{"id":166,"date":"2023-10-17T18:33:41","date_gmt":"2023-10-18T01:33:41","guid":{"rendered":"https:\/\/live-usc-dornsife.pantheonsite.io\/erik-meijer\/?page_id=166"},"modified":"2026-01-14T17:10:49","modified_gmt":"2026-01-15T01:10:49","slug":"papers","status":"publish","type":"page","link":"https:\/\/dornsife.usc.edu\/erik-meijer\/papers\/","title":{"rendered":"Papers"},"content":{"rendered":"\n\n \n \n\n\n\n\n\n\n\n
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Journal articles<\/h2>\n

Nichols, E., et al. (2026). Exploring the association between higher education and steeper cognitive decline in a nationally representative longitudinal study in India. American Journal of Epidemiology<\/i>. In press.<\/p>\n

Hernandez, R., et al. (2025). Can response time adjustments to question demands together with average response time distinguish between levels of satisficing? Findings from three surveys in a large U.S. panel study. Journal of Survey Statistics and Methodology<\/i>. In press.<\/p>\n

Meijer, E., & Liu, Y. (2025). Missing data and imputation in the international studies following the Harmonized Cognitive Assessment Protocol. Journals of Gerontology Series B: Psychological<\/i> <\/i>Sciences and Social Sciences<\/i>. In press. https:\/\/doi.org\/10.1093\/geronb\/gbaf223<\/a><\/p>\n

Nichols, E., et al. (2025). Key research priorities in methodological approaches for measuring the exposome and studying its role in the development of dementia. Alzheimer\u2019s & Dementia<\/i>, 21<\/i>, e70928. https:\/\/doi.org\/10.1002\/alz.70928<\/a><\/p>\n

Nichols, E., Gross, A. L., Hayes-Larson, E., Meijer, E., Kobayashi, L. C., & Lee, J. (2025). Estimating cognitive decline in longitudinal studies with high mortality and a long interwave period: A comparison of approaches and considerations around integrating end-of-life interview data. Alzheimer\u2019s & Dementia<\/i>, 21<\/i>, e70951. https:\/\/doi.org\/10.1002\/alz.70951<\/a><\/p>\n

Meijer, E., Postepska, A., & Wansbeek, T. (2025). Handling multiple proxies. Empirical Economics<\/i>, 69<\/i>, 2901\u20132926. https:\/\/doi.org\/10.1007\/s00181-025-02825-x<\/a><\/p>\n

Gross, A. L., et al. (2025). Language, literacy, and sensory impairments and missing cognitive test scores in the Harmonized Cognitive Assessment Protocol of the China Health and Retirement Longitudinal Study. Aging Clinical and Experimental Research<\/i>, 37<\/i>, 146. https:\/\/doi.org\/10.1007\/s40520-0253-03039-y<\/a><\/p>\n

Nichols, E., Markot, M., Gross, A. L., Jones, R. N., Meijer, E., Schneider, S., & Lee, J. (2025). The added value of metadata on test completion time for the quantification of cognitive functioning in survey research. Journal of the International Neuropsychological Society<\/i>, 31<\/i>, 117\u2013126. https:\/\/doi.org\/<\/a> 10.1017\/S1355617724000742<\/a><\/p>\n

Strangmann, I. M., et al. (2025). The association between multilingualism and cognitive function among literate and illiterate older adults with low education in India. Alzheimer\u2019s & Dementia: Behavior &<\/i> <\/i>Socioeconomics of Aging<\/i>, 1<\/i>, e70018. https:\/\/doi.org\/10.1002\/bsa3.70018<\/a><\/p>\n

Hernandez, R., et al. (2025). Evidence supports the validity and reliability of response times from a brief survey as a digital biomarker for processing speed in a large panel study. American Journal<\/i> <\/i>of Epidemiology<\/i>, 194<\/i>, 3208\u20133216. https:\/\/doi.org\/10.1093\/aje\/kwae478<\/a><\/p>\n

Snoke, J., Meijer, E., Phillips, D., Wilkens, J., & Lee, J. (2025). Synthesizing surveys with multiple units of observation: An application to the Longitudinal Aging Study in India. Journal of Survey Statistics<\/i> <\/i>and Methodology<\/i>, 13<\/i>, 420\u2013444. https:\/\/doi.org\/10.1093\/jssam\/smae047<\/a><\/p>\n

Petrosyan, S., et al. (2025). The association of multilingualism with diverse language families and cognition among adults with and without education in India. Neuropsychology<\/i>, 39<\/i>, 223\u2013234. https:\/\/doi.org\/10.1037\/neu0000988<\/a><\/p>\n

Maupin, D., Gao, H., Nichols, E., Gross, A., Meijer, E., & Jin, H. (2025). Dementia ascertainment in India and development of nation-specific cutoffs: A machine learning and diagnostic analysis. Alzheimer\u2019s<\/i> <\/i>& Dementia: Diagnosis, Assessment & Disease Monitoring<\/i>, 17<\/i>, e70049. https:\/\/doi.org\/10.1002\/dad2.70049<\/a><\/p>\n

Gao, H., et al. (2024). Early identification of cognitive impairment in community environments through modeling subtle inconsistencies in questionnaire responses: Machine learning model development and validation. JMIR Formative Research<\/i>, 8<\/i>, e54335. https:\/\/doi.org\/10.2196\/54335<\/a><\/p>\n

