Is it possible to estimate the size of the required sample without using statistical formulae?
Yes, if a general rule of thumb is employed.
The rule of thumb: Add 20 subjects for each additional variable.
Illustration:
A study has the following variables in the questionnaire/ Data collection Form:
Age; Sex; Heart