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Presentation on multilevel modeling using Stata, July 26th, noon, 6050 ISR

Frey's new report explores how the changing US electorate could shape the next 5 presidential elections, 2016 to 2032

U-M's Data Science Initiative offers expanded consulting services via CSCAR

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Adjusting for Time-Varying Confounding in Survival Analysis

Publication Abstract

Barber, Jennifer S., Susan A. Murphy, and N. Verbitsky. 2004. "Adjusting for Time-Varying Confounding in Survival Analysis." Sociological Methodology, 34:163-192.

In this paper we illustrate how directly including endogenous time-varying confounders in the model of the effect of an exposure on a response can lead to bias in discrete time survival analysis. An alternative to this method is Hern·n, Brumback and Robinsí (1999) use of sample weights to adjust for endogenous

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