Hello there,

first post in this forum. I hope this is the correct subforum, as I have a question regarding psychology statistics, but I am using a regression analysis.

I tested a mediation hypothesis with SPSS using linear regression. I did not find this hypothesized mediation, but I still have problems interpreting the results.

Variable A (Predictor 1) predicts C (dependent variable) significantly, as does variable B (hypothesized mediator/Predictor 2). The thing is that A does not predict B significantly, so there is no mediation, but I have two main effects.

My problem is that if I use a model with both predictors, both effects diminish (as seen in either the p-value or the B). It seems like there is an overlap between both predictors. I also did a correlation analysis to check for that, and Pearson is not significant (p = 0.065), but Spearman and Kendall are significant.

What do I do now? How do I describe the result? I am not sure, if B is a confounder in this case and if I can somehow correct for the overlapping effect.

Thanks in advance!

Edit: Btw, we were told that we could use the Baron & Kenny procedure and do not need to use newer methods, although they might be better

first post in this forum. I hope this is the correct subforum, as I have a question regarding psychology statistics, but I am using a regression analysis.

I tested a mediation hypothesis with SPSS using linear regression. I did not find this hypothesized mediation, but I still have problems interpreting the results.

Variable A (Predictor 1) predicts C (dependent variable) significantly, as does variable B (hypothesized mediator/Predictor 2). The thing is that A does not predict B significantly, so there is no mediation, but I have two main effects.

My problem is that if I use a model with both predictors, both effects diminish (as seen in either the p-value or the B). It seems like there is an overlap between both predictors. I also did a correlation analysis to check for that, and Pearson is not significant (p = 0.065), but Spearman and Kendall are significant.

What do I do now? How do I describe the result? I am not sure, if B is a confounder in this case and if I can somehow correct for the overlapping effect.

Thanks in advance!

Edit: Btw, we were told that we could use the Baron & Kenny procedure and do not need to use newer methods, although they might be better

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