Thanks for the great video! Could you say a bit more about how to actually use GPower for JointSignificance (respectively bootstrapping with power > .80), please? I cannot follow which tests to use in the programme when you talk about it in the video. Thank you!
In this case we have two regression models. The model for the a-path has one predictor (IV), the model for the b-path and the c'-path has two predictors (IV, MED). If you have covariates in your model you add their number to that. I would use: test-family: t-test statistical test: linear multiple regression, fixed model, single regression coefficient type of power-analysis: a-priori Then you can decide whether to do a one-tailed or a two tailed test. Effect size: Here you can choose a small effect for the path (f²=0.02), a medium sized effect (0.15) or a large effect (0.35) - or anything in between. You make this decision seperately for the a-path and the b-path. alpha error 0.05 Power: Here you put in the power for ONE path only, so that both powers multiplied lead to the power for the mediation you want (as I showed in the video) Number of predictors: 1 for the a-path (plus covariates, if you use any), 2 for the b-path. Then click on "calculate" (Technically the first regression for the a-path is not a multiple regresssion but a simple regression. But since simple regression is just a special case of multiple regression I assume that makes no difference.)
hi, thank you for this video! im using percentile bootstrap for my mediation analysis (PROCESS v.4), it means i can't use g power because it doesnt have a distributional assumption, am i correct? if i am, i need to base my gpower on fritz & mackinnon, right? what i'm asking is how do we choose the path effect size? is it up to the researcher or based on previous research/theoritical assumption? thank you ^^
I don't think that the paper by Fritz&MacKinnon is applicable here, because with your design you would have 4 IVs (4 dummy variables) for the 4+1 conditions and the paper is about one IV only.
@@RegorzStatistik thanks for the quick answer. do you have any insights on how I can approach this topic? There seems to be a lack of information on this.
@@gaara97531 The only thing that comes to my mind is programming a Monte Carlo simulation to calculate power (but I don't know any easy ressources how to do that).
I am not even sure whether they have mentioned which significance level they used (they have used alpha for the a-path). So I have always assumed that they had used p
hi, the number of the predictor refers to the arrow pointing to DV right? If my model include arrows for direct effect and mediation effect, I have to include all arrows or only direct effect arrows as number of predictors ?
Table 3 in the article by Fritz and MacKinnon. Deciding how large the a-path and the b-path should be. Then going to the results in the line "percentile bootstrap"
For more than one hypothesis I would run a power analysis for each hypothesis test and then take the largest resulting sample size. Thus you would make sure that the power is high enough for all your hypotheses.
For the first part (predicting the mediator) there is one predictor in the model, for the second part (predicting the DV) there are two predictors (as long as the IV is continous, of course).
What if I use 3 predictors( i’m using 3 traits of personality)? Is it wrong to do that with G power? Also, in My Thesis there’s 2 mediators and 1 criterion. Does it change anything?
Unfortunately not. The f2 of .15 is a medium sized effect (small would be .02, large .35). Getting the effect size for a power calculation is the biggest problem of this analysis. Maybe you can find possible effect sizes in the literature for the effects you are investigating. Otherwise you would have to decide how large (or better: how small) an effect you want to be able to find with your study. For my master's thesis I used the following argument: 1. For my research questions there are no prior results from which I can deduce an effect size. 2. A medium or large effect size seems unlikely because of ... (some chararcteristics of my study) 3. A small effect would not be that relevant in practice Therefore, I chose an effect halfway between small and medium.
Thank you for this video. It is very helpful. I am doing a study in which I am using PLS (using SmartPLS software) analysis. My research model has 3 independent variables, 2 mediating variables, and 1 dependent variable. Can I use G*power in this case to do power analysis? My sample size is 160. I need to show that power is not an issue with this sample size.
You can use Cohen (1992) table. See references below: 1. Hair, J., Hult, T., Ringle, C., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (Second Edi). SAGE. 2. Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS-SEM: The inverse square root and gamma-exponential methods. Information Systems Journal, 28(1), 227-261. doi.org/10.1111/isj.12131
Hi thank you for making this video! Would you please advise which method/software can be used to calculate sample size for a multiple mediation model? Thank you in advance :)
I guess that would be a case for Monte Carlo simulation (but I haven't calculate power for a multiple mediation yet). Maybe this article can help you there: Schoemann, A. M., Boulton, A. J., & Short, S. D. (2017). Determining power and sample size for simple and complex mediation models. Social Psychological and Personality Science, 8(4), 379-386.
