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Thompson says America must "unchoose" policies that have led to mass incarceration

Axinn says new data on campus rape will "allow students to see for themselves the full extent of this problem"

Frey says white population is growing in Detroit and other large cities


Susan Murphy to speak at U-M kickoff for data science initiative, Oct 6, Rackham

Andrew Goodman-Bacon, former trainee, wins 2015 Nevins Prize for best dissertation in economic history

Deirdre Bloome wins ASA award for work on racial inequality and intergenerational transmission

Bob Willis awarded 2015 Jacob Mincer Award for Lifetime Contributions to the Field of Labor Economics

Next Brown Bag

Monday, Oct 5 at noon, 6050 ISR
Colter Mitchell: Biological consequences of poverty

Collaborative Research: On Latent Class Models of Measurement Error

a PSC Research Project [ARCHIVE DISPLAY]

Investigator:   Roger Tourangeau

This study will advance the knowledge about successful and efficient strategies for questionnaire development. It proposes a series of studies to investigate the use of latent class analysis (LCA) to assess questionnaire items. The LCA models can be used when two or more measures are available for the same latent class variable. The models can often be applied to extant data, since some surveys include multiple measures for key constructs and others routinely collect reinterview data. Surveys, and with them questionnaires, are used across many disciplines, some of which don't have access to large resources for questionnaire development and questionnaire testing. Finding a method that can draw knowledge about question performance from existing data (such as reinterview data) will be particularly useful.

Funding Period: 03/01/2006 to 02/28/2010

This PSC Archive record is displayed for historical reference.

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