests is attributable to one latent variable, representing a cognitive function. (B) A bifactor model, in which a specific subfactor is added to account for covariation between Tests 2 and 3 that is greater than predicted from a unidimensional model. Observed test scores are shown in squares, while latent or unobserved variables are shown in circles. Arrows from latent variables to observed indicators represent factor loadings or relationships between the underlying latent variable and its observed indicators.