Thank you very much for this video! Do you have any advice on doing a power analysis for a mediation analysis using the PROCESS model with three mediators? Unfortunately, I only found resources discussing analyses with one or two mediators but not three. Any help would be much appreciated!
Hi, thank you for this video. Do you know where to read about the sample size needed for a 0.80 power, for a moderated mediation with PROCESS model 14? In which there is 1 IV, 1DV, 1 mediation variable, and 1 moderator variable (dichotomous)? Thanks!
PROCESS use OLS regression similar to PLS-SEM. See references below: 1. Hair, J., Hult, T., Ringle, C., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (Second Edi). SAGE. 2. Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS-SEM: The inverse square root and gamma-exponential methods. Information Systems Journal, 28(1), 227-261. doi.org/10.1111/isj.12131
Thanks for the great video! Could you say a bit more about how to actually use GPower for JointSignificance (respectively bootstrapping with power > .80), please? I cannot follow which tests to use in the programme when you talk about it in the video. Thank you!
In this case we have two regression models. The model for the a-path has one predictor (IV), the model for the b-path and the c'-path has two predictors (IV, MED). If you have covariates in your model you add their number to that.
I would use:
test-family: t-test
statistical test: linear multiple regression, fixed model, single regression coefficient
type of power-analysis: a-priori
Then you can decide whether to do a one-tailed or a two tailed test.
Effect size: Here you can choose a small effect for the path (f²=0.02), a medium sized effect (0.15) or a large effect (0.35) - or anything in between. You make this decision seperately for the a-path and the b-path.
alpha error 0.05
Power: Here you put in the power for ONE path only, so that both powers multiplied lead to the power for the mediation you want (as I showed in the video)
Number of predictors: 1 for the a-path (plus covariates, if you use any), 2 for the b-path.
Then click on "calculate"
(Technically the first regression for the a-path is not a multiple regresssion but a simple regression. But since simple regression is just a special case of multiple regression I assume that makes no difference.)
Thanks a lot for this video, it was extremely helpful! Following from that, how would one calculate power for moderated mediation?
Unfortunately, I don't know any tool for an easy power calculation for a moderated mediation analysis.
Great video!
Thank you for the video! How would I go about testing a moderated mediation (Hayes PROCESS model 58 for example)? Thank you in advance!
Unfortunately, I haven't made a video about that yet.
Thank you for the informative video.Does this method works for survival outcome when i have categorical exposure and mediator?
Unfortunately I don't have any experience with survival data.
hi, thank you for this video! im using percentile bootstrap for my mediation analysis (PROCESS v.4), it means i can't use g power because it doesnt have a distributional assumption, am i correct? if i am, i need to base my gpower on fritz & mackinnon, right? what i'm asking is how do we choose the path effect size? is it up to the researcher or based on previous research/theoritical assumption? thank you ^^
Ideally, it is based on previous research.
@@RegorzStatistik okk i get it now. Thank youu
Does anything change in using the paper by Fritz if a plan do an experimental study with 4 Conditions (1 Control) and plan to do a mediation analysis?
I don't think that the paper by Fritz&MacKinnon is applicable here, because with your design you would have 4 IVs (4 dummy variables) for the 4+1 conditions and the paper is about one IV only.
@@RegorzStatistik thanks for the quick answer. do you have any insights on how I can approach this topic? There seems to be a lack of information on this.
@@gaara97531 The only thing that comes to my mind is programming a Monte Carlo simulation to calculate power (but I don't know any easy ressources how to do that).
Thank you for this very helpful video! You mentioned the power was .80 for the Fritz & MacKinnon table, was the significance level p
I am not even sure whether they have mentioned which significance level they used (they have used alpha for the a-path). So I have always assumed that they had used p
@@RegorzStatistik this was my question too. So, should we assume p < 0.05? thank you!
@@hannahmcgowan152 For my master's thesis I have assumed that they have based their calculations on p
@@RegorzStatistik Thank you for the info and taking the time to look through the article! I really appreciate it :)
hi, the number of the predictor refers to the arrow pointing to DV right? If my model include arrows for direct effect and mediation effect, I have to include all arrows or only direct effect arrows as number of predictors ?
