I am planning to study a hypothesis for understanding the pathophysiology in a particular disease. I am therefore wanting to know how many disease cases do I need to study for such research.
Power function is a good guideline to decide sample size in hypothesis testing. A purely statistical way to decide the sample size is by controlling sizes of the errors (type one error and type two error) via power function. However, non-statistical ways such as cost, time, man-power also affect when deciding the sample size.
Dear Wasim, in disease related research
1. You have find the prevalence of the particular disease in the same geographical area.
2. Decide and fix the power of the test
3. What are the type one error and type two error.
4. Use the appropriate formula for finding the sample size for the particular study.
If your study related to prevalence or prevalence is already found in the previous study means, then you can use the following formula.
4 p q
Sample Size = n = --------------
d^2
p = prevalence (in percentage)
q = 100 - p
d = admissible error (10% of prevalence)
The sample size is one of the most difficult tasks.
It depends on many factors - the hypothesis of a distribution, the level of reliability.
By small samples almost nothing can be said. You can say, but it would be groundless conclusions.
Tip this. Take as a model disease in another region.
Look what kind of histogram, coca interval in the histogram and what level of error. Focus on the data.
From the experience of the analysis of health information and statistics:
аppropriate distribution type beta-distribution with a sample of 200 patients and 95% reliability.
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