Sample size calculation: Single proportion
Command: | Sample size![]() |
Description
Calculates the required sample size for the comparison of a proportion with a given proportion. The sample size takes into account the required significance level and power of the test (see Sample size calculation: 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.
- Proportion (%): the hypothesized proportion (considered to be biologically significantly different from the null hypothesis value), expressed as a percentage.
- Null hypothesis value (%): the null hypothesis value (a proportion, expressed as a percentage).
Example
In the example you consider a proportion of at least 70 to be significantly different from the null hypothesis value 50%.
For α-level you select 0.05 and for β-level you select 0.20 (power is 80%).
After you click Calculate the program displays the required sample size, which is 47.
A table shows the required sample size for different Type I and Type II Error levels.
Literature
- Machin D, Campbell MJ, Tan SB, Tan SH (2009) Sample size tables for clinical studies. 3rd ed. Chichester: Wiley-Blackwell.
See also
Recommended book
Sample Size Tables for Clinical Studies
David Machin, Michael J. Campbell, Say-Beng Tan, Sze-Huey Tan
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Sample Sizes for Clinical, Laboratory and Epidemiology Studies includes the sample size software (SSS) and formulae and numerical tables needed to design valid clinical studies. The text covers clinical as well as laboratory and epidemiology studies and contains the information needed to ensure a study will form a valid contribution to medical research. The authors, noted experts in the field, explain step by step and explore the wide range of considerations necessary to assist investigational teams when deriving an appropriate sample size for their when planned study. The book contains sets of sample size tables with companion explanations and clear worked out examples based on real data. In addition, the text offers bibliography and references sections that are designed to be helpful with guidance on the principles discussed.