A biosocial analysis of the sources of missing data in criminological research

Joseph A. Schwartz and Kevin M. Beaver

Journal of Criminal Justice, 2014, vol. 42, issue 6, 452-461

Abstract: Failing to deal with missing data patterns effectively may result in biased parameter estimates and ultimately may produce inaccurate results and conclusions. The vast majority of criminological research has addressed this issue with listwise deletion (LD) and multiple imputation (MI) techniques. Identifying the specific covariates that directly contribute to patterns of missingness is highly important in deciding which technique to use. One of the more surprising omissions from the identified list of covariates is the potential role of genetic influences in the development of missingness.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jcjust:v:42:y:2014:i:6:p:452-461

DOI: 10.1016/j.jcrimjus.2014.07.002

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