I used SPSS HAYES macro to test for indirect effect, and got the results as below.
I used bootstrap method to derive confidence intervals, and it seems the indirect effect is significant at p<.05
However, SPSS macro does not produce the exact p-value for the indirect effect it has calculated via bootstrap method. Can I just manually calculate the p-value by looking up the t-distribution table using the standardized effect and bootstrapped standard error?
If possible, what df value should I use for the t statistic? should I use the df value for the entire model with the mediator included, or the total effect model which does not include the mediator?
Best Answer
You should not attempt to compute a p-value. Simply report the confidence interval. Doing so contains the same relevant information as a p-value (do you have enough evidence to reject the null of no effect?). If the 95% confidence interval excludes 0, the corresponding p-value will necessarily be less than .05. Although people do conduct Wald t-tests by dividing the estimate by the bootstrap standard error to arrive at a t-statistic, if the sampling distribution of the statistic is not symmetric (and it is usually not symmetric in testing indirect effects), using this t-statistic in a t-test is invalid. The confidence interval, which may not be symmetric, is a more valid way to test the null hypothesis with bootstrapping.