If I have two correlations: one between variable 1 and variable 2; second between variable 1 and variable 3. What's the best way to analyze the data so that I am able to make the assumption that the correlation between variable 1 and variable 2 is stronger than the one between variable 1 and variable 3. Can I make that assumption just based on the fact that one correlation coefficient is higher than the other, or do I have to make further tests? If so, what's the best way to do that in SPSS.
Thank you very much for helping me with this question.
You can apply test of difference between two correlations. It will help you out-https://psycnet.apa.org/record/1992-15158-001
To compare two correlations in SPSS, you can use Fisher's r-to-z transformation. Here are the steps:
You can also use the COMPARE CORRELATIONS command in SPSS to automate these steps. To use this command, you need to have the two correlation matrices you want to compare in the same SPSS data file. Then, go to Analyze > Correlate > Bivariate and select the variables for the first correlation matrix. Next, click on the COMPARE button and select the variables for the second correlation matrix. SPSS will output the difference between the two correlation coefficients and a significance test for this difference.
The best way is to learn R and get rid of SPSS. There are many ways to do this, and each way has advantages and disadvantages, and may depend on more or less assumptions about the underlying data generating process. Thereis an R package with quite a few methods built in. https://cran.r-project.org/web/packages/cocor/cocor.pdf There is no universal correct answer. You need experience and knowledge of the relevant mathematics.
I made a R script that compare two correlation coefficients by bootstrap method. You can declare the method of correlation, which you want
https://github.com/DanielPysz/Bootstrap_Correlation_Comparising.git
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