Thanks for the link.Hosam wrote: ↑Thu Nov 26, 2015 7:48 pm However, if you want to use Gpower you could get sample size of 138 respondent as the following (please correct me if I'm mistaken)
F tests - Linear multiple regression: Fixed model, R² increase
Analysis: A priori: Compute required sample size
Input: Effect size f² = 0.15
α err prob = 0.05
Power (1-β err prob) = 0.95
Number of tested predictors = 5
Total number of predictors = 5
Output: Noncentrality parameter λ = 20.7000000
Critical F = 2.2828562
Numerator df = 5
Denominator df = 132
Total sample size = 138
Actual power = 0.9507643
Sample size calculation using G*power Analysis
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Re: Sample size calculation using G*power Analysis
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Re: Sample size calculation using G*power Analysis
can anyone show me a tutorial on how to use the program? i a currently doing my thesis, with 2 independent variable, 1 mediator and 1 dependent
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Re: Sample size calculation using G*power Analysis
thanks for the help guys
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Re: Sample size calculation using G*power Analysis
Hello all,
I have a reflective-formative type model and there are two first order latent variables. I am interested in testing the weights of the two first order latent variables to second order latent variable. I will use the disjointed two stage approach to model analysis. Should I calculate the sample size in the second stage by using n=2 for the number of predictors and the t-test method? Or should I calculate the sample size in the first stage by using n=20 for the number of predictors and the t-test method? (one of the first order latent variables have 20 indicators and another have 9 indicators.)
Thank you.
I have a reflective-formative type model and there are two first order latent variables. I am interested in testing the weights of the two first order latent variables to second order latent variable. I will use the disjointed two stage approach to model analysis. Should I calculate the sample size in the second stage by using n=2 for the number of predictors and the t-test method? Or should I calculate the sample size in the first stage by using n=20 for the number of predictors and the t-test method? (one of the first order latent variables have 20 indicators and another have 9 indicators.)
Thank you.
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Re: Sample size calculation using G*power Analysis
Hi everyone,
In continuation to the discussion here, I had a query.
When calculating minimum sample size in GPower for a study that has one tailed hypotheses, I have used the following settings (based on 2nd order, 2 latent variables predicting another 2nd order latent variable, all reflective):
t-test
Linear multiple regression: Fixed model , single regression coefficient
A priori analysis
One tailed
Effect size 0.05
Alpha error prob. 0.05
Power 0.80
No. of predictors = 2
This gives me a minimum sample size of 126
As part of my analysis, I have done a group specific analysis (2 groups with greater than 126 sample size) as well as analysis of the total dataset (greater than 300 sample size).
Am I correct to assume that I have followed the correct settings for GPower and I can say that the sample size of the study is sufficient based on the above GPower A priori analysis?
In continuation to the discussion here, I had a query.
When calculating minimum sample size in GPower for a study that has one tailed hypotheses, I have used the following settings (based on 2nd order, 2 latent variables predicting another 2nd order latent variable, all reflective):
t-test
Linear multiple regression: Fixed model , single regression coefficient
A priori analysis
One tailed
Effect size 0.05
Alpha error prob. 0.05
Power 0.80
No. of predictors = 2
This gives me a minimum sample size of 126
As part of my analysis, I have done a group specific analysis (2 groups with greater than 126 sample size) as well as analysis of the total dataset (greater than 300 sample size).
Am I correct to assume that I have followed the correct settings for GPower and I can say that the sample size of the study is sufficient based on the above GPower A priori analysis?
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Re: Sample size calculation using G*power Analysis
Your sample size is sufficient to detect effects with an effect size of 0.05 with 5% error probability and 80% power in each group. However, that does not mean that you are able to detect differences between the groups. That would be another different power analysis.
Dr. Jan-Michael Becker, BI Norwegian Business School, SmartPLS Developer
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de
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Re: Sample size calculation using G*power Analysis
Yes, I have understood your point. As I mentioned, I have done separate analysis for each group as well as an overall analysis, I have not done any comparison of the two groups.
Thank you Dr. Becker and wish you a very happy new year :)
Thank you Dr. Becker and wish you a very happy new year :)
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Re: Sample size calculation using G*power Analysis
There is another method to calculate power
Aguirre-Urreta, M., & Rönkkö, M. (2015). Sample size determination and statistical power analysis in PLS using R: an annotated tutorial. Communications of the Association for Information Systems, 36(1), 3.
Has anyone tried this?
Aguirre-Urreta, M., & Rönkkö, M. (2015). Sample size determination and statistical power analysis in PLS using R: an annotated tutorial. Communications of the Association for Information Systems, 36(1), 3.
Has anyone tried this?
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Re: Sample size calculation using G*power Analysis
I also want to use gpower analysis in order calculate the sample size. Could you pls enlighten me on how to tackle this ?