Longitudinal Modeling with Randomly and Systematically Missing Data: A Simulation of Ad Hoc, Maximum Likelihood, and Multiple Imputation Techniques

Newman, Daniel A

doi:10.1177/1094428103254673

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Longitudinal Modeling with Randomly and Systematically Missing Data: A Simulation of Ad Hoc, Maximum Likelihood, and Multiple Imputation Techniques

Author(s): Daniel A. Newman

Publication date Created: July 2003

Publication date (Print): July 2003

Journal: Organizational Research Methods

Publisher: SAGE Publications

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Title: Organizational Research Methods

Abbreviated Title: Organizational Research Methods

Publisher: SAGE Publications

ISSN (Print): 1094-4281

ISSN (Electronic): 1552-7425

Publication date Created: July 2003

Publication date (Print): July 2003

Volume: 6

Issue: 3

Pages: 328-362

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DOI: 10.1177/1094428103254673

SO-VID: 9588241f-b660-48d9-98e0-9dd0984643bb

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Longitudinal Modeling with Randomly and Systematically Missing Data: A Simulation of Ad Hoc, Maximum Likelihood, and Multiple Imputation Techniques

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