Data Harmonization in Aging Research: Not so Fast

REFERENCES

• Bath, P. A., Deeg, D., & Poppelaars, J. (2010). The harmonisation of longitudinal data: A case study using data from cohort studies in The Netherlands and the United Kingdom. Ageing & Society, 30, 1419–1437. doi: 10.1017/S0144686X1000070X
   Web of Science ®Google Scholar
• Bauer, D. J., & Hussong, A. M. (2009). Psychometric approaches for developing commensurate measures across independent studies: Traditional and new models. Psychological Methods, 14, 101–125. doi: 10.1037/a0015583
   PubMed Web of Science ®Google Scholar
• Buhrmester, M., Kwang, T., & Gosling, S. (2011). Amazon’s Mechanical Turk: A new source of inexpensive, yet high quality, data? Perspectives on Psychological Science, 6, 3–5. doi: 10.1177/1745691610393980
   PubMed Web of Science ®Google Scholar
• Choi, S. W., Podrabsky, T., McKinney, N., Schalet, B. D., Cook, K. F., & Cella, D. (2012). PROSetta Stone® Analysis report: A Rosetta stone for patient reported outcomes (Vol. 1). Chicago, IL: Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University. Retrieved May 15, 2013, from http://www.prosettastone.org/AnalysisReport/Pages/default.aspx
   Google Scholar
• Curran, P. J., & Hussong, A. M. (2009). Integrative data analysis: The simultaneous analysis of multiple data sets. Psychological Methods, 14, 81–100. doi: 10.1037/a0015914
   PubMed Web of Science ®Google Scholar
• Curran, P. J., Hussong, A. M., Cai, L., Huang, W., Chassin, L., Sher, K. J., & Zucker, R. A. (2008). Pooling data from multiple longitudinal studies: The role of item response theory in integrative data analysis. Developmental Psychology, 44, 365–380. doi: 10.1037/0012-1649.44.2.365
   PubMed Web of Science ®Google Scholar
• Davidov, E., Schmidt, P., & Schwartz, S. H. (2008). Bringing values back in: The adequacy of the European social survey to measure values in 20 countries. Public Opinion Quarterly, 72, 420–445. doi: 10.1093/poq/nfn035
   Web of Science ®Google Scholar
• Embretson, S. E., & Reise, S. P. (2000). Item response theory for psychologists. Mahwah, NJ: Lawrence Erlbaum Associates.
   Google Scholar
• Finkel, D., Pedersen, N., & McGue, M. (1995). Genetic influences on memory performance in adulthood: Comparison of Minnesota and Swedish twin studies. Psychology and Aging, 10, 437–446. doi: 10.1037/0882-7974.10.3.437
   PubMed Web of Science ®Google Scholar
• Fortier, I., Doiron, D., Wolfson, C., & Raina, P. (2012). Harmonizing data for collaborative research on aging: Why should we foster such an agenda? Canadian Journal on Aging / La Revue Canadienne Du Vieillissement, 31, 95–99. doi: 10.1017/S0714980811000729
   PubMed Web of Science ®Google Scholar
• Gatz, M., Pedersen, N. L., Plomin, R., Nesselroade, J. R., & McClearn, G. E. (1992). The importance of shared genes and shared environments for symptoms of depression in older adults. Journal of Abnormal Psychology, 101, 701–708. doi: 10.1037/0021-843X.101.4.701
   PubMed Web of Science ®Google Scholar
• Hambleton, R. K., & Jones, R. W. (1993). Comparison of classical test theory and item response theory and their applications to test development. Educational Measurement: Issues and Practice, 12, 38–47. doi: 10.1111/j.1745-3992.1993.tb00543.x
   Google Scholar
• Hamilton, C. M., Strader, L. C., Pratt, J. G., Maiese, D., Hendershot, T., Kwok, R. K., … Haines, J. (2011). The Phenx Toolkit: Get the most from your measures. American Journal of Epidemiology, 174, 253–260. doi: 10.1093/aje/kwr193
   PubMed Web of Science ®Google Scholar
• Horn, J. L., & McArdle, J. J. (1992). A practical and theoretical guide to measurement invariance in aging research. Experimental Aging Research, 18, 117–144. doi: 10.1080/03610739208253916
   PubMed Web of Science ®Google Scholar
• Johnson, W., Bouchard, T. J., Krueger, R. F., Jr., McGue, M., & Gottesman, I. I. (2004). Just one g: Consistent results from three test batteries. Intelligence, 32, 95−107. doi: 10.1016/S0160-2896(03)00062-X
   Web of Science ®Google Scholar
• Jones, R. N., & Fonda, S. J. (2004). Use of an IRT-based latent variable model to link different forms of the CES-D from the Health and Retirement Study. Social Psychiatry and Psychiatric Epidemiology, 39, 828–835.
   PubMed Web of Science ®Google Scholar
• Lee, J., Zamarro, G., Phillips, D., Angrisani, M., & Chien, S. (2011). RAND-harmonized ELSA data documentation, version: A. Retrieved December 28, 2012, from https://mmicdata.rand.org/meta/codebooks/RH_ELSA_Codebook.pdf
   Google Scholar
• Linacre, J. M. (2012). A user’s guide to WINSTEPS® MINISTEP Rasch-model computer programs. Program Manual 3.75.0. Beaverton, Oregon: Winsteps.com
   Google Scholar
• McArdle, J. J., Grimm, K. J., Hamagami, F., Bowles, R. P., & Meredith, W. (2009). Modeling life-span growth curves of cognition using longitudinal data with multiple samples and changing scales of measurement. Psychological Methods, 14, 126–149. doi: 10.1037/a0015857
   PubMed Web of Science ®Google Scholar
• McGue, M., & Christensen, K. (1997). Genetic and environmental contributions to depression symptomatology: Evidence from Danish twins 75 years of age and older. Journal of Abnormal Psychology, 106, 439–448. doi: 10.1037/0021-843X.106.3.439
   PubMed Web of Science ®Google Scholar
• Molenaar, D., van der Sluis, S., Boomsma, D. I., Haworth, C. M., Hewitt, J. K., Martin, N. G., … Dolan, C. V. (2013). Genotype by environment interactions in cognitive ability: A survey of 14 studies from four countries covering four age groups. Behavior Genetics, 43, 208–219. doi: 10.1007/s10519-012-9581-7
   PubMed Web of Science ®Google Scholar
• Paolacci, G., Chandler, J., & Ipeirotis, P. G. (2010). Running experiments on Amazon Mechanical Turk. Judgment and Decision Making, 5, 411–419.
   Web of Science ®Google Scholar
• Pedersen, N. L., Christensen, K., Dahl, A., Finkel, D., Franz, C. E., Gatz, M., … Reynolds, C. A. (2013). IGEMS: The consortium on interplay of genes and environment across multiple studies. Twin Research and Human Genetics, 16, 481–489. doi: 10.1017/thg.2012.110
   PubMed Web of Science ®Google Scholar
• Qualtrics. (2013). Qualtrics software, version 45634 of the Qualtrics Research Suite. Copyright ©. Provo, UT: Qualtrics. Retrieved from http://www.qualtrics.com
   Google Scholar
• Radloff, L. (1977). A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385–401. doi: 10.1177/014662167700100306
   Web of Science ®Google Scholar
• Reise, S. P., & Widaman, K. F. (1999). Assessing the fit of measurement models at the individual level: A comparison of item response theory and covariance structure approaches. Psychological Methods, 4, 3–21. doi: 10.1037/1082-989X.4.1.3
   Web of Science ®Google Scholar
• Roth, M., Tym, E., Mountjoy, C. Q., Huppert, F. A., Hendrie, H., Verma, S., & Goddard, R. (1986). CAMDEX. A standardised instrument for the diagnosis of mental disorder in the elderly with special reference to the early detection of dementia. The British Journal of Psychiatry, 149, 698–709. doi: 10.1192/bjp.149.6.698
   PubMed Web of Science ®Google Scholar
• Schwarz, N. (1999). Self-reports: How the questions shape the answers. American Psychologist, 54, 93–105. doi: 10.1037/0003-066X.54.2.93
   Web of Science ®Google Scholar
• Sharp, E. S., Suthers, K. M., Crimmins, E., & Gatz, M. (2009). Does “No” mean “Sometimes”? How older adults respond to the same depression symptoms with different response formats. Clinical Gerontologist, 32, 371–378. doi: 10.1080/07317110903110385
   PubMed Web of Science ®Google Scholar
• Shipley, W. C. (1940). A self-administering scale for measuring intellectual impairment and deterioration. The Journal of Psychology, 9, 371–377. doi: 10.1080/00223980.1940.9917704
   Web of Science ®Google Scholar
• van Buuren, S., Eyres, S., Tennant, A., & Hopman-Rock, M. (2003). Assessing comparability of dressing disability in different countries by response conversion. The European Journal of Public Health, 13(Suppl. 3), 15–19. doi: 10.1093/eurpub/13.suppl_3.15
   PubMed Web of Science ®Google Scholar
• Velozo, C. A., Byers, K. L., Wang, Y.-C., & Joseph, B. R. (2007). Translating measures across the continuum of care: Using Rasch analysis to create a crosswalk between the functional independence measure and the minimum data set. The Journal of Rehabilitation Research and Development, 44, 467–478. doi: 10.1682/JRRD.2006.06.0068
   PubMed Web of Science ®Google Scholar
• Wright, B. D., Linacre, J. M., Gustafson, J.-E., & Martin-Löf, P. (1994). Reasonable mean-square fit values. Rasch Measurement Transactions, 8, 370.
   Google Scholar