Sample Size Determination
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Simple or Multiple Linear Regression: Change in effect size
This utility can be used to calculate required 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
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.
Your guesstimate of 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)
Enter positive number between 0.01 and 99.99
Required
In Percentage. Should be between 0.001 to 99.999. Common values are 80 % and 90 %
Sample Size Required =
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