Biostats Calculator

Features > Sample size calculator

Studies that aim to establish a result with a hypothesis test can fail in two ways:

• False positive (type I error) - they claim a relationship where none is present
• False negative (type II error) - they fail to claim a relationship where there is one present

The permitted false positive rate (α) determines the confidence level, and is chosen as part of the hypothesis test.

The false negative rate (β) determines the power of the study. Larger studies are more powerful and will produce false negatives less often.

The sample size calculator uses power analysis techniques to determine the study size required to achieve a chosen level of statistical power.

After selecting Sample size from the menu, describe the variable being measured. Biostats Calculator can perform power analysis for:

• Categorical data - the difference in proportions of a certain condition between two groups. Estimates of the proportion in each group are required.
• Numeric data - a difference in mean values of a measurement between two groups. You should provide estimates of the mean and standard deviation in each group.

You can also choose to alter the permitted type I and type II error rates.

The two comparison groups can be of different sizes (e.g. if few cases are available, but many controls). Adjust the Relative group size slider to set the correct ratio.

Biostats Calculator reports:

• The sample size required for the study
• The size of each comparison group

Biostats Calculator can perform this test and 11 others from the convenience of your iPhone or iPod Touch. Buy it today!