Schneider, S., et al. (2024). Can you tell people\u2019s cognitive ability level from their response patterns in questionnaires? Behavior Research Methods<\/i>, 56<\/i>, 6741\u20136758. https:\/\/doi.org\/10.3758\/s13428-024-02388-2<\/a><\/p>\n

Angrisani, M., et al. (2024). Modifiable risk factors for dementia in India: A cross-sectional study revisiting estimates and reassessing prevention potential and priorities. BMJ Public Health<\/i>, 2<\/i>, e001362. https:\/\/doi.org\/10.1136\/bmjph-2024-001362<\/a><\/p>\n

Lee, J., & Meijer, E. (2024). Different reasonable methodological choices can lead to vastly different estimates of the economic burden of diseases [Invited comment]. The Lancet Healthy Longevity<\/i>, 5<\/i>, e504\u2013e505. https:\/\/doi.org\/10.1016\/S2666-7568(24)00130-2<\/a><\/p>\n

Nichols, E., et al. (2024). Considerations for the use of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) in cross-country comparisons of cognitive aging and dementia. Alzheimer\u2019s<\/i> <\/i>& Dementia<\/i>, 20<\/i>, 4635\u20134648. https:\/\/doi.org\/10.1002\/alz.13895<\/a><\/p>\n

Geldsetzer, P., Chang, A. Y., Meijer, E., Sudharsanan, N., Charu, V., Kramlinger, P., & Haarburger, R. (2024). Interviewer biases in medical survey data: The example of blood pressure measurements. PNAS Nexus<\/i>, 3<\/i>(3), pgae109. https:\/\/doi.org\/10.1093\/pnasnexus\/pgae109<\/a><\/p>\n

Angrisani, M., Casanova, M., Lee, J., & Meijer, E. (2024). The economic burden of dementia in India. AEA<\/i> <\/i>Papers and Proceedings<\/i>, 114<\/i>, 418\u2013422. https:\/\/doi.org\/10.1257\/pandp.20241061<\/a><\/p>\n

Schneider, S., et al. (2024). Cognitive functioning and the quality of survey responses: An individual participant data meta-analysis of 10 epidemiological studies of aging. Journals of Gerontology:<\/i> <\/i>Psychological Sciences<\/i>, 79<\/i>(5), gbae030. https:\/\/doi.org\/10.1093\/geronb\/gbae030<\/a><\/p>\n

Kobayashi, L. C., et al. (2024). Cross-national comparisons of later-life cognitive function using data from the Harmonized Cognitive Assessment Protocol (HCAP): Considerations and recommended best practices. Alzheimer\u2019s & Dementia<\/i>, 20<\/i>, 2273\u20132281. https:\/\/doi.org\/10.1002\/alz.13694<\/a><\/p>\n

Hernandez, R., et al. (2024). Attrition from longitudinal ageing studies and performance across domains of cognitive functioning: An individual participant data meta-analysis. BMJ Open<\/i>, 14<\/i>, e079241. https:\/\/doi.org\/10.1136\/bmjopen-2023-079241<\/a><\/p>\n

Gross, A. L., et al. (2024). Prevalence of DSM-5 mild and major neurocognitive disorder in India: Results from the LASI-DAD. PLoS One<\/i>, 19<\/i>, e0297220. https:\/\/doi.org\/10.1371\/journal.pone.0297220<\/a><\/p>\n

Khobragade, P., et al. (2024). Performance of the Informant Questionnaire on Cognitive Decline for the Elderly (IQCODE) in a nationally representative study in India: The LASI-DAD study. International<\/i> <\/i>Psychogeriatrics<\/i>, 36<\/i>, 177\u2013187. https:\/\/doi.org\/10.1017\/S1041610222000606<\/a><\/p>\n

Schneider, S., et al. (2023). Using item response times in online questionnaires to detect mild cognitive impairment. Journals of Gerontology: Psychological Sciences<\/i>, 78<\/i>, 1278\u20131283. https:\/\/doi.org\/10.1093\/geronb\/gbad043<\/a><\/p>\n

Lee, J., et al. (2023). Prevalence of dementia in India: National and state estimates from a nationwide study. Alzheimer\u2019s & Dementia<\/i>, 19<\/i>, 2898\u20132912. https:\/\/doi.org\/10.1002\/alz.12928<\/a><\/p>\n

Lee, J., et al. (2023). Deep phenotyping and genomic data from a nationally representative study on dementia in India. Scientific Data<\/i>, 10<\/i>, 45. https:\/\/doi.org\/10.1038\/s41597-023-01941-6<\/a><\/p>\n

Junghaenel, D. U., et al. (2023). Inferring cognitive abilities from response times to web-administered survey items in a population-representative sample. Journal of Intelligence<\/em>, 11<\/em>(1), 3. https:\/\/doi.org\/10.3390\/jintelligence11010003<\/a><\/p>\n

Gatz, M., Schneider, S., Meijer, E., Darling, J. E., Orriens, B., Liu, Y., & Kapteyn, A. (2022). Identifying cognitive impairment among older participants in a nationally representative internet panel. Journals of Gerontology: Psychological Sciences<\/em>. https:\/\/doi.org\/10.1093\/geronb\/gbac172<\/a><\/p>\n

Meijer, E., Casanova, M., Kim, H., Llena-Nozal, A., & Lee, J. (2022). Economic costs of dementia in 11 countries in Europe: Estimates from nationally representative cohorts of a panel study. The Lancet Regional Health \u2013 Europe<\/em>, 20<\/em>, 100445. https:\/\/doi.org\/10.1016\/j.lanepe.2022.100445<\/a><\/p>\n

