       Document 1254
 DOCN  M9591254
 TI    Regression analysis of censored and truncated data: estimating
       reporting-delay distributions and AIDS incidence from surveillance data.
 DT    9509
 AU    Pagano M; Tu XM; De Gruttola V; MaWhinney S; Department of
       Biostatistics, Harvard School of Public Health,; Boston, Massachusetts
       02115.
 SO    Biometrics. 1994 Dec;50(4):1203-14. Unique Identifier : AIDSLINE
       MED/95306600
 AB    AIDS surveillance provides a vital source of information for health
       departments to assess the AIDS epidemic and to plan for future
       health-care needs. However, the use of surveillance data requires proper
       adjustments for the underreporting of AIDS cases caused by the delay in
       reporting diagnosed AIDS cases to the surveillance system. The
       statistical problem of adjusting for this underreporting concerns making
       inferences about an unobservable random sample of which only a portion
       is observed in a chronologic time interval defined by the analysis. Most
       regression methods for making inferences using right-truncated data
       employ a reverse-time hazard function, which requires that the observed
       data be transformed so that methods for left-truncated data can be
       applied. In this paper, we discuss fitting regression models to data
       that can be truncated and even censored in arbitrary intervals. The
       proposed methodology was applied to the national AIDS surveillance data
       provided by the Centers for Disease Control to analyze the trend of
       delays over chronologic time and variation among different geographic
       regions as well as across risk groups.
 DE    Acquired Immunodeficiency Syndrome/*EPIDEMIOLOGY  Algorithms
       Biometry/METHODS  Comparative Study  Demography  Human  Incidence
       *Models, Statistical  *Population Surveillance  Regression Analysis
       Support, U.S. Gov't, P.H.S.  United States/EPIDEMIOLOGY  JOURNAL ARTICLE

       SOURCE: National Library of Medicine.  NOTICE: This material may be
       protected by Copyright Law (Title 17, U.S.Code).

