Turnover modeling and event history analysis

  title={Turnover modeling and event history analysis},
  author={Rodney A. Mccloy and Justin Purl and Erin S. Banjanovic},
  journal={Industrial and Organizational Psychology},
  pages={320 - 325}
Speer, Dutta, Chen, and Trussell (2019) emphasized three words characteristic of the turnover field: “practical,” “modeling,” and “messier” (p. 277 [in the Abstract]), and advocated use of survival analysis (more generically, event history analysis, or EHA) as “a powerful tool for the purposes of turnover prediction [that] should be given consideration when planning turnover analyses” (p. 291). We agree and propose that this modeling approach best addresses the messy nature of practical… Expand
1 Citations
Artificial intelligence in personnel management: the development of APM model
Purpose Managers have mixed views of how artificial intelligence (AI) affects personnel management (PM). The purpose of this paper is to identify potential knowledge gap and bring new insights toExpand


Here to stay or go? Connecting turnover research to applied attrition modeling
Abstract Attrition modeling is a direct application of extant turnover research that can favorably impact workforce planning and action planning. However, while academic research enablesExpand
Reviewing employee turnover: focusing on proximal withdrawal states and an expanded criterion.
This work reconceptualizes employee turnover to promote researchers' understanding and prediction of why employees quit or stay in employing institutions and proposes "proximal withdrawal states" that motivate members to participate or withdraw from organizations as an expanded criterion. Expand
It’s About Time: Using Discrete-Time Survival Analysis to Study Duration and the Timing of Events
This article uses longitudinal data on the career paths of 3,941 special educators as a springboard, and derives maximum likelihood estimators for the parameters of a discrete-time hazard model and shows how the model can befit using standard logistic regression software. Expand
Statistical Models and Methods for Lifetime Data
  • G. Johnston
  • Computer Science, Mathematics
  • Technometrics
  • 2003
This book describes and illustrates how to compute a simple “naive” variance estimate and conŽ dence intervals that would be correct under the assumption of an underlying nonhomogeneous Poisson process model. Expand
Event-history analysis for left-truncated data.
  • G. Guo
  • Psychology, Medicine
  • Sociological methodology
  • 1993
Practical guidance for coping with social science event-history data that are left-truncated, especially when the length of exposure prior to observation is known is provided. Expand
The Statistical Analysis of Failure Time Data
This book complements the other references well, and merits a place on the bookshelf of anyone concerned with the analysis of lifetime data from any Ž eld. Expand
QUANTITATIVE METHODS IN PSYCHOLOGY Modeling the Days of Our Lives: Using Survival Analysis When Designing and Analyzing Longitudinal Studies of Duration and the Timing of Events
Psychologists studying whether and when events occur face unique design and analytic difficulties. The fundamental problem is how to handle censored observations, the people for whom the target eventExpand
Applied Longitudinal Data Analysis
PART I 1. A framework for investigating change over time 2. Exploring Longitudinal Data on Change 3. Introducing the multilevel model for change 4. Doing data analysis with the multilevel mode forExpand
An Alternative Approach: The Unfolding Model of Voluntary Employee Turnover
The model of employee turnover described in this paper applies constructs and concepts from decision making, statistics, and social psychology to facilitate understanding and to redirect theoryExpand
Event History Analysis