Schneider, S., Junghaenel, D. U., Meijer, E., Zelinski, E. M., Jin, H., Lee, P.-J., & Stone, A. A. (2022). Quality of survey responses at older ages predicts cognitive decline and mortality risk. Innovation in Aging<\/em>, 6<\/em>(3), 1\u201311. https:\/\/doi.org\/10.1093\/geroni\/igac027<\/a><\/p>\n

Schneider, S., Jin, H., Orriens, B., Junghaenel, D. U., Kapteyn, A., Meijer, E., & Stone, A. A. (2022). Using attributes of survey items to predict response times may benefit survey research. Field Methods<\/em>. https:\/\/doi.org\/10.1177\/1525822X221100904<\/a><\/p>\n

Liu, Y., Schneider, S., Orriens, B., Meijer, E., Darling, J. E., Gutsche, T., & Gatz, M. (2022). Self-administered web-based tests of executive functioning and perceptual speed: Measurement development study with a large probability-based survey panel. Journal of Medical Internet Research<\/em>, 24<\/em>(5), e34347. https:\/\/doi.org\/10.2196\/34347<\/a><\/p>\n

Meijer, E., Spierdijk, L., & Wansbeek, T. (2022). Moment conditions for the quadratic regression model with measurement error. Econometric Reviews<\/em>, 41<\/em>, 749\u2013774. https:\/\/doi.org\/10.1080\/07474938.2022.2052666<\/a><\/p>\n

Lee, J., Wilkens, J., Meijer, E., Sekher, T. V., Bloom, D. E., & Hu, P. (2022). Hypertension awareness, treatment, and control and their association with healthcare access in the middle-aged and older Indian population: A nationwide cohort study. PLoS Medicine<\/em>, 19<\/em>(1), e1003855. https:\/\/doi.org\/10.1371\/journal.pmed.1003855<\/a><\/p>\n

Schneider, S., Junghaenel, D. U., Zelinski, E. M., Meijer, E., Stone, A. A., Langa, K. M., & Kapteyn, A. (2021). Subtle mistakes in self-report surveys predict future transition to dementia. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring<\/em>, 13<\/em>(1), e12252. https:\/\/doi.org\/10.1002\/dad2.12252<\/a><\/p>\n

Jung, D., Lee, J., & Meijer, E. (2021). Revisiting the effect of retirement on cognition: Heterogeneity and endowment. Journal of the Economics of Ageing<\/em>, 21<\/em>, 100361. https:\/\/doi.org\/10.1016\/j.jeoa.2021.100361<\/a><\/p>\n

Jin, H., Chien, S., Meijer, E., Khobragade, P., & Lee, J. (2021). Learning from clinical consensus diagnosis in India to facilitate automatic classification of dementia: Machine learning study. JMIR Mental Health<\/em>, 8<\/em>(5), e27113. https:\/\/doi.org\/10.2196\/27113<\/a><\/p>\n

Lee, J., Meijer, E., Phillips, D., & Hu, P. (2021). Disability incidence rates for men and women in 23 countries: Evidence on health effects of gender inequality. Journals of Gerontology: Medical Sciences<\/em>, 76<\/em>, 328\u2013338. https:\/\/doi.org\/10.1093\/gerona\/glaa288<\/a><\/p>\n

Meijer, E., Oczkowski, E., & Wansbeek, T. (2021). How measurement error affects inference in linear regression. Empirical Economics<\/em>, 60<\/em>, 131\u2013155. https:\/\/doi.org\/10.1007\/s00181-020-01942-z<\/a><\/p>\n

Angrisani, M., Lee, J., & Meijer, E. (2020). The gender gap in education and late-life cognition: Evidence from multiple countries and birth cohorts. Journal of the Economics of Ageing<\/em>, 16<\/em>, 100232. https:\/\/doi.org\/10.1016\/j.jeoa.2019.100232<\/a><\/p>\n

Gross, A. L., Khobragade, P. Y., Meijer, E., & Saxton, J. A. (2020). Measurement and structure of cognition in the Longitudinal Aging Study in India \u2013 Diagnostic Assessment of Dementia. Journal of the American Geriatrics Society<\/em>, 68<\/em>, S11\u2013S19. https:\/\/doi.org\/10.1111\/jgs.16738<\/a><\/p>\n

Angrisani, M., Casanova, M., & Meijer, E. (2020). Work-life balance and labor force attachment at older ages. Journal of Labor Research<\/em>, 41<\/em>, 34\u201368. https:\/\/doi.org\/10.1007\/s12122-020-09301-8<\/a><\/p>\n

Kapteyn, A., et al. (2020). Tracking the effect of the COVID-19 pandemic on American households. Survey Research Methods<\/em>, 14<\/em>(2), 179\u2013186. https:\/\/doi.org\/10.18148\/srm\/2020.v14i2.7737<\/a><\/p>\n

Lee, J., Lau, S., Meijer, E., & Hu, P. (2020). Living longer, with or without disability? A global and longitudinal perspective. Journals of Gerontology: Medical Sciences<\/em>, 75<\/em>(1), 162\u2013167. https:\/\/doi.org\/10.1093\/gerona\/glz007<\/a><\/p>\n

Hurd, M. D., Meijer, E., Moldoff, M., & Rohwedder, S. (2019). Reducing cross-wave variability in survey measures of household wealth. Journal of Economic and Social Measurement<\/em>, 44<\/em>, 117\u2013139. https:\/\/doi.org\/10.3233\/JEM-190465<\/a><\/p>\n

