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Modeling college student persistence...

Chen, Sea-Shon.

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Modeling college student persistence: A logistic regression analysis approach.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Modeling college student persistence: A logistic regression analysis approach./
作者:	Chen, Sea-Shon.
面頁冊數:	233 p.
附註:	Source: Dissertation Abstracts International, Volume: 59-02, Section: A, page: 4270.
Contained By:	Dissertation Abstracts International59-02A.
標題:	Higher education. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9824701
ISBN:	9780591768510

Modeling college student persistence: A logistic regression analysis approach.
Chen, Sea-Shon.

Modeling college student persistence: A logistic regression analysis approach. - 233 p.

Source: Dissertation Abstracts International, Volume: 59-02, Section: A, page: 4270.

Thesis (Ph.D.)--The Florida State University, 1998.

This study was to construct student persistence models at a vocational and technical college in Taiwan to predict a student's probability of leaving college. Based on suicide, employee turnover, and social bond theories and relevant empirical research from 1970 to 1996, a conceptual model was presented. The logistic regressions produced primary and secondary persistence models, presented as figures and equations. The results also supported the statistical significance of ten variables (gender, entrance examination score, major department, first semester academic GPA, first semester social integration, housing, occupational guidance program, first semester gym grade, and second semester academic GPA) in the conceptual model. Pascarella and Chapman (1983) reported the pooled classification rate was 70%. In this study, the overall classification rates for the primary persistence model was 77% and for the secondary persistence model it was 78%. The primary and secondary persistence models can be used to calculate probability of persistence for freshman-year students at the end of first and second semesters.

ISBN: 9780591768510Subjects--Topical Terms:

641065
Higher education.

Modeling college student persistence: A logistic regression analysis approach.
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500 $a Source: Dissertation Abstracts International, Volume: 59-02, Section: A, page: 4270.
500 $a Major Professor: Hollie Thomas.
502 $a Thesis (Ph.D.)--The Florida State University, 1998.
520 $a This study was to construct student persistence models at a vocational and technical college in Taiwan to predict a student's probability of leaving college. Based on suicide, employee turnover, and social bond theories and relevant empirical research from 1970 to 1996, a conceptual model was presented. The logistic regressions produced primary and secondary persistence models, presented as figures and equations. The results also supported the statistical significance of ten variables (gender, entrance examination score, major department, first semester academic GPA, first semester social integration, housing, occupational guidance program, first semester gym grade, and second semester academic GPA) in the conceptual model. Pascarella and Chapman (1983) reported the pooled classification rate was 70%. In this study, the overall classification rates for the primary persistence model was 77% and for the secondary persistence model it was 78%. The primary and secondary persistence models can be used to calculate probability of persistence for freshman-year students at the end of first and second semesters.
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