G-POWER analysis
Rakhi1234
Jukanti_U3.docx
Step A: Determine and Understand Statistical Power
[8] -- Tuesday, October 27, 2020 -- 19:52:41
t tests - Means: Wilcoxon-Mann-Whitney test (two groups)
Options: A.R.E. method
Analysis: A priori: Compute required sample size
Input: Tail(s) = One
Parent distribution = Normal
Effect size d = 0.5
α err prob = 0.05
Power (1-β err prob) = 0.8
Allocation ratio N2/N1 = 1
Output: Noncentrality parameter δ = 2.5152354
Critical t = 1.6603560
Df = 99.2225438
Sample size group 1 = 53
Sample size group 2 = 53
Total sample size = 106
Actual power = 0.8032180
[10] -- Tuesday, October 27, 2020 -- 19:54:07
t tests - Means: Wilcoxon-Mann-Whitney test (two groups)
Options: A.R.E. method
Analysis: A priori: Compute required sample size
Input: Tail(s) = One
Parent distribution = Normal
Effect size d = 0.5
α err prob = 0.05
Power (1-β err prob) = 0.9
Allocation ratio N2/N1 = 1
Output: Noncentrality parameter δ = 2.9519033
Critical t = 1.6560176
Df = 137.4197
Sample size group 1 = 73
Sample size group 2 = 73
Total sample size = 146
Actual power = 0.9019025
[7] -- Tuesday, October 27, 2020 -- 19:49:09
t tests - Means: Wilcoxon-Mann-Whitney test (two groups)
Options: A.R.E. method
Analysis: A priori: Compute required sample size
Input: Tail(s) = One
Parent distribution = Normal
Effect size d = 0.5
α err prob = 0.05
Power (1-β err prob) = 0.95
Allocation ratio N2/N1 = 1
Output: Noncentrality parameter δ = 3.3138635
Critical t = 1.6536729
Df = 173.7071
Sample size group 1 = 92
Sample size group 2 = 92
Total sample size = 184
Actual power = 0.9511454
How the sample size changed as the desired statistical power was increased. Describe the changes and how this influences the choice of a statistical power level for an apriori sample size determination.
Step B: Determine and Understand Statistical Significance
[12] -- Tuesday, October 27, 2020 -- 20:08:43
t tests - Means: Wilcoxon-Mann-Whitney test (two groups)
Options: A.R.E. method
Analysis: A priori: Compute required sample size
Input: Tail(s) = One
Parent distribution = Normal
Effect size d = 0.5
α err prob = 0.05
Power (1-β err prob) = 0.8
Allocation ratio N2/N1 = 1
Output: Noncentrality parameter δ = 2.5152354
Critical t = 1.6603560
Df = 99.2225438
Sample size group 1 = 53
Sample size group 2 = 53
Total sample size = 106
Actual power = 0.8032180
[13] -- Tuesday, October 27, 2020 -- 20:09:41
t tests - Means: Wilcoxon-Mann-Whitney test (two groups)
Options: A.R.E. method
Analysis: A priori: Compute required sample size
Input: Tail(s) = One
Parent distribution = Normal
Effect size d = 0.5
α err prob = 0.01
Power (1-β err prob) = 0.8
Allocation ratio N2/N1 = 1
Output: Noncentrality parameter δ = 3.2039809
Critical t = 2.3495505
Df = 162.2479
Sample size group 1 = 86
Sample size group 2 = 86
Total sample size = 172
Actual power = 0.8025758
[14] -- Tuesday, October 27, 2020 -- 20:10:29
t tests - Means: Wilcoxon-Mann-Whitney test (two groups)
Options: A.R.E. method
Analysis: A priori: Compute required sample size
Input: Tail(s) = One
Parent distribution = Normal
Effect size d = 0.5
α err prob = 0.001
Power (1-β err prob) = 0.8
Allocation ratio N2/N1 = 1
Output: Noncentrality parameter δ = 3.9844329
Critical t = 3.1228850
Df = 252.0113
Sample size group 1 = 133
Sample size group 2 = 133
Total sample size = 266
Actual power = 0.8041150
How the sample size changed as the statistical significance (Apha) was increased. Describe the changes and how this influences the choice of a statistical significance level for an apriori sample size determination.
Step C: Determine and Understand Effect Size
[15] -- Tuesday, October 27, 2020 -- 20:17:24
t tests - Means: Wilcoxon-Mann-Whitney test (two groups)
Options: A.R.E. method
Analysis: A priori: Compute required sample size
Input: Tail(s) = One
Parent distribution = Normal
Effect size d = 0.2
α err prob = 0.05
Power (1-β err prob) = 0.8
Allocation ratio N2/N1 = 1
Output: Noncentrality parameter δ = 2.4913937
Critical t = 1.6473202
Df = 618.7043
Sample size group 1 = 325
Sample size group 2 = 325
Total sample size = 650
Actual power = 0.8006136
[16] -- Tuesday, October 27, 2020 -- 20:18:03
t tests - Means: Wilcoxon-Mann-Whitney test (two groups)
Options: A.R.E. method
Analysis: A priori: Compute required sample size
Input: Tail(s) = One
Parent distribution = Normal
Effect size d = 0.5
α err prob = 0.05
Power (1-β err prob) = 0.8
Allocation ratio N2/N1 = 1
Output: Noncentrality parameter δ = 2.5152354
Critical t = 1.6603560
Df = 99.2225438
Sample size group 1 = 53
Sample size group 2 = 53
Total sample size = 106
Actual power = 0.8032180
[17] -- Tuesday, October 27, 2020 -- 20:18:52
t tests - Means: Wilcoxon-Mann-Whitney test (two groups)
Options: A.R.E. method
Analysis: A priori: Compute required sample size
Input: Tail(s) = One
Parent distribution = Normal
Effect size d = 0.8
α err prob = 0.05
Power (1-β err prob) = 0.8
Allocation ratio N2/N1 = 1
Output: Noncentrality parameter δ = 2.5332049
Critical t = 1.6858361
Df = 38.1070457
Sample size group 1 = 21
Sample size group 2 = 21
Total sample size = 42
Actual power = 0.8003744
How the sample size changed as the effect level was increased. Describe the changes and how this influences the choice of an effect size for an apriori sample size determination.
Conclusion
References
