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Activity Number: 329
Type: Contributed
Date/Time: Tuesday, August 8, 2006 : 2:00 PM to 3:50 PM
Sponsor: Section on Survey Research Methods
Abstract - #307562
Title: Estimation of Measurement Error and Identification of Causes in the Absence of Validation Data
Author(s): Andy Peytchev*+
Companies: University of Michigan
Address: 426 Thompson Street, Ann Arbor, MI, 48106-1248,
Keywords: measurement error ; interviewer effects ; two-stage model
Abstract:

In order to identify survey design factors that induce measurement error, validation data are needed. Gold standards are difficult to obtain and are of limited types. In the absence of truth, analyses commonly revert to differences in means, such as the Kish and Hansen, Hurwitz, and Bershad models for interviewer variance, and similar ANOVA models for comparisons of response scales. Proposed is a two-stage approach - the measurement error is first estimated through a predictive model and then it is modeled using hypothesized covariates. This two-stage model will be demonstrated on cumulated waves of the Survey of Consumer Attitudes to examine interviewer effects on measurement error. Effects of interviewer experience, call history, and current call characteristics on measurement error will also be estimated.

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