Galesic, M., Bruine de Bruin, W., Dumas, M., Kapteyn, A., Darling, J. E., & Meijer, E. (2018). Asking about social circles improves election predictions and illuminates voting behaviour. Nature Human Behaviour<\/em>, 2<\/em>, 187\u2013193. https:\/\/doi.org\/10.1038\/s41562-018-0302-y<\/a><\/p>\n

Meijer, E., Spierdijk, L., & Wansbeek, T. (2017). Consistent estimation of linear panel data models with measurement error. Journal of Econometrics<\/em>, 200<\/em>, 169\u2013180. https:\/\/doi.org\/10.1016\/j.jeconom.2017.06.003<\/a><\/p>\n

Meijer, E., & Karoly, L. A. (2017). Representativeness of the low-income population in the Health and Retirement Study. Journal of the Economics of Ageing<\/em>, 9<\/em>, 90\u201399. https:\/\/doi.org\/10.1016\/j.jeoa.2016.08.004<\/a><\/p>\n

Angrisani, M., Hurd, M. D., Meijer, E., Parker, A. M., & Rohwedder, S. (2017). Personality and employment transitions at older ages: Direct and indirect effects through non-monetary job characteristics. Labour<\/em>, 31<\/em>, 127\u2013152. https:\/\/doi.org\/10.1111\/labr.12090<\/a><\/p>\n

Gutsche, T. L., Kapteyn, A., Meijer, E., & Weerman, B. (2014). The RAND Continuous 2012 Presidential Election Poll. Public Opinion Quarterly<\/em>, 78<\/em>, 233\u2013254. https:\/\/doi.org\/10.1093\/poq\/nfu009<\/a><\/p>\n

Galama, T. J., Hullegie, P., Meijer, E., & Outcault, S. (2012). Is there empirical evidence for decreasing returns to scale in a health capital model? Health Economics<\/em>, 21<\/em>, 1080\u20131100. PMCID:\u00a0PMC3412934; https:\/\/doi.org\/10.1002\/hec.2843<\/a><\/p>\n

Meijer, E., Rohwedder, S., & Wansbeek, T. (2012). Measurement error in earnings data: Using a mixture model approach to combine survey and register data. Journal of Business & Economic Statistics<\/em>, 30<\/em>, 191\u2013201. PMCID: PMC3604906; https:\/\/doi.org\/10.1198\/jbes.2011.08166<\/a><\/p>\n

Meijer, E., Kapteyn, A., & Andreyeva, T. (2011). Internationally comparable health indices. Health Economics<\/em>, 20<\/em>, 600\u2013619. PMCID: PMC3601939; https:\/\/doi.org\/10.1002\/hec.1620<\/a><\/p>\n

Meijer, E., Karoly, L. A., & Michaud, P.-C. (2010). Using matched survey and administrative data to estimate eligibility for the Medicare Part\u00a0D low-income subsidy program. Social Security Bulletin<\/em>, 70<\/em>(2), 63\u201382. http:\/\/www.socialsecurity.gov\/policy\/docs\/ssb\/v70n2\/<\/a><\/p>\n

Meijer, E., & Ypma, J. Y. (2008). A simple identification proof for a mixture of two univariate normal distributions. Journal of Classification<\/em>, 25<\/em>, 113\u2013123. https:\/\/doi.org\/10.1007\/s00357-008-9008-6<\/a><\/p>\n

Wansbeek, T., & Meijer, E. (2007). Comments on: Panel data analysis\u2014advantages and challenges. Test<\/em>, 16<\/em>, 33\u201336. https:\/\/doi.org\/10.1007\/s11749-007-0050-1<\/a><\/p>\n

Meijer, E., & Wansbeek, T. (2007). The sample selection model from a method of moments perspective. Econometric Reviews<\/em>, 26<\/em>, 25\u201351. https:\/\/doi.org\/10.1080\/07474930600972194<\/a><\/p>\n

Meijer, E. (2007). Citations, reference list, and author index with apacite. Eutypon<\/em>, 16\u201319<\/em>, 1\u201331. http:\/\/www.eutypon.gr\/eutypon\/e-cont-16-19.html<\/a><\/p>\n

Meijer, E., & Rouwendal, J. (2006). Measuring welfare effects in models with random coefficients. Journal of Applied Econometrics<\/em>, 21<\/em>, 227\u2013244. https:\/\/doi.org\/10.1002\/jae.841<\/a><\/p>\n

Meijer, E. (2005). Matrix algebra for higher order moments. Linear Algebra and its Applications<\/em>, 410<\/em>, 112\u2013134. https:\/\/doi.org\/10.1016\/j.laa.2005.02.040<\/a><\/p>\n

De Haan, J., Leertouwer, E., Meijer, E., & Wansbeek, T. (2003). Measuring central bank independence: A latent variables approach. Scottish Journal of Political Economy<\/em>, 50<\/em>, 326\u2013340. https:\/\/doi.org\/10.1111\/1467-9485.5003005<\/a><\/p>\n

Rouwendal, J., & Meijer, E. (2001). Preferences for housing, jobs, and commuting: A mixed logit analysis. Journal of Regional Science<\/em>, 41<\/em>, 475\u2013505. https:\/\/doi.org\/10.1111\/0022-4146.00227<\/a><\/p>\n

