SPSS and SAS programs for comparing Pearson correlations and OLS regression coefficients

• Published in: Behavior research methods Vol. 45; no. 3; pp. 880 - 895
• Main Authors: Weaver, Bruce, Wuensch, Karl L.
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.09.2013; Springer Nature B.V
• Subjects: Behavioral Science and Psychology; Body Height; Body Weight; Cognitive Psychology; Confidence Intervals; Data Interpretation, Statistical; Economic models; Female; Humans; Least-Squares Analysis; Male; Models, Statistical; Multivariate analysis; Psychology; Pulmonary Disease, Chronic Obstructive - diagnosis; Regression Analysis; Research Design; Respiratory Function Tests; Software; Variables; Regression; Correlation; SPSS; SAS; Ordinary least squares
• ISSN: 1554-3528; 1554-351X; 1554-3528
• DOI: 10.3758/s13428-012-0289-7

Several procedures that use summary data to test hypotheses about Pearson correlations and ordinary least squares regression coefficients have been described in various books and articles. To our knowledge, however, no single resource describes all of the most common tests. Furthermore, many of these tests have not yet been implemented in popular statistical software packages such as SPSS and SAS. In this article, we describe all of the most common tests and provide SPSS and SAS programs to perform them. When they are applicable, our code also computes 100 × (1 − α)% confidence intervals corresponding to the tests. For testing hypotheses about independent regression coefficients, we demonstrate one method that uses summary data and another that uses raw data (i.e., Potthoff analysis). When the raw data are available, the latter method is preferred, because use of summary data entails some loss of precision due to rounding.