how to test the homogeneity of slopes using spss version 25

The data are from the UCLA study of chronic obstructive pulmonary disease. We chose this data set for two reasons: (1) It contains variables suitable for demonstrating all of the methods we discuss, and (2) readers can easily download it in several formats (SAS, Stata, SPSS, Statistica, S-Plus, and ASCII) from the UCLA Academic Technology Services Web site ( ). To illustrate the various methods, we use the lung function data set from Afifi, Clark, and May’s ( 2003) book Computer-Aided Multivariate Analysis. ) Users can select the desired confidence level for CIs (when they are applicable) by setting the value of a variable called alpha (e.g., set alpha =. (The data files, code, and output are also available on the authors’ Web sites: and. In all cases, SPSS and SAS programs to carry out the computations are provided as part of the online supplementary material, along with the output they generate.

We describe the various methods in this order: methods concerning (1) single parameters (e.g., testing the significance of a correlation), (2) two independent parameters (e.g., the difference between two independent correlations), (3) k independent parameters, where k ≥ 2 (e.g., testing the equivalence of three correlations), and (4) two nonindependent parameters (e.g., the difference between two nonindependent correlations).

When they are applicable, our code also computes 100 × (1 − α)% confidence intervals (CIs) corresponding to the statistical tests. With that in mind, the twofold purpose of this article is to provide a single resource that briefly reviews the most common methods for testing hypotheses about Pearson correlations and OLS regression coefficients and to provide SPSS and SAS code that performs the calculations. It would be much more convenient if one could carry out all of these tests using one’s usual statistical software. Footnote 1 However, such programs can be relatively difficult to use (e.g., if they are old 16-bit DOS programs, they may not run on modern computers), or they may not provide all of the desired output (e.g., one program we found reports a z-test result, but not the corresponding p-value). In some cases, data analysts may find stand-alone programs that perform the desired tests. Furthermore, many of the methods described in those various resources have not yet been implemented in standard statistical software packages such as SPSS and SAS. However, we are not aware of any single resource that describes all of the most common procedures. Several textbooks and articles describe methods for testing hypotheses concerning Pearson correlations and coefficients from ordinary least squares (OLS) regression models (e.g., Howell, 2013 Kenny, 1987 Potthoff, 1966 Raghunathan, Rosenthal, & Rubin, 1996 Steiger, 1980).

How to test the homogeneity of slopes using spss version 25