Publication type
Journal Article
Authors
Publication date
October 15, 2022
Summary:
A new approach to the analysis of heterogeneous categorical sequences is proposed. The first-order Markov model is employed in a finite mixture setting with initial state and transition probabilities being expressed as functions of time. The expectation–maximization algorithm approach to parameter estimation is implemented in the presence of positive equivalence constraints that determine which observations must be placed in the same class in the solution. The proposed model is applied to a dataset from the British Household Panel Survey to evaluate the association between the education background and life outcomes of study participants. The analysis of the survey data reveals many interesting relationships between the level of education and major life events.
Published in
Statistical Modelling
Volume and page numbers
Volume: 22 , p.457 -476
DOI
https://doi.org/10.1177/1471082X21989170
ISSN
1471082
Subjects
#547292