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Abstract

This paper discusses the statistical principles, methods, and software programs used to calculate sample size. In addition, it reviews the practical challenges faced in calculating sample size. We show that because of such challenges, statistical calculations often do not provide us with a clear-cut number for the study sample size; rather they suggest a range of reasonable numbers. The paper also discusses several important nonstatistical considerations in determination of sample size, such as novelty of the study and availability of resources.

Keywords: Power, sample size, type I error, type II error

(ProQuest: ... denotes formulae omitted.)

Introduction

"How many is enough?" is a qu estion that epid em iologists and clinician s ask them selves when they plan on conducting a new study. Researchers want to enroll a large enough number of people such that statistical errors (type I and type II) are minimized yet the cost, labor, and time to do the study remain acceptable. Sample size calculations often remind us of complex formulas. While we provide some formulas in the text, the main aim of the article is not to offer a long list of such formulas. Rather, the main aim is to discuss the statistical principles behind sample size calculation, issues that may make such calculations not-so-straightforward, and nonstatistical considerations in sample size determination. Therefore, in this article, we discuss the following topics:

1. The need to calculate sample size;

2. Principles;

3. Some formulas;

4. Factors that need to be determined for sample size calculations;

5. Assumptions made for sample size calculations;

6. Nonstatistical considerations;

7. Methods used to calculate sample size; and

8. Software used to calculate sample size.

The final part of the paper, Summary and Conclusions, ties these sections together.

1- The need to calculate sample size

When we would like to learn about an attribute of a population, such as mean cholesterol of the people of China, it may not be feasible for us to study the entire population due to cost or time issues. Besides cost and time issues, it may not be ethical to study the entire population if accurate enough results could be obtained by studying a subgroup of all people. For these reasons, we need to study a sample of...

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