American Statistical Association
We use data collected in the National Comorbidity Survey - Adolescent (NCS-A) to develop a methodology to estimate the small-area prevalence of serious emotional distress (SED) in schools in the United States, exploiting the clustering of the main NCS-A sample by school. The NCS-A instrument includes both a short screening scale, the K6, and extensive diagnostic assessments of the individual disorders and associated impairment that determine the diagnosis of SED. We fitted a Bayesian bivariate multilevel regression model with correlated effects for the probability of SED and a modified K6 score at the individual and school levels.
Our results provide evidence for the existence of variation in the prevalence of SED across schools and geographical regions. Although the concordance between the modified K6 scale and SED is only modest for individuals, the school-level random effects for the two measures are strongly correlated. Under this model, we obtain a prediction equation for the rate of SED based on the mean K6 score and covariates. This finding supports the feasibility of using short screening scales like the K6 as an alternative to more comprehensive lay assessments in estimating school-level rates of SED. These methods may be applicable to other studies aiming at small-area estimation for geographical units. This is a joint work with Alan Zaslavsky.
Dr. Fan Li received her Ph.D. from Johns Hopkins University Department of Biostatistics in 2006, and did postdoctoral research in Harvard University Department of Health Care Policy. Since 2008, she has been an Assistant Professor in the Department of Statistical Science at Duke University. Her research interests are Bayesian analysis, causal inference, small area estimation, and missing data.
|Date:||Tuesday, March 6, 2012|
|Time:||3:30 - 4:30 P.M.|
New York State Psychiatric Institute
1051 Riverside Drive
6th Floor Boardroom (6601)
New York, New York