A Practical Introduction to Methods for Analyzing Longitudinal Data in the Presence of Missing Data Using a Marijuana Price Survey

Published in: Journal of Criminal Psychology, v. 5, no. 2, 2015, p.137-148

Posted on RAND.org on March 18, 2016

by Jeremy N. V. Miles, Priscillia Hunt

Read More

Access further information on this document at Journal of Criminal Psychology

This article was published outside of RAND. The full text of the article can be found at the link above.

PURPOSE: In applied psychology research settings, such as criminal psychology, missing data are to be expected. Missing data can cause problems with both biased estimates and lack of statistical power. The paper aims to discuss these issues. DESIGN/METHODOLOGY/APPROACH: Recently, sophisticated methods for appropriately dealing with missing data, so as to minimize bias and to maximize power have been developed. In this paper the authors use an artificial data set to demonstrate the problems that can arise with missing data, and make naïve attempts to handle data sets where some data are missing. FINDINGS: With the artificial data set, and a data set comprising of the results of a survey investigating prices paid for recreational and medical marijuana, the authors demonstrate the use of multiple imputation and maximum likelihood estimation for obtaining appropriate estimates and standard errors when data are missing. ORIGINALITY/VALUE: Missing data are ubiquitous in applied research. This paper demonstrates that techniques for handling missing data are accessible and should be employed by researchers.

This report is part of the RAND Corporation External publication series. Many RAND studies are published in peer-reviewed scholarly journals, as chapters in commercial books, or as documents published by other organizations.

Our mission to help improve policy and decisionmaking through research and analysis is enabled through our core values of quality and objectivity and our unwavering commitment to the highest level of integrity and ethical behavior. To help ensure our research and analysis are rigorous, objective, and nonpartisan, we subject our research publications to a robust and exacting quality-assurance process; avoid both the appearance and reality of financial and other conflicts of interest through staff training, project screening, and a policy of mandatory disclosure; and pursue transparency in our research engagements through our commitment to the open publication of our research findings and recommendations, disclosure of the source of funding of published research, and policies to ensure intellectual independence. For more information, visit www.rand.org/about/principles.

The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.