Statistical Power Determination
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Power : Simple or Multiple Linear Regression: Change in effect size
This utility can be used to calculate statistical power gined with sample size for Simple or Multiple Linear Regression to detect significant increase in effect size, when more predictors are added to the model.
Method used and other details
Sample Size in your study (N)
Required
Sample Size in your study (N).
Number of previous predictors. (K1)
Required
Number of previous predictors before adding additional predictors.
Number of additional predictors. (K2)
Required
Number of additional predictors to be added. Total number of predictors in your study are K1 + K2.
Change in effect size after adding K2 predictors in your study. You can choose any effect size from available options.
f squared
f
R squared
η squared
Required
Approximate expected change in effect size due to addition of new predictors, based on previus studies / pilot study. you can choose any of following four.
f squared (f
2
), f, R squared (R
2
), η squared (η
2
).
Confidence Level %
Enter positive number between 0.01 to 99.99
Required
In percentage. Commonly used values are 95, 99 and 90. Should be between 0.01 to 99.99.
Power ( 1 - β) =
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