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| 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. | Weaver and Koopman (2014) use SPSS macros available from [[https://sites.google.com/a/lakeheadu.ca/bweaver/Home/statistics/spss/my-spss-page/rhoci | here]] to obtain confidence intervals for each element of a matrix of Pearson correlations showing associations between variables. |
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| 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]. | This method is also suggested by Howell (2002) and has advantages over using 95% confidence intervals based upon regression coefficients of standardised variables in giving asymmetric intervals which are contained within the range [-1,1] and is, therefore, to be preferred. |
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| Howell (2002) [[http://faculty.vassar.edu/lowry/rho.html|on-line calculator.]] |
A 95% confidence interval using the backtransformed Fisher transformation for a ''single'' Pearson correlation may also be computed using this [[http://vassarstats.net/rho.html|on-line calculator.]] __References__ Bonett DG (2019) Point-biserial correlation: Interval estimation,hypothesis testing, meta-analysis, and sample size determination. To appear ''British Journal of Mathematical and Statistical Psychology''. Confidence intervals for different types of bi-serial correlations used as alternative two group effect sizes to Cohen's d. Howell DC (2002) Statistical Methods for Psychologists. Fifth Edition. Wadsworth:Pacific Grove, CA. Weaver B and Koopman R (2014) An SPSS Macro to Compute Confidence Intervals for Pearson’s Correlation. To appear in ''The Quantitative Methods for Psychology'' in Spring 2014. |
How do I obtain 95% Confidence Intervals for a (Pearson) correlation in SPSS?
Weaver and Koopman (2014) use SPSS macros available from here to obtain confidence intervals for each element of a matrix of Pearson correlations showing associations between variables.
This method is also suggested by Howell (2002) and has advantages over using 95% confidence intervals based upon regression coefficients of standardised variables in giving asymmetric intervals which are contained within the range [-1,1] and is, therefore, to be preferred.
A 95% confidence interval using the backtransformed Fisher transformation for a single Pearson correlation may also be computed using this on-line calculator.
References
Bonett DG (2019) Point-biserial correlation: Interval estimation,hypothesis testing, meta-analysis, and sample size determination. To appear British Journal of Mathematical and Statistical Psychology. Confidence intervals for different types of bi-serial correlations used as alternative two group effect sizes to Cohen's d.
Howell DC (2002) Statistical Methods for Psychologists. Fifth Edition. Wadsworth:Pacific Grove, CA.
Weaver B and Koopman R (2014) An SPSS Macro to Compute Confidence Intervals for Pearson’s Correlation. To appear in The Quantitative Methods for Psychology in Spring 2014.