One essential feature common to all social and behavioral phenomena is variability across units of analysis at different levels, such as individual and family characteristics and contextual (such as neighborhood and clinic) characteristics. The development of statistical methods so as to better understand and accommodate such variability has been a major methodological achievement of modern social and behavioral sciences. Individuals differ greatly not only in background attributes but also in how they respond to a treatment, intervention, or stimulation. We call the second type of variability """"""""heterogeneous treatment effects."""""""" The proposed research assembles an interdisciplinary team, encompassing such diverse fields as statistics, sociology, psychiatry, economics, and public health, to develop methodological tools that can be used to better understand and investigate the consequences of both types of heterogeneity, with a special emphasis on heterogeneous treatment effects. Specifically, the proposed research has four aims: (1) It will illustrate, through empirical studies, the pervasiveness of heterogeneous treatment effects in social and behavioral sciences. Examples will be drawn from a variety of fields, using both experimental and observational data. (2) It will demonstrate, through micro-level simulations, that heterogeneity in treatment effects can give rise to composition biases in estimated treatment effects when selecting criteria for receiving treatment change. (3) It will develop a set of diagnostic and analytical tools that will help researchers and practitioners to detect and utilize heterogeneous treatment effects so as to better match interventions to the individual and/or social/clinic setting. Special attention will be paid to heterogeneous treatment effects in social, behavioral, and medical sciences. (4) To demonstrate the usefulness of the tools, it will apply the diagnostic and analytical tools to substantive research in three areas: (a) the effects of a job training program on the productivity of low-skilled workers, (b) the protective effect of a spouse on health among the elderly, and (c) the effectiveness of psychiatric treatments on mental health among veterans. 1 The proposed research will provide new knowledge and practical solutions on how to deal with heterogeneous treatment effects in social and behavioral sciences. This work has general implications for almost all research areas dealing with human subjects. In addition to scientific articles, a book resulting from the project will be produced that will be accessible to a wide variety of social, behavioral and medical scientists.

Agency
National Institute of Health (NIH)
Institute
National Institute of Nursing Research (NINR)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21NR010856-04
Application #
7847630
Study Section
Special Emphasis Panel (ZDA1-GXM-A (27))
Program Officer
Aziz, Noreen M
Project Start
2007-09-29
Project End
2012-05-31
Budget Start
2010-06-11
Budget End
2012-05-31
Support Year
4
Fiscal Year
2010
Total Cost
$258,336
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Miscellaneous
Type
Organized Research Units
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Zhou, Xiang; Xie, Y U (2016) Propensity Score-Based Methods versus MTE-Based Methods in Causal Inference: Identification, Estimation, and Application. Sociol Methods Res 45:3-40
Cheng, Siwei; Xie, Yu (2013) Structural effect of size on interracial friendship. Proc Natl Acad Sci U S A 110:7165-9
Xie, Yu (2013) Population heterogeneity and causal inference. Proc Natl Acad Sci U S A 110:6262-8
Xie, Yu; Zhou, Xiang (2012) Modeling individual-level heterogeneity in racial residential segregation. Proc Natl Acad Sci U S A 109:11646-51
Hoggatt, Katherine J; Flores, Marie; Solorio, Rosa et al. (2012) The ""Latina epidemiologic paradox"" revisited: the role of birthplace and acculturation in predicting infant low birth weight for Latinas in Los Angeles, CA. J Immigr Minor Health 14:875-84
Xie, Yu; Brand, Jennie E; Jann, Ben (2012) Estimating Heterogeneous Treatment Effects with Observational Data. Sociol Methodol 42:314-347
Tsai, Shu-Ling; Xie, Yu (2011) Heterogeneity in returns to college education: selection bias in contemporary taiwan. Soc Sci Res 40:796-810
Pfeiffer, Paul N; Valenstein, Marcia; Hoggatt, Katherine J et al. (2011) Electroconvulsive therapy for major depression within the Veterans Health Administration. J Affect Disord 130:21-5
Xie, Yu (2011) VALUES AND LIMITATIONS OF STATISTICAL MODELS. Res Soc Stratif Mobil 29:343-349
Xie, Yu (2011) CAUSAL INFERENCE AND HETEROGENEITY BIAS IN SOCIAL SCIENCE. Inf Knowl Syst Manage 10:279-289

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