%0 Book Section %B Explorations in the Economics of Aging %D 2011 %T Cognition and Economic Outcomes %A John J McArdle %A James P Smith %A Robert J. Willis %E David A Wise %K Health Conditions and Status %B Explorations in the Economics of Aging %I University of Chicago Press %C Chicago %G eng %4 cognition %$ 23450 %! Cognition and Economic Outcomes %0 Report %D 2011 %T Cognitive Aging and Human Capital %A John J McArdle %A Robert J. Willis %K Health Conditions and Status %K Net Worth and Assets %I University of Michigan %G eng %4 human Capital/Cognitive ability/Aging %$ 62830 %0 Journal Article %J Perspect Psychol Sci %D 2010 %T Contemporary Modeling of Gene × Environment Effects in Randomized Multivariate Longitudinal Studies. %A John J McArdle %A Carol A Prescott %X

There is a great deal of interest in the analysis of Genotype × Environment interactions (G×E). There are some limitations in the typical models for the analysis of G×E, including well-known statistical problems in identifying interactions and unobserved heterogeneity of persons across groups. The impact of a treatment may depend on the level of an unobserved variable, and this variation may dampen the estimated impact of treatment. Some researchers have noted that genetic variation may sometimes account for unobserved, and hence unaccounted for, heterogeneity. The statistical power associated with the G×E design has been studied in many different ways, and most results show that the small effects expected require relatively large or nonrepresentative samples (i.e., extreme groups). In this article, we describe some alternative approaches, such as randomized designs with multiple measures, multiple groups, multiple occasions, and analyses, to identify latent (unobserved) classes of people. These approaches are illustrated with data from the Aging, Demographics, and Memory Study (part of the Health and Retirement Study) examining the relations among episodic memory (based on word recall), APOE4 genotype, and educational attainment (as a proxy for an environmental exposure). Randomized clinical trials (RCTs) and randomized field trials (RFTs) have multiple strengths in the estimation of causal influences, and we discuss how measured genotypes can be incorporated into these designs. Use of these contemporary modeling techniques often requires different kinds of data be collected and encourages the formation of parsimonious models with fewer overall parameters, allowing specific G×E hypotheses to be investigated with a reasonable statistical foundation.

%B Perspect Psychol Sci %I 5 %V 5 %P 606-21 %8 2010 Sep %G eng %N 5 %1 http://www.ncbi.nlm.nih.gov/pubmed/22472970?dopt=Abstract %2 PMC3004154 %4 Genome-Wide Association Study/Genome-Wide Association Study/Genotyping/Environment/Methodology/genetics/genetics %$ 25290 %R 10.1177/1745691610383510 %0 Book Section %B The Sage Handbook of Measurement %D 2009 %T Contemporary Challenges of Longitudinal Measurement Using HRS Data %A John J McArdle %E Geoffrey Walford %E Eric Tucker %E Madhu Viswanathan %K Methodology %B The Sage Handbook of Measurement %I Sage Publications %C London %G eng %4 Methodology %$ 25270 %& 26 %R https://dx.doi.org/10.4135/9781446268230.n26