Sample Output 2 – Mediation with Additional Options (It is not important which number you choose.) Still you will not get the same results as when running the same model with the same data with PROCESS in SPSS because the random numbers generators of SPSS and R are different.Ĩ.
#Hayes process 3 covariate generator
If you want to get the same results each time you can give the random number generator a start value by setting the seed parameter to any integer number. As a result, if you repeatedly run an analysis with bootstrapping you will get slightly different results (SE, p-values, confidence intervals) each time you run the analysis. Based on a random numbers generator many random samples are drawn from your sample with replacement.
Otherwise you would have to test the normality assumption before reporting the test results for the a-path, b-path and c'-path.īootstrapping - Start Value for the Random Numbers Generatorīootstrapping has a random component. If you want to get robust confidence intervals for the rest of the estimates you can do that by setting the modelbt parameter to 1. You can change this by setting the boot parameter to the number of samples you would like to have.īootstrapping Not Only for Indirect Effectsīy default, PROCESS uses bootstrapping for the indirect effects. With more covariates you have to bind them together with c(.).īy default, for models with bootstrapping the number of bootstrap samples is 5,000. If you have only one covariate you can simply put it into the formula. If you want to add covariates to your model you can use cov =. You can get standardized effects for all the regression paths by setting the stand parameter to 1. In small to medium samples it can lead to misleading results and in large samples there are still reasons to prefer the bootstrapping results.) (In general I do not recommend using the Sobel test. You can run a Sobel-test by setting the normal parameter to 1. If you run a mediation model you can test the total effect (= c-path) by setting the total parameter to 1. If you run a mediation model you can calculate effect sizes (partially standardized = ps, and completely standardized indirect effects = cs) by setting the effsize parameter to 1. Following are some additional PROCESS parameters that could be helpful for your mediation model.
#Hayes process 3 covariate code
Even though the limited code above gives you the mediation test in many cases you want to have additional information.
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