Document Type
Report
Source Publication Title
Technical Report 319
Abstract
The paper extends the authors' earlier methods for estimating transition probabilities, by combining aggregate and haphazard recapture data, to the case of categorical covariates. Both fixed and time-dependent covariates are considered. A two-stage estimation procedure is proposed. The first stage uses a Markov model to estimate multivariate transition probabilities for the response and all covariates. The second stage uses the Stage 1 estimates to model covariate effects. The required number of sampling waves depends only on the number of response levels and time-dependent covariate levels — and not on the number of fixed covariate levels. Recommendations are given for the required sampling fraction — which decreases with the increasing population size — to obtain reliable results. A key improvement over the earlier work is the capability to estimate transition probabilities within small strata obtained by post-stratification of a large sample, without requiring the strata sample sizes to be large.
Disciplines
Mathematics | Physical Sciences and Mathematics
Publication Date
1-1-1997
Language
English
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Han, Chien-Pai and Hawkins, D. L., "Estimating Transition Probabilities from Aggregate Samples Augmented by Haphazard Recaptures II. The Case of Covariates." (1997). Mathematics Technical Papers. 220.
https://mavmatrix.uta.edu/math_technicalpapers/220