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Frey and colleagues outline 10 trends showing scale of America's demographic transitions

Starr says surveys intended to predict recidivism assign higher risk to poor

Prescott and colleagues find incidence of noncompetes in U.S. labor force varies by job, state, worker education

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PAA 2015 Annual Meeting: Preliminary program and list of UM participants

ISR addition wins LEED Gold Certification

PSC Fall 2014 Newsletter now available

Martha Bailey and Nicolas Duquette win Cole Prize for article on War on Poverty

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Mon, March 9
Luigi Pistaferri, Consumption Inequality and Family Labor Supply

Comparing Personal Trajectories and Drawing Causal Inferences From Longitudinal Data

Archived Abstract of Former PSC Researcher

Raudenbush, Stephen W. 2001. "Comparing Personal Trajectories and Drawing Causal Inferences From Longitudinal Data." Annual Review of Psychology, 52 : 501-525.

This review considers statistical analysis of data from studies that obtain repeated measures on each of many participants. Such studies aim to describe the average change in populations and to illuminate individual differences in trajectories of change. A person-specific model for the trajectory of each participant is viewed as the foundation of any analysis having these aims. A second, between-person model describes how persons vary in their trajectories. This two-stage modeling framework is common to a variety of popular analytic approaches variously labeled hierarchical models, multilevel models, latent growth models, and random coefficient models. Selected published examples reveal how the approach can be flexibly adapted to represent development in domains as diverse as vocabulary growth in early childhood, academic learning, and antisocial propensity during adolescence. The review then considers the problem of drawing causal inferences from repeated measures data.

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