Back to Annual Meeting Page		American Public Health Association 133rd Annual Meeting & Exposition December 10-14, 2005 Philadelphia, PA

Abstract #110298

Adam C. Carle, MA, PhD, Statistical Research Division, U.S. Census Bureau, Center for Survey Methods Research, Washington, DC 20233-9100, 301-763-1863, adam.c.carle@census.gov

The possibility exists that a measurement instrument is not equally valid across cultural groups. Measurement bias, a form of non-sampling error, occurs when individuals equivalent on true levels of a variable, but from different groups, do not have identical probabilities of observed scores. Bias can lead to inaccurate diagnoses, attenuate or accentuate group differences, and affect the validity and reliability of epidemiological studies. Previous research has suggested that Hispanics experience greater rates of depression as compared to non-Hispanic Caucasians. Likewise, research has demonstrated that Hispanics suffer from disparities in treatment of depression, and are less likely to receive adequate care. However, data addressing the cross-ethnic validity of the instruments used in these studies are lacking, leaving unclear whether findings reflect true differences, or are affected by measurement bias. Using data from the National Longitudinal Alcohol Epidemiological Survey (NLAES), a nationally representative household survey of 42,692 participants, the current paper addresses these issues and presents analyses exploring violations of measurement invariance on a standardized of depression across Hispanic and non-Hispanic Caucasians. The results of Confirmatory factor analysis for ordered-categorical measures (CFA-OCM) describe the presence and extent of measurement bias across these groups, discuss its role in clinical diagnoses, address the degree to which group differences on the observed scores can be validly interpreted, and demonstrate the importance of establishing measurement invariance prior to making epidemiological estimates. Further implications with respect to public health, prevention, and intervention are discussed.

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