Extensions of Multiple-Group Item Response Theory Alignment: Application to Psychiatric Phenotypes in an International Genomics ConsortiumGRP Investigators, WGSPD Consortium, Mansolf, M., Vreeker, A., Reise, S. P., Freimer, N. B., Glahn, D. C., Gur, R. E., Moore, T. M., Pato, C. N., Pato, M. T., Palotie, A., Holm, M., Suvisaari, J., Partonen, T., Kieseppa, T., Paunio, T., Boks, M., Kahn, R., Ophoff, R. A., Bearden, C. E., Loohuis, L. O., Teshiba, T. & DeGeorge, D., 5-Feb-2020, In : Educational and Psychological Measurement. 40 p., 0013164419897307.
Research output: Contribution to journal › Article › Academic › peer-review
Large-scale studies spanning diverse project sites, populations, languages, and measurements are increasingly important to relate psychological to biological variables. National and international consortia already are collecting and executing mega-analyses on aggregated data from individuals, with different measures on each person. In this research, we show that Asparouhov and Muthen's alignment method can be adapted to align data from disparate item sets and response formats. We argue that with these adaptations, the alignment method is well suited for combining data across multiple sites even when they use different measurement instruments. The approach is illustrated using data from the Whole Genome Sequencing in Psychiatric Disorders consortium and a real-data-based simulation is used to verify accurate parameter recovery. Factor alignment appears to increase precision of measurement and validity of scores with respect to external criteria. The resulting parameter estimates may further inform development of more effective and efficient methods to assess the same constructs in prospectively designed studies.
|Number of pages||40|
|Journal||Educational and Psychological Measurement|
|Publication status||Published - 5-Feb-2020|
- test equating, differential item functioning, mega-analysis, harmonization, data integration, INTEGRATIVE DATA-ANALYSIS, VALIDATION, IMPUTATION, INTERVIEW, INFERENCE, VARIABLES, SYMPTOMS, SAMPLES, SCALES