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Longitudinal analysis of categorical epidemiological data: a study of Three Mile Island.
The accident at the Three Mile Island nuclear power plant in 1979 led to an unprecedented set of events with potentially life threatening implications. This paper focusses on the analysis of a longitudinal study of the psychological well-being of the mothers of young children living within 10 miles...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
1985
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1568476/ https://www.ncbi.nlm.nih.gov/pubmed/4076089 |
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author | Fienberg, S E Bromet, E J Follmann, D Lambert, D May, S M |
author_facet | Fienberg, S E Bromet, E J Follmann, D Lambert, D May, S M |
author_sort | Fienberg, S E |
collection | PubMed |
description | The accident at the Three Mile Island nuclear power plant in 1979 led to an unprecedented set of events with potentially life threatening implications. This paper focusses on the analysis of a longitudinal study of the psychological well-being of the mothers of young children living within 10 miles of the plant. The initial analyses of the data utilize loglinear/logit model techniques from the contingency table literature, and involve the fitting of a sequence of logit models. The inadequancies of these analyses are noted, and a new class of mixture models for logistic response structures is introduced to overcome the noted shortcomings. The paper includes a brief outline of the methodology relevant for the fitting of these models using the method of maximum likelihood, and then the model is applied to the TMI data. The paper concludes with a discussion of some of the substantive implications of the mixture model analysis. |
format | Text |
id | pubmed-1568476 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 1985 |
record_format | MEDLINE/PubMed |
spelling | pubmed-15684762006-09-18 Longitudinal analysis of categorical epidemiological data: a study of Three Mile Island. Fienberg, S E Bromet, E J Follmann, D Lambert, D May, S M Environ Health Perspect Research Article The accident at the Three Mile Island nuclear power plant in 1979 led to an unprecedented set of events with potentially life threatening implications. This paper focusses on the analysis of a longitudinal study of the psychological well-being of the mothers of young children living within 10 miles of the plant. The initial analyses of the data utilize loglinear/logit model techniques from the contingency table literature, and involve the fitting of a sequence of logit models. The inadequancies of these analyses are noted, and a new class of mixture models for logistic response structures is introduced to overcome the noted shortcomings. The paper includes a brief outline of the methodology relevant for the fitting of these models using the method of maximum likelihood, and then the model is applied to the TMI data. The paper concludes with a discussion of some of the substantive implications of the mixture model analysis. 1985-11 /pmc/articles/PMC1568476/ /pubmed/4076089 Text en |
spellingShingle | Research Article Fienberg, S E Bromet, E J Follmann, D Lambert, D May, S M Longitudinal analysis of categorical epidemiological data: a study of Three Mile Island. |
title | Longitudinal analysis of categorical epidemiological data: a study of Three Mile Island. |
title_full | Longitudinal analysis of categorical epidemiological data: a study of Three Mile Island. |
title_fullStr | Longitudinal analysis of categorical epidemiological data: a study of Three Mile Island. |
title_full_unstemmed | Longitudinal analysis of categorical epidemiological data: a study of Three Mile Island. |
title_short | Longitudinal analysis of categorical epidemiological data: a study of Three Mile Island. |
title_sort | longitudinal analysis of categorical epidemiological data: a study of three mile island. |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1568476/ https://www.ncbi.nlm.nih.gov/pubmed/4076089 |
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