Wansbeek, T., Wedel, M., & Meijer, E. (2001). Comment on “Microeconometrics” by J.A. Hausman. Journal of Econometrics<\/em>, 100<\/em>, 89\u201391. https:\/\/doi.org\/10.1016\/S0304-4076(00)00065-8<\/a><\/p>\n

Meijer, E., & Wansbeek, T. (2000). Measurement error in a single regressor. Economics Letters<\/em>, 69<\/em>, 277\u2013284. https:\/\/doi.org\/10.1016\/S0165-1765(00)00328-1<\/a><\/p>\n

Meijer, E., & Wansbeek, T. (1999). Quadratic prediction of factor scores. Psychometrika<\/em>, 64<\/em>, 495\u2013507. https:\/\/doi.org\/10.1007\/BF02294569<\/a><\/p>\n

Busing, F. M. T. A., Meijer, E., & Van der Leeden, R. (1999). Delete-m <\/em>jackknife for unequal m<\/em>. Statistics and Computing<\/em>, 9<\/em>, 3\u20138. https:\/\/doi.org\/10.1023\/A:1008800423698<\/a><\/p>\n

Meijer, E., & Mooijaart, A. (1996). Factor analysis with heteroscedastic errors. British Journal of Mathematical and Statistical Psychology<\/em>, 49<\/em>, 189\u2013202. https:\/\/doi.org\/10.1111\/j.2044-8317.1996.tb01082.x<\/a><\/p>\n

Meijer, E., & Mooijaart, A. (1994). The use of third-order moments in structural models. Q\u00fcestii\u00f3<\/em>, 18<\/em>, 75\u201384. http:\/\/www.idescat.cat\/sort\/questiio\/sumaris\/sum181.html<\/a><\/p>\n

 <\/p>\n

Book chapters<\/h3>\n

Meijer, E., Spierdijk, L., & Wansbeek, T. (2015). Measurement error in panel data. In B. H. Baltagi (Ed.), The Oxford handbook of panel data<\/em> (pp.\u00a0325\u2013362). Oxford, UK: Oxford University Press. https:\/\/doi.org\/10.1093\/oxfordhb\/9780199940042.013.0011<\/a><\/p>\n

Kapteyn, A., & Meijer, E. (2014). A comparison of different measures of health and their relation to labor force transitions at older ages. In D. A. Wise (Ed.), Discoveries in the economics of aging<\/em> (pp. 115\u2013156). Chicago, IL: University of Chicago Press. (with a comment by S. F. Venti) https:\/\/doi.org\/10.7208\/chicago\/9780226146126.003.0004<\/a><\/p>\n

Meijer, E., Spierdijk, L., & Wansbeek, T. (2013). Measurement error in the linear dynamic panel data model. In B. C. Sutradhar (Ed.), ISS-2012 proceedings volume on longitudinal data analysis subject to measurement error, missing values and\/or outliers<\/em> (pp. 77\u201392). New York, NY: Springer. https:\/\/doi.org\/10.1007\/978-1-4614-6871-4_4<\/a><\/p>\n

Fernandes, M., Meijer, E., & Zamarro, G. (2008). Comparison between SHARE, ELSA, and HRS. In A. B\u00f6rsch-Supan et al. (Eds.), Health, ageing and retirement in Europe (2004\u20132007): Starting the longitudinal dimension<\/em> (pp. 23\u201363). Mannheim, Germany: Mannheim Research Institute for the Economics of Aging (MEA). http:\/\/www.share-project.org\/publications\/books0\/first-results-books.html<\/a><\/p>\n

De Leeuw, J., & Meijer, E. (2008). Introduction to multilevel analysis. In J. de Leeuw & E. Meijer (Eds.), Handbook of multilevel analysis<\/em> (pp.\u00a01\u201375). New York, NY: Springer. https:\/\/doi.org\/10.1007\/978-0-387-73186-5_1<\/a><\/p>\n

Van der Leeden, R., Meijer, E., & Busing, F. M. T. A. (2008). Resampling multilevel models. In J. de Leeuw & E. Meijer (Eds.), Handbook of multilevel analysis<\/em> (pp.\u00a0401\u2013433). New York, NY: Springer. https:\/\/doi.org\/10.1007\/978-0-387-73186-5_11<\/a><\/p>\n

Wansbeek, T., & Meijer, E. (2001). Measurement error and latent variables. In B. H. Baltagi (Ed.), A companion to theoretical econometrics<\/em> (pp. 162\u2013179). Malden, MA: Blackwell. https:\/\/doi.org\/10.1002\/9780470996249.ch9<\/a><\/p>\n

Meijer, E., Busing, F. M. T. A., & Van der Leeden, R. (1998). Estimating bootstrap confidence intervals for two-level models<\/a>. In J. J. Hox & E. D. De Leeuw (Eds.), Assumptions,robustness, and estimation methods in multivariate modeling<\/em> (pp. 35\u201347). Amsterdam, Netherlands: TT Publicaties.<\/p>\n

Busing, F. M. T. A., Meijer, E., & Van der Leeden, R. (1995). The MLA program for two-level analysis with resampling options<\/a>. In T. A. B. Snijders, B. Engel, J. C. van Houwelingen, A. Keen, G. J. Stemerdink, & M. Verbeek (Eds.), SSS\u201995: Toeval zit overal<\/em> (pp. 37\u201358). Groningen, Netherlands: iec ProGAMMA.<\/p>\n

