Powers

Daniel A. Powers

Professor of Sociology, University of Texas at Austin
Areas of Expertise:
  • Children & Families
  • Race & Ethnicity
  • Women

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About Daniel

Powers’ research focuses on health disparities, with a specific focus on the Hispanic infant mortality paradox and race/ethnic comparisons of change in infant mortality over time. Most of his substantive work is intertwined with his methodological interests in survival modeling, regression decomposition, age-period-cohort models, and other topics. In addition to his focus on the Hispanic paradox, Powers investigates race (black-white) differences in the sources of change in infant mortality using an age-period-cohort perspective. Powers applies state of the art statistical computing approaches to substantive problems, and is affiliate of the Population Research Center and faculty associate in the Department of Statistics and Data Sciences.

Briefs

Many Low Income Women in Texas Do Not Get the Effective Contraception They Want after Giving Birth

  • Kate Coleman-Minahan
  • Kari White
  • Daniel A. Powers
  • Chloe Dillaway
  • Amanda Stevenson
  • Kristine Hopkins
  • Daniel Grossman

Podcast

Publications

"Contraception after Delivery among Publicly Insured Women in Texas: Use Compared with Preference" (with Kate Coleman-Minahan, Kari White, Daniel A. Powers, Amanda Stevenson, and Chloe Dillaway). Obstetrics & Gynecology 130, no. 2 (2017): 393-402.

Assesses women's preferences for contraception after delivery and compares use with preferences.

Statistical Methods for Categorical Data Analysis (with Yu Xie) (Emerald Group Publishing Limited, 2008).

Presents the methods that form the core of contemporary categorical data analysis; both the transformational and latent variable approaches and so synthesizes similar methods in statistical and economic literatures. 

"Bayesian Ridge Estimations of Age-Period-Cohort Models" in Dynamic Demographic Analysis, edited by Robert Schoen (Springer Press, 2016), 337-359.

Shows that a Bayesian ridge regression model with a common prior for the shrinkage parameter yields estimated age, period, and cohort effects similar to those based on the intrinsic estimator. Allowing informative and non-informative priors on the shrinkage parameters associated with each temporal component produces results similar to mixed-effects APC models and the intrinsic estimator depending on the strength of the prior information on the shrinkage parameter for the cohort effects. 

"Erosion of Advantage: Decomposing Differences in Infant Mortality Rates among Older Non-Hispanic White and Mexican-Origin Mothers" Population Research and Policy Review 35, no. 1 (2016): 23-48.

Builds on findings from recent research showing an erosion of infant survival advantage in the Mexican-origin population relative to non-Hispanic whites at older maternal ages, with patterns that differ by nativity. Quantifies the degree to which differences in the distribution and effects of risk factors contribute to the infant mortality gap at older maternal ages across the three populations of interest.

"Paradox Revisited: A Further Investigation of Race/Ethnic Differences in Infant Mortality by Maternal Age" Demography 50, no. 2 (2013): 495-520.

Reexamines the epidemiological paradox of lower overall infant mortality rates in the Mexican-origin population relative to U.S.-born non-Hispanic whites. A comparison of infant mortality rates among U.S.-born non-Hispanic white and Mexican-origin mothers by maternal age reveals an infant survival advantage at younger maternal ages when compared with non-Hispanic whites accompanied by higher infant mortality at older ages for Mexican-origin women.

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