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| Suppose we have two variables, X and Y we wish to correlate. To obtain the 95% Confidence Interval for their correlation firstly standardise the two variables by subtracting their mean and dividing by their standard deviation. This can also be done using CROSSTABS in the EXPLORE menu. | Weaver and Koopman (2014) use SPSS macros to implement a bootstrap approach [[https://sites.google.com/a/lakeheadu.ca/bweaver/Home/statistics/spss/my-spss-page/rhoci | here]] to obtain a 95% confidence interval for a Pearson correlation of two variables X and Y. |
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| Perform a linear regression using one of the standardised variables as the predictor of the other after selecting 95% confidence intervals for the regression estimate in the window obtained by clicking on the statistics button in the regression window. | The bootstrap method has advantages over other approaches (such as using 95% confidence intervals based upon regression coefficients of standardised variables) in giving asymmetric intervals which are contained within the range [-1,1]. |
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| There is also an | Howell (2002) |
How do I obtain 95% Confidence Intervals for a (Pearson) correlation in SPSS?
Weaver and Koopman (2014) use SPSS macros to implement a bootstrap approach here to obtain a 95% confidence interval for a Pearson correlation of two variables X and Y.
The bootstrap method has advantages over other approaches (such as using 95% confidence intervals based upon regression coefficients of standardised variables) in giving asymmetric intervals which are contained within the range [-1,1].
Howell (2002) on-line calculator.