Size matters: Standard errors in the application of null hypothesis significance testing in criminology and criminal justice

Shawn D. Bushway, Gary Sweeten, David B. Wilson

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


Null Hypothesis Significance Testing (NHST) has been a mainstay of the social sciences for empirically examining hypothesized relationships, and the main approach for establishing the importance of empirical results. NHST is the foundation of classical or frequentist statistics. The approach is designed to test the probability of generating the observed data if no relationship exists between the dependent and independent variables of interest, recognizing that the results will vary from sample to sample. This paper is intended to evaluate the state of the criminological and criminal justice literature with respect to the correct application of NHST. We apply a modified version of the instrument used in two reviews of the economics literature by McCloskey and Ziliak to code 82 articles in criminology and criminal justice. We have selected three sources of papers: Criminology, Justice Quarterly, and a recent review of experiments in criminal justice by Farrington and Welsh. We find that most researchers provide the basic information necessary to understand effect sizes and analytical significance in tables which include descriptive statistics and some standardized measure of size (e.g., betas, odds ratios). On the other hand, few of the articles mention statistical power and even fewer discuss the standards by which a finding would be considered large or small. Moreover, less than half of the articles distinguish between analytical significance and statistical significance, and most articles used the term 'significance' in ambiguous ways.

Original languageEnglish (US)
Pages (from-to)1-22
Number of pages22
JournalJournal of Experimental Criminology
Issue number1
StatePublished - Apr 2006
Externally publishedYes


  • Criminal justice
  • Criminology
  • Justice Quarterly
  • Regression
  • Review
  • Significance
  • Standard error
  • Testing

ASJC Scopus subject areas

  • Law


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