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Application of ordinal logistic regression model to occupation data
People's occupational choices might be influenced by their parents' occupation, gender, previous experiences, ages, and their own education level. We can study the relationship of one's occupation choice with education level and father's occupation. The occupational choices will be the outcome varia...
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| Format: | Article |
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2009
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| LEADER | 00000njm a2000000a 4500 | ||
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| 001 | oai:repository.ui.edu.ng:123456789/7641 | ||
| 042 | |a dc | ||
| 720 | |a Adepoju, A. A. |e author | ||
| 720 | |a Adegbite, M. |e author | ||
| 260 | |c 2009 | ||
| 520 | |a People's occupational choices might be influenced by their parents' occupation, gender, previous experiences, ages, and their own education level. We can study the relationship of one's occupation choice with education level and father's occupation. The occupational choices will be the outcome variable which consists of categories of occupations. The regression methods are capable of allowing researchers to identify explanatory variables related to organizational programs and services that contribute to the overall staff status. These methods also permit researchers to estimate the magnitude of the effect of the explanatory variables on the outcome variable. Therefore, regression methods seem to be superior in studying the relationship between the explanatory and outcome variables. This study used ordinal logistic regression method to examine the relationship between the ordinal outcome variable, different levels of staff status in the Lagos State Civil Service of Nigeria, the explanatory variables are Gender, Indigenous status, Educational Qualification, Previous Experience and Age. The outcome variable was measured on an ordered, categorical, and three-point Likert scale as Junior staff Middle Management staff, and Senior Management staff. Within the complete models, the legit link was the better choice because of its satisfying parallel lines assumption and larger model- fitting statistics. The study revealed that two explanatory variables namely, Education Qualification and Previous Working Experience significantly predicted the probability of an individual staff being a member of any of the three levels of staff status | ||
| 024 | 8 | |a 1117 - 1693 | |
| 024 | 8 | |a ui_art_adepoju_application_2009 | |
| 024 | 8 | |a Journal of Scientific and Industrial Studies, 7(1), 2009. Pp. 39 - 49 | |
| 024 | 8 | |a http://ir.library.ui.edu.ng/handle/123456789/7641 | |
| 653 | |a Ordinal logistic regression | ||
| 653 | |a Proportional odds model | ||
| 653 | |a Binary logistic | ||
| 653 | |a Categorical data | ||
| 653 | |a Likert scale | ||
| 245 | 0 | 0 | |a Application of ordinal logistic regression model to occupation data |