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Surprising findings on what influences unintended pregnancy from Wise, Geronimus and Smock

Recommendations on how to reduce discrimination resulting from ban-the-box policies cite Starr's work

Brian Jacob on NAEP scores: "Michigan is the only state in the country where proficiency rates have actually declined over time."

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Call for papers: Conference on computational social science, April 2017, U-M

Sioban Harlow honored with 2017 Sarah Goddard Power Award for commitment to women's health

Post-doc fellowship in computational social science for summer or fall 2017, U-Penn

ICPSR Summer Program scholarships to support training in statistics, quantitative methods, research design, and data analysis

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Mon, March 13, 2017, noon:
Rachel Best

Susan A. Murphy photo

Methodological challenges in constructing effective treatment sequences for chronic psychiatric disorders

Publication Abstract

Murphy, Susan A., David W. Oslin, A John Rush, and Ji Zhu. 2007. "Methodological challenges in constructing effective treatment sequences for chronic psychiatric disorders." Neuropsychopharmacology, 32(2): 257-262.

Psychiatric disorders are often chronic conditions that require sequential decision making to achieve the best clinical outcomes. Sequential decisions are necessary to accommodate treatment response heterogeneity, a variable course of illness, and the often heavy burden associated with intensive or longer-term treatment. Yet, only a few studies in this field have been designed to address sequential decisions. Most of the experimental designs and data analytic methods that are best suited for improving sequential clinical decision making are often found in nonmedical fields such as engineering, computer science, and statistics. Promising designs and methods are surveyed with a focus on those areas most immediately useful for informing clinical decision making.

DOI:10.1038/sj.npp.1301241 (Full Text)

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