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Sample Size Calculation Guide

The document summarizes a sample size calculation for a study comparing two groups. Based on a previous study with an effect size of 0.75, power of 80%, and alpha of 0.05, the required sample size for each group is 29 patients. Two software programs, G-Power and PASS, were used to calculate the sample size and both determined that a sample of 23 patients per group would achieve a power of 80.14% to detect an effect size of 0.75 between the groups with an alpha of 0.05 using a two-sided independent t-test.

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212 views2 pages

Sample Size Calculation Guide

The document summarizes a sample size calculation for a study comparing two groups. Based on a previous study with an effect size of 0.75, power of 80%, and alpha of 0.05, the required sample size for each group is 29 patients. Two software programs, G-Power and PASS, were used to calculate the sample size and both determined that a sample of 23 patients per group would achieve a power of 80.14% to detect an effect size of 0.75 between the groups with an alpha of 0.05 using a two-sided independent t-test.

Uploaded by

AmalAbdlFattah
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Sample Size Calculation:

According to previous studies, the effect size = 0.75, power = 0.80, and alpha level of
significance = 0.05, the sample size obtained for each group is about = 29 patients. The
calculation is done using G-power which produced figure () which represents the sample size vs.
the power levels.

Source: G-power software

Figure(): The power analysis

The calculation is repeated using the program PASS to obtain the sample size required.

Numeric Results for Two-Sample T-Test


Alternative Hypothesis: H1: d ≠ 0

Effect
Target Actual Size
Power Power N1 N2 N d Alpha
0.80 0.8014 23 23 46 0.75 0.050

References
Cohen, Jacob. 1988. Statistical Power Analysis for the Behavioral Sciences. Lawrence Erlbaum
Associates. Hillsdale, New Jersey
Julious, S. A. 2010. Sample Sizes for Clinical Trials. Chapman & Hall/CRC. Boca Raton, FL.
Machin, D., Campbell, M., Tan, B. T., Tan, S. H. 2009. Sample Size Tables for Clinical Studies,
3rd Edition. Wiley-Blackwell.
Ryan, Thomas P. 2013. Sample Size Determination and Power. John Wiley & Sons. New Jersey.
Report Definitions
Target Power is the desired power. May not be achieved because of integer N1 and N2.
Actual Power is the achieved power. Because N1 and N2 are integers, this value is often
(slightly) larger than the target power. N1 and N2 are the number of items sampled from each
population. N is the total sample size, N1 + N2.
Effect Size: d = (μ1 - μ2) / σ is the effect size. Cohen recommended Low = 0.2, Medium = 0.5,
and High = 0.8. Alpha is the probability of rejecting a true null hypothesis.

Summary Statements

Group sample sizes of 23 and 23 achieve 80.14% power to reject the null hypothesis of zero

effect size when the population effect size is 0.75 and the significance level (alpha) is 0.050

using a two-sided two-sample equal-variance t-test.

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