 <\/p>\n

Books<\/h3>\n

De Leeuw, J., & Meijer, E. (Eds.). (2008). Handbook of multilevel analysis<\/em>. New York, NY: Springer. https:\/\/doi.org\/10.1007\/978-0-387-73186-5<\/a><\/p>\n

Wansbeek, T., & Meijer, E. (2000). Measurement error and latent variables in econometrics<\/em>. Amsterdam, Netherlands: North-Holland. Available from Amazon<\/a><\/p>\n

Meijer, E. (1998). Structural equation models for nonnormal data<\/em>. Leiden, Netherlands: DSWO Press.<\/p>\n

 <\/p>\n

Reports<\/h3>\n

Bugliari, D., et al. (2025a). RAND HRS detailed imputations file 2022 (v1) documentation<\/i>. Santa Monica, CA: RAND Center for the Study of Aging. https:\/\/hrsdata.isr.umich.edu\/data-products\/rand<\/a> (Also earlier versions under slightly different names [2013\u20132024])<\/p>\n

Bugliari, D., et al. (2025b). RAND HRS longitudinal file 2022 (v2) documentation<\/i>. Santa Monica, CA: RAND Center for the Study of Aging. https:\/\/hrsdata.isr.umich.edu\/data-products\/rand<\/a> (Also earlier versions under slightly different names [2013\u20132024])<\/p>\n

De La O, J., et al. (2025). Gateway harmonized HRS-HCAP documentation, version A.2<\/i>. Los Angeles, CA: Gateway to Global Aging Data. (Also earlier versions under slightly different names [2024]) https:\/\/doi.org\/10.25553\/sfaq-br29<\/a><\/p>\n

Chien, S., et al. (2025). Harmonized LASI-DAD documentation, version B.1 (2017\u20132024)<\/i>. Los Angeles, CA: Gateway to Global Aging Data. (Also earlier versions [2020\u20132024]) https:\/\/doi.org\/10.25553\/h5wx-ay45<\/a><\/p>\n

Wilkens, J., et al. (2024). Harmonized ELSA-HCAP documentation, version A.2<\/i>. Los Angeles, CA: Gateway to Global Aging Data. https:\/\/doi.org\/10.34729\/gmcv-6g43<\/a><\/p>\n

Chien, S., et al. (2023). Harmonized Mex-Cog documentation, version A.2<\/i>. Los Angeles, CA: Gateway to Global Aging Data. https:\/\/doi.org\/10.34729\/3JTX-WE73<\/a><\/p>\n

Chien, S., et al. (2023). Harmonized LASI documentation, version A.3<\/i>. Los Angeles, CA: Gateway to Global Aging Data. https:\/\/doi.org\/10.25549\/h-lasi<\/a> (Also earlier versions under slightly different names [2020\u20132021])<\/p>\n

LASI-DAD Study Collaborators. (2022). Harmonized diagnostic assessment of dementia for the<\/i> <\/i>Longitudinal Aging Study in India (LASI-DAD) wave 1 report<\/i>. Los Angeles, CA: University of Southern California, Center for Economic and Social Research. https:\/\/doi.org\/10.34729\/HAKB-5045<\/a><\/p>\n

LASI Investigators. (2021). User guide for 2017\u20132019 Longitudinal Aging Study in India (LASI) wave 1<\/em>. Los Angeles, CA: University of Southern California, Center for Economic and Social Research. https:\/\/g2aging.org<\/a><\/p>\n

Angrisani, M., Kapteyn, A., Meijer, E., & Saw, H.-W. (2019). Sampling and weighting the Understanding America Study (Working Paper No. 2019-004). Los Angeles, CA: University of Southern California, Center for Economic and Social Research. https:\/\/doi.org\/10.2139\/ssrn.3502405<\/a><\/p>\n

Hurd, M. D., Meijer, E., Pantoja, P., & Rohwedder, S. (2018). Addition to the RAND HRS longitudinal files: IRA withdrawals in the HRS, 2000 to 2014<\/em> (Working Paper No. WP 2018-388). Ann Arbor, MI: Michigan Retirement Research Center. https:\/\/doi.org\/10.2139\/ssrn.3337842<\/a><\/p>\n

Pantoja, P., et al. (2018). RAND HRS tax calculations 2014 (V2) documentation<\/em>. Santa Monica, CA: RAND Corporation, Center for the Study of Aging. Available from http:\/\/hrsonline.isr.umich.edu\/modules\/meta\/rand\/index.html<\/a> (Also an earlier version under a slightly different name [2017])<\/p>\n

Beaumaster, S., et al. (2017). Harmonized SHARE documentation, version D.4<\/em>. Los Angeles, CA: University of Southern California, Center for Economic and Social Research. https:\/\/g2aging.org<\/a> (Also earlier versions [2011\u20132017])<\/p>\n

Sikoki, B., Witoelar, F., Strauss, J., Meijer, E., & Suriastini, W. (2013). IFLS East user’s guide and field report<\/em>. Yogyakarta, Indonesia: SurveyMETER. http:\/\/surveymeter.org\/research\/3\/iflseast<\/a><\/p>\n

Chien, S., Feeney, K., Liu, J., Meijer, E., & Lee, J. (2013). Harmonized LASI pilot data documentation, version: A<\/em> (Working Paper No. WR-1018). Santa Monica, CA: RAND Corporation. https:\/\/doi.org\/10.2139\/ssrn.2354660<\/a><\/p>\n