All arrows poitning to the variable (from IV and MED)
@@RegorzStatistik Thank you so much, is there any article that I can review for?😄
I dont understand how to know the sample size I need with bootstrapping method
Table 3 in the article by Fritz and MacKinnon. Deciding how large the a-path and the b-path should be.
Then going to the results in the line "percentile bootstrap"
what if we have more than 1 models in our study? do we need to connect them all or calculate for each one and then sum all the predictors together?
For more than one hypothesis I would run a power analysis for each hypothesis test and then take the largest resulting sample size. Thus you would make sure that the power is high enough for all your hypotheses.
Hi. If I have 1 IV and 1 mediator how many predictors shall I indicate? In my study attachment styles is my IV and resilience is my mediator.
For the first part (predicting the mediator) there is one predictor in the model, for the second part (predicting the DV) there are two predictors (as long as the IV is continous, of course).
@@RegorzStatistik I see. In that case how many predictors shall I indicate to compute for my sample size?
@@katdino8935 I don't really understand the question given my previous answer.
What if I use 3 predictors( i’m using 3 traits of personality)? Is it wrong to do that with G power? Also, in My Thesis there’s 2 mediators and 1 criterion. Does it change anything?
That is a much more complex model and lies outside of the scope of this tutorial.
so helpful!!! Thank you!!
Hi, is the effect size for mediation analysis always 0.15? I haven’t conducted my study yet so don’t know what the effect size will be?
Unfortunately not. The f2 of .15 is a medium sized effect (small would be .02, large .35).
Getting the effect size for a power calculation is the biggest problem of this analysis. Maybe you can find possible effect sizes in the literature for the effects you are investigating. Otherwise you would have to decide how large (or better: how small) an effect you want to be able to find with your study.
For my master's thesis I used the following argument:
1. For my research questions there are no prior results from which I can deduce an effect size.
2. A medium or large effect size seems unlikely because of ... (some chararcteristics of my study)
3. A small effect would not be that relevant in practice
Therefore, I chose an effect halfway between small and medium.
@@RegorzStatistik thank you!
Thank you for this video. It is very helpful.
I am doing a study in which I am using PLS (using SmartPLS software) analysis. My research model has 3 independent variables, 2 mediating variables, and 1 dependent variable. Can I use G*power in this case to do power analysis? My sample size is 160. I need to show that power is not an issue with this sample size.
I don't know how the power is calculated if you use PLS.
@@RegorzStatistik thanks. Can you suggest some method to do it?
@@RathorPhD Unfortunately not, I don't know enough about PLS.
You can use Cohen (1992) table. See references below:
1. Hair, J., Hult, T., Ringle, C., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (Second Edi). SAGE.
2. Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS-SEM: The inverse square root and gamma-exponential methods. Information Systems Journal, 28(1), 227-261. doi.org/10.1111/isj.12131
Hi thank you for making this video! Would you please advise which method/software can be used to calculate sample size for a multiple mediation model? Thank you in advance :)
I guess that would be a case for Monte Carlo simulation (but I haven't calculate power for a multiple mediation yet). Maybe this article can help you there:
Schoemann, A. M., Boulton, A. J., & Short, S. D. (2017). Determining power and sample size for simple and complex mediation models. Social Psychological and Personality Science, 8(4), 379-386.
@@RegorzStatistik Thanks a lot for your help! I will check out the paper :)
Thank you very much for this video! Do you have any advice on doing a power analysis for a mediation analysis using the PROCESS model with three mediators? Unfortunately, I only found resources discussing analyses with one or two mediators but not three. Any help would be much appreciated!
Unfortunately not (other than running a Monte Carlo simulation).
@@RegorzStatistik Thank you for your quick response! I will look into that.
Hi, thank you for this video. Do you know where to read about the sample size needed for a 0.80 power, for a moderated mediation with PROCESS model 14? In which there is 1 IV, 1DV, 1 mediation variable, and 1 moderator variable (dichotomous)? Thanks!
Unfortunately, I don't know any tool for sample size calculations for moderated mediation.
PROCESS use OLS regression similar to PLS-SEM. See references below:
1. Hair, J., Hult, T., Ringle, C., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (Second Edi). SAGE.
2. Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS-SEM: The inverse square root and gamma-exponential methods. Information Systems Journal, 28(1), 227-261. doi.org/10.1111/isj.12131