| Abstract: | Traditional correlational and regression analyses of aggregated absences are ill-suited for estimating parameters of the absence-taking process. A class of event history models is described that effectively deals with the distributional and temporal properties of absences. One such model, a proportional hazard rate model, was applied to the daily attendance records of 2,130 incumbent, white-collar employees of a national financial service organization. Temporal and historical variables affected the hazard rate of voluntary absence taking. Demographic variables that were significantly correlated with aggregated absences did not improve prediction of the hazard rate. Consequences of violating the modeling assumptions of independent observations and large samples were examined empirically. Results indicated that the model was robust to such violations. Implications of the findings and of the successful application of the model are discussed. Several recommendations are made for using the model in organizations and for future studies of absence taking and other low base-rate events in organizations. (PsycINFO Database Record (c) 2010 APA, all rights reserved) |