Kapteyn, A., Meijer, E., & Weerman, B. (2012). Methodology of the RAND Continuous 2012 Presidential Election Poll<\/em> (Working Paper No. WR-961). RAND Corporation. https:\/\/doi.org\/10.2139\/ssrn.2146149<\/a><\/p>\n

Foster, K., Meijer, E., Schuh, S., & Zabek, M. A. (2011). The 2009 Survey of Consumer Payment Choice<\/em> (Public Policy Discussion Paper No. 11-01). Federal Reserve Bank of Boston. https:\/\/doi.org\/10.2139\/ssrn.1864854<\/a><\/p>\n

Lee, J., Kapteyn, A., Meijer, E., & Yang, J.-S. (2010). Pre- and post-retirement asset portfolios<\/em> (Publication No. 213). Filene Research Institute. http:\/\/staging.filene.org\/research\/report\/pre-and-post-retirement-asset-portfolios<\/a><\/p>\n

Foster, K., Meijer, E., Schuh, S., & Zabek, M. A. (2009). The 2008 Survey of Consumer Payment Choice<\/em> (Public Policy Discussion Paper No. 09-10). Federal Reserve Bank of Boston. https:\/\/doi.org\/10.2139\/ssrn.1559959<\/a><\/p>\n

Meijer, E., Karoly, L. A., & Michaud, P.-C. (2009). Estimates of potential eligibility for low-income subsidies under Medicare Part D<\/em> (Tech. Rep. No. TR-686). RAND Corporation. http:\/\/www.rand.org\/pubs\/technical_reports\/TR686\/<\/a><\/p>\n

Meijer, E. (2004). Computation of characteristics of value-of-time distributions and their standard errors<\/em> (Research Report No. 04F09). University of Groningen, SOM Research School. https:\/\/doi.org\/10.2139\/ssrn.2052669<\/a><\/p>\n

Busing, F. M. T. A., Meijer, E., & Van der Leeden, R. (1994). MLA: Software for multilevel analysis of data with two levels. User\u2019s guide for version 1.0b<\/em> (Tech. Rep. No. PRM 94-01<\/a>). Leiden University, Department of Psychology. (Version 4.1, 2005<\/a>)<\/p>\n

 <\/p>\n

Working papers<\/h3>\n

Kapteyn, A., et al. (2024). COVID-19 infections and cognitive function<\/i> (CESR-Schaeffer Working Paper No. 2024-003). Los Angeles, CA: University of Southern California. https:\/\/doi.org\/10.2139\/ssrn.4884504<\/a><\/p>\n

Perez-Arce, F., Prados, M., Meijer, E., & Lee, J. (2021). Social Security coverage around the world: The case of China, India and Mexico<\/em> (Working Paper No. WP 2021-439). Ann Arbor, MI: Michigan Retirement and Disability Research Center. https:\/\/mrdrc.isr.umich.edu\/publication_types\/working-papers\/<\/a><\/p>\n

Meijer, E., P\u00e9rez-Arce, F., & Prados, M. (2020). A framework for cost-benefit analysis of totalization agreements<\/em> (Working Paper No. WP 2020-410). Ann Arbor, MI: Michigan Retirement and Disability Research Center. https:\/\/doi.org\/10.2139\/ssrn.3885782<\/a><\/p>\n

Angrisani, M., Kapteyn, A., & Meijer, E. (2019). Sorting into jobs and labor supply and demand at older ages<\/em> (Working Paper). National Bureau of Economic Research. https:\/\/doi.org\/10.2139\/ssrn.3493892<\/a><\/p>\n

Prados, M. J., Meijer, E., & P\u00e9rez-Arce, F. (2019). Macroeconomic effects of social security totalization agreements<\/em> (Working Paper No. WP 2019-407). Ann Arbor, MI: Michigan Retirement and Disability Research Center. https:\/\/doi.org\/10.2139\/ssrn.3885751<\/a><\/p>\n

Angrisani, M., Casanova, M., & Meijer, E. (2017). Work-life balance and labor force attachment at older ages<\/em> (Working Paper No. WP 2017-366). Ann Arbor, MI: Michigan Retirement Research Center. https:\/\/doi.org\/10.2139\/ssrn.3110845<\/a><\/p>\n

Hurd, M. D., Meijer, E., Moldoff, M., & Rohwedder, S. (2016). Improved wealth measures in the Health and Retirement Study: Asset reconciliation and cross-wave imputation<\/em> (Working Paper No. WR-1150). Santa Monica, CA: RAND Corporation. https:\/\/doi.org\/10.2139\/ssrn.2791708<\/a><\/p>\n

Angrisani, M., Kapteyn, A., & Meijer, E. (2015). Nonmonetary job characteristics and employment transitions at older ages<\/em> (Working Paper No. WP 2015-326). Ann Arbor, MI: Michigan Retirement Research Center. https:\/\/doi.org\/10.2139\/ssrn.2689805<\/a><\/p>\n

Lee, J., Meijer, E., & Phillips, D. (2015). The effect of using different imputation methods for economic variables in aging surveys<\/em> (Working Paper No. 2015-019). Los Angeles, CA: University of Southern California, Center for Economic and Social Research. https:\/\/doi.org\/10.2139\/ssrn.2650214<\/a><\/p>\n

Angrisani, M., Hurd, M. D., & Meijer, E. (2012). Investment decisions in retirement: The role of subjective expectations<\/em> (Working Paper No. WP\u00a02012-274). Michigan Retirement Research Center. https:\/\/doi.org\/10.2139\/ssrn.2188403<\/a><\/p>\n

