Statistical harmonization of versions of measures across studies using external data: self-rated health and self-rated memory
Annals of Epidemiology. 2025-01-01; :
DOI: 10.1016/j.annepidem.2025.01.002
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Wu Y(1), Hayes-Larson E(1), Zhou Y(2), Bouteloup V(3), Zimmerman SC(4), Pederson
AM(5), Planche V(6), Seamans MJ(1), Westreich D(7), Maria Glymour M(5), Gibbons
LE(8), Dufouil C(3), Mayeda ER(9).
Author information:
(1)Department of Epidemiology, University of California, Los Angeles Fielding
School of Public Health, CA, USA.
(2)Department of Epidemiology, University of California, Los Angeles Fielding
School of Public Health, CA, USA; Department of Biostatistics, University of
California, Los Angeles Fielding School of Public Health, CA, USA.
(3)Univ. Bordeaux, Inserm, Bordeaux Population Health, UMR 1219, Bordeaux,
France; CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux, France.
(4)Department of Epidemiology and Biostatistics, University of California, San
Francisco, CA, USA.
(5)Department of Epidemiology and Biostatistics, University of California, San
Francisco, CA, USA; Department of Epidemiology, Boston University School of
Public Health, Boston, MA, USA.
(6)Univ. Bordeaux, CNRS, Institut des Maladies Neurodégénératives, UMR 5293,
Bordeaux, France; Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources
et de Recherche, CHU de Bordeaux, France.
(7)Department of Epidemiology, University of North Carolina Gillings School of
Global Public Health, Chapel Hill, North Carolina, USA.
(8)Department of Medicine, School of Medicine, University of Washington,
Seattle, WA, USA.
(9)Department of Epidemiology, University of California, Los Angeles Fielding
School of Public Health, CA, USA. Electronic address: .
PURPOSE: Harmonizing variables for constructs measured differently across
studies is essential for comparing, combining, and generalizing results. We
developed and fielded a brief survey to harmonize Likert and continuous versions
of measures for two constructs, self-rated health and self-rated memory, for use
in studies of French older adults.
METHODS: We recruited 300 participants from a French memory clinic in 2023 to
answer both the Likert and continuous versions of self-rated health and
self-rated memory questions. For each construct, we predicted responses to the
Likert version with multinomial and ordinal logistic models, varying
specifications of continuous version responses (linear or spline) and covariate
sets (question order, age, sex/gender, and interactions between the continuous
version and covariates). We also implemented a percentiles-based crosswalk
sensitivity analysis. We compared Cohen’s weighted kappa values to identify the
best statistical harmonization approach.
RESULTS: In the final models [multinomial models with continuous version spline,
question order (self-rated memory model only), age, sex/gender, and interactions
between the continuous version and covariates], weighted kappa values were 0.61
for self-rated health and 0.60 for self-rated memory, reflecting moderate
agreement.
CONCLUSIONS: Primary data collection feasibly facilitates statistical
harmonization of variables for constructs measured differently across studies.
Copyright © 2025. Published by Elsevier Inc.
DOI: 10.1016/j.annepidem.2025.01.002
PMID: 39800088
Conflict of interest statement: Declaration of Competing Interest The authors
declare that they have no known competing financial interests or personal
relationships that could have appeared to influence the work reported in this
paper. Conflict of Interest None declared.