Sample size calculation: Single mean

Command

Sampling Single mean

Description

Calculates the required sample size for the comparison of a sample mean with a given value. The sample size takes into account the required significance level and power of the test (see Sampling: Introduction).

Required input

• Type I error - alpha: the probability of making a Type I error (α-level, two-sided), i.e. the probability of rejecting the null hypothesis when in fact it is true.
• Type II error - beta: the probability of making a Type II error (β-level), i.e. the probability of accepting the null hypothesis when in fact it is false.
• Mean: the hypothesized mean (considered to be biologically significant different from the null hypothesis value).
• Standard deviation: hypothesized standard deviation (known from previous studies or from the literature).
• Null hypothesis value: the null hypothesis value.

Example

In the example you consider a value of at least 60 to be significant different from the null hypothesis value 50. From a previous study, you expect the standard deviation of the sample to be 14.

For α-level you select 0.05 and for β-level you select 0.20 (power is 80%).

After you click the Calculate button the program displays the required sample size, which is 18 in the example.

A table shows the required sample size for different Type I and Type II Error levels.

Comparison of two paired samples

To calculate the sample size required for the comparison of two paired samples, you use the same procedure as for a Single mean.

In the dialog box, for Mean, you enter the hypothesized mean difference; for Standard deviation, enter the hypothesized standard deviation of the differences, and for Null hypothesis value enter the value 0.

Literature

• Machin D, Campbell MJ, Tan SB, Tan SH (2009) Sample size tables for clinical studies. 3rd ed. Chichester: Wiley-Blackwell.

See also

• Sampling menu
• Sampling: Introduction
• Sampling: Single proportion
• Sampling: Comparison of two means
• Sampling: Comparison of two proportions
• Sampling: Correlation coefficient
• Sampling: Area under ROC curve
• Sampling: Comparison of two ROC curves
• Sampling: Survival analysis (logrank test)