Hung, A. A., Meijer, E., Mihaly, K., & Yoong, J. (2009). Building up, spending down: financial literacy, retirement savings management, and decumulation<\/em> (Working Paper No. WR-712). RAND Corporation. https:\/\/doi.org\/10.2139\/ssrn.1520203<\/a><\/p>\n

Gilbert, P. D., & Meijer, E. (2006). Money and credit factors<\/em> (Working Paper No. 2006-3). Bank of Canada. http:\/\/www.bankofcanada.ca\/2006\/03\/publications\/research\/working-paper-2006-3\/<\/a><\/p>\n

Gilbert, P. D., & Meijer, E. (2005). Time series factor analysis with an application to measuring money<\/em> (Research Report No. 05F10). University of Groningen, SOM Research School. http:\/\/irs.ub.rug.nl\/ppn\/289322812<\/a><\/p>\n

Cools, K., Le Grand, H., Meijer, E., & Wansbeek, T. (2004). Solving the value metrics puzzle<\/em> (Working Paper). University of Groningen, Department of Economics. https:\/\/doi.org\/10.2139\/ssrn.568423<\/a><\/p>\n

 <\/p>\n

See also<\/em><\/p>\n

RAND: http:\/\/www.rand.org\/pubs\/authors\/m\/meijer_erik.html<\/a><\/p>\n

RePEc: http:\/\/ideas.repec.org\/f\/pme236.html<\/a><\/p>\n

SSRN: http:\/\/papers.ssrn.com\/sol3\/cf_dev\/AbsByAuth.cfm?per_id=386896<\/a><\/p>\n

 <\/p>\n

Other publications<\/h3>\n

Meijer, E., & Wansbeek, T. (2001, 2005). Microeconometrie<\/em> (Lecture Notes). Groningen, Netherlands: University of Groningen, Faculty of Economics.<\/p>\n

Meijer, E. (1999). [Book review of D. A. Harville (1997), Matrix algebra from a statistician’s perspective<\/em>]. Kwantitatieve Methoden<\/em>, 20<\/em>(60), 129\u2013131. (in Dutch)<\/p>\n

Rosenberg, F. A., Meurs, H., & Meijer, E. (1997). Grote prijsveranderingen: Een empirische budgetrestrictie-benadering [Large changes in prices: An empirical controlled budget approach]. In B. Egeter & N. Kalfs (Eds.), Colloquium Vervoersplanologisch Speurwerk \u2013 1997 \u2013 Sprong in het duister? Lange termijn ontwikkelingen in het vervoersplanologisch onderzoek<\/em> (pp. 1463\u20131482). Delft, Netherlands: C.V.S. http:\/\/www.cvs-congres.nl\/cvspdfdocs\/CVS1997deel3C.pdf<\/a> (in Dutch)<\/p>\n

Rosenberg, F. A., Meurs, H., & Meijer, E. (1997). Large changes in prices: An empirical controlled budget approach. In Policy, planning and sustainability: Proceedings of Seminars C and D held at the European Transport Forum Annual Meeting, Brunel University, England, 1\u20135 September 1997<\/em> (pp. 367\u2013378). London: PTRC. http:\/\/abstracts.aetransport.org\/paper\/index\/id\/548\/confid\/3<\/a><\/p>\n

Meurs, H., Meijer, E., & Pommer, J. (1997). No parking, no business? Verkeerskunde<\/em>, 48<\/em>(9), 30\u201334. (in Dutch)<\/p>\n

Meurs, H., Meijer, E., & Pommer, J. (1997). Parkeerkwaliteit langs de meetlat [A yardstick for parking quality]. Verkeerskunde<\/em>, 48<\/em>(7\/8), 30\u201334. (in Dutch)<\/p>\n

Busing, F. M. T. A., Van der Leeden, R., & Meijer, E. (1995). MLA: Software for two-level analysis with resampling options. Multilevel Modelling Newsletter<\/em>, 7<\/em>(3), 11\u201313. http:\/\/www.bristol.ac.uk\/cmm\/learning\/support\/new7-3.pdf<\/a><\/p>\n

Meijer, E., Van der Leeden, R., & Busing, F. M. T. A. (1995). Implementing the bootstrap for multilevel models. Multilevel Modelling Newsletter<\/em>, 7<\/em>(2), 7\u201311. http:\/\/www.bristol.ac.uk\/cmm\/learning\/support\/new7-2.pdf<\/a><\/p>\n\n\n\n<\/div>\n\n\n <\/div><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":635,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-166","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/dornsife.usc.edu\/erik-meijer\/wp-json\/wp\/v2\/pages\/166","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dornsife.usc.edu\/erik-meijer\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/dornsife.usc.edu\/erik-meijer\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/dornsife.usc.edu\/erik-meijer\/wp-json\/wp\/v2\/users\/635"}],"replies":[{"embeddable":true,"href":"https:\/\/dornsife.usc.edu\/erik-meijer\/wp-json\/wp\/v2\/comments?post=166"}],"version-history":[{"count":19,"href":"https:\/\/dornsife.usc.edu\/erik-meijer\/wp-json\/wp\/v2\/pages\/166\/revisions"}],"predecessor-version":[{"id":383,"href":"https:\/\/dornsife.usc.edu\/erik-meijer\/wp-json\/wp\/v2\/pages\/166\/revisions\/383"}],"wp:attachment":[{"href":"https:\/\/dornsife.usc.edu\/erik-meijer\/wp-json\/wp\/v2\/media?parent=166"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}