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Western Kentucky University

Using Biodata to Predict Alternative Measures of Training Period Turnover

Abstract

dc:description.abstract

Logistic Regression was utilized to add to what is known about biodata and turnover. Biodata items from 958 former and current employees in a manufacturing environment were used to develop models to predict a) which employees will turnover prior to completion of a ninety-day training period, b) who will leave voluntarily versus involuntarily, and of those who leave voluntarily c) which leavers are functional versus dysfunctional. A significant relationship was found between biodata items and completion of the ninety-day training period. The resulting model indicated that those who completed training were employed at time of hire, had higher aptitude scores, and had a previous address close to the plant. In addition, those who left voluntarily had higher levels of performance than involuntary leavers. However, biodata items did not differentiate between voluntary and involuntary leavers or between functional and dysfunctional leavers.

Degree

thesis:*
Name thesis:degree_name
Master of Arts
Discipline thesis:degree_discipline
Department of Psychology
Year
1996

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Pankratz, Ronald

Subjects

dc:subject × 2

Identifiers

dc:identifier.*
Repository record dc:identifier
https://digitalcommons.wku.edu/theses/877
OAI identifier oai:identifier
oai:digitalcommons.wku.edu:theses-1880

Chain of custody

source
Harvested from
Western Kentucky University
Base URL
digitalcommons.wku.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Pankratz, Ronald. Using Biodata to Predict Alternative Measures of Training Period Turnover. 1996. https://digitalcommons.wku.edu/theses/877