Partial Correlations
This feature requires the Statistics Base option.
The Partial Correlations procedure computes partial correlation coefficients that describe the linear relationship between two variables while controlling for the effects of one or more additional variables. Correlations are measures of linear association. Two variables can be perfectly related, but if the relationship is not linear, a correlation coefficient is not an appropriate statistic for measuring their association.
Example. Is there a relationship between healthcare funding and disease rates? Although you might expect any such relationship to be a negative one, a study reports a significant positive correlation: as healthcare funding increases, disease rates appear to increase. Controlling for the rate of visits to healthcare providers, however, virtually eliminates the observed positive correlation. Healthcare funding and disease rates only appear to be positively related because more people have access to healthcare when funding increases, which leads to more reported diseases by doctors and hospitals.
Statistics. For each variable: number of cases with nonmissing values, mean, and standard deviation. Partial and zero-order correlation matrices, with degrees of freedom and significance levels.
Partial Correlations Data Considerations
Data. Use symmetric, quantitative variables.
Assumptions. The Partial Correlations procedure assumes that each pair of variables is bivariate normal.
To Obtain Partial Correlations
This feature requires the Statistics Base option.
- From the menus choose:
- Select two or more numeric variables for which partial correlations are to be computed.
- Select one or more numeric control variables.
The following options are also available:
- Test of Significance. You can select two-tailed or one-tailed probabilities. If the direction of association is known in advance, select One-tailed. Otherwise, select Two-tailed.
- Display actual significance level. By default, the probability and degrees of freedom are shown for each correlation coefficient. If you deselect this item, coefficients significant at the 0.05 level are identified with a single asterisk, coefficients significant at the 0.01 level are identified with a double asterisk, and degrees of freedom are suppressed. This setting affects both partial and zero-order correlation matrices.
This procedure pastes PARTIAL CORR command syntax.