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I used SPSS HAYES macro to test for indirect effect, and got the results as below.

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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?

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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.

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