On the Use of Aggregate Survey Data for Estimating Regional Major Depressive Disorder Prevalence.
Psychometrika
; 87(1): 344-368, 2022 03.
Article
en En
| MEDLINE
| ID: mdl-34487315
ABSTRACT
Major depression is a severe mental disorder that is associated with strongly increased mortality. The quantification of its prevalence on regional levels represents an important indicator for public health reporting. In addition to that, it marks a crucial basis for further explorative studies regarding environmental determinants of the condition. However, assessing the distribution of major depression in the population is challenging. The topic is highly sensitive, and national statistical institutions rarely have administrative records on this matter. Published prevalence figures as well as available auxiliary data are typically derived from survey estimates. These are often subject to high uncertainty due to large sampling variances and do not allow for sound regional analysis. We propose a new area-level Poisson mixed model that accounts for measurement errors in auxiliary data to close this gap. We derive the empirical best predictor under the model and present a parametric bootstrap estimator for the mean squared error. A method of moments algorithm for consistent model parameter estimation is developed. Simulation experiments are conducted to show the effectiveness of the approach. The methodology is applied to estimate the major depression prevalence in Germany on regional levels crossed by sex and age groups.
Palabras clave
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Trastorno Depresivo Mayor
Tipo de estudio:
Prevalence_studies
/
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Psychometrika
Año:
2022
Tipo del documento:
Article