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ISSN: 2155-6180

Journal of Biometrics & Biostatistics
Open Access

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Research Article

Visualizing Transitions between Multiple States–Illustrated by Analysis of Social Transfer Payments

Jacob Pedersen1, Jakob Bue Bjorner1,2,3 and Karl Bang Christensen2*

1National Research Centre for the Working Environment, Copenhagen, Denmark

2Department of Public Health, University of Copenhagen, Denmark

3QualityMetric, Lincoln, RI, USA

*Corresponding Author:
Karl Bang Christensen
Department of Public Health
University of Copenhagen, Denmark
E-mail: [email protected]

Received Date: August 19, 2013; Accepted Date: September 27, 2013; Published Date: September 29, 2013

Citation: Pedersen J, Bjorner JB, Christensen KB (2013) Visualizing Transitions between Multiple States–Illustrated by Analysis of Social Transfer Payments. J Biomet Biostat 4:175. doi:10.4172/2155-6180.1000175

Copyright: © 2013 Pedersen J,, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Background: Multi-state analyses are used increasingly in areas such as economic, medical, and social research. They provide a powerful analysis for situations where the research subjects move between several distinct states, but results are often complex. The purpose of the current paper is to present a simple descriptive analysis to visualize patterns in the transitions: the Top10 chart. Data on social transfer payments are used to illustrate the approach. Methods: spent in each state, and is constructed from individual level data. Persons with the same pattern of transitions between states are grouped together and average durations are calculated. We analyzed data from 4950 Danish employees aged 18-59 years who, during two years of follow-up, could at any time be in one of seven mutually exclusive states: work, unemployment, sick-listing, studying, parent leave, disability pension, and an absorbing state consisting of those who died, retried, or emigrated. Results: The 10 most frequent transitional patterns described 84% of all women and 90% of all men in the sample. For women, the typical patterns involved working throughout the study (61.7%), patterns with sick-listing (12.0%), patterns with unemployment (5.3%), patterns with parent leave (3.6%), and studying (1.5%). For men, the typical patterns involved working throughout (68.8%), sick-listing (9.1%), unemployment (4.7%), parent leave (5.2%), and studying (0.9%). Conclusion: The Top10 chart provides a simple descriptive visualization of complex transitional patterns.

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