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Bivariate transition model for analyzing ordinal and nominal categorical responses: An application to the Labour Force Survey data

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Bivariate transition model for analyzing ordinal and nominal categorical responses: An application to the Labour Force Survey data. / Rezaei Ghahroodi, Z; Ganjali, M; Harandi, F et al.
In: Journal of Applied Statistics, Vol. 38, No. 4, 04.2011, p. 817-832.

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Rezaei Ghahroodi Z, Ganjali M, Harandi F, Berridge D. Bivariate transition model for analyzing ordinal and nominal categorical responses: An application to the Labour Force Survey data. Journal of Applied Statistics. 2011 Apr;38(4):817-832. Epub 2011 Jan 6. doi: 10.1080/02664761003692324

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Rezaei Ghahroodi, Z ; Ganjali, M ; Harandi, F et al. / Bivariate transition model for analyzing ordinal and nominal categorical responses : An application to the Labour Force Survey data. In: Journal of Applied Statistics. 2011 ; Vol. 38, No. 4. pp. 817-832.

Bibtex

@article{1189a3ed85eb41a09f5a5bf8481134ac,
title = "Bivariate transition model for analyzing ordinal and nominal categorical responses: An application to the Labour Force Survey data",
abstract = "In many panel studies, bivariate ordinal–nominal responses are measured and the aim is to investigate the effects of explanatory variables on these responses. A regression analysis for these types of data must allow for the correlation among responses of the same individual. To analyse such ordinal–nominal responses using a proper weighting approach, an ordinal–nominal bivariate transition model is proposed and maximum likelihood is used to find the parameter estimates. We propose a method in which the likelihood function can be partitioned to make possible the use of existing software. The approach is applied to the Labour Force Survey data in Iran, where the ordinal response, at the first period, is the duration of unemployment for unemployed people and the nominal response, in the second period, is economic activity status of these individuals. The interest is to find the reasons for staying unemployed or moving to another status of economic activity.",
keywords = "duration of unemployment, economic activity status, survey data , ordinal–nominal association measure , pseudo-R 2",
author = "{Rezaei Ghahroodi}, Z and M Ganjali and F Harandi and Damon Berridge",
year = "2011",
month = apr,
doi = "10.1080/02664761003692324",
language = "English",
volume = "38",
pages = "817--832",
journal = "Journal of Applied Statistics",
issn = "1360-0532",
publisher = "Routledge",
number = "4",

}

RIS

TY - JOUR

T1 - Bivariate transition model for analyzing ordinal and nominal categorical responses

T2 - An application to the Labour Force Survey data

AU - Rezaei Ghahroodi, Z

AU - Ganjali, M

AU - Harandi, F

AU - Berridge, Damon

PY - 2011/4

Y1 - 2011/4

N2 - In many panel studies, bivariate ordinal–nominal responses are measured and the aim is to investigate the effects of explanatory variables on these responses. A regression analysis for these types of data must allow for the correlation among responses of the same individual. To analyse such ordinal–nominal responses using a proper weighting approach, an ordinal–nominal bivariate transition model is proposed and maximum likelihood is used to find the parameter estimates. We propose a method in which the likelihood function can be partitioned to make possible the use of existing software. The approach is applied to the Labour Force Survey data in Iran, where the ordinal response, at the first period, is the duration of unemployment for unemployed people and the nominal response, in the second period, is economic activity status of these individuals. The interest is to find the reasons for staying unemployed or moving to another status of economic activity.

AB - In many panel studies, bivariate ordinal–nominal responses are measured and the aim is to investigate the effects of explanatory variables on these responses. A regression analysis for these types of data must allow for the correlation among responses of the same individual. To analyse such ordinal–nominal responses using a proper weighting approach, an ordinal–nominal bivariate transition model is proposed and maximum likelihood is used to find the parameter estimates. We propose a method in which the likelihood function can be partitioned to make possible the use of existing software. The approach is applied to the Labour Force Survey data in Iran, where the ordinal response, at the first period, is the duration of unemployment for unemployed people and the nominal response, in the second period, is economic activity status of these individuals. The interest is to find the reasons for staying unemployed or moving to another status of economic activity.

KW - duration of unemployment

KW - economic activity status

KW - survey data

KW - ordinal–nominal association measure

KW - pseudo-R 2

UR - http://www.scopus.com/inward/record.url?scp=79551698682&partnerID=8YFLogxK

U2 - 10.1080/02664761003692324

DO - 10.1080/02664761003692324

M3 - Journal article

AN - SCOPUS:79551698682

VL - 38

SP - 817

EP - 832

JO - Journal of Applied Statistics

JF - Journal of Applied Statistics

SN - 1360-0532

IS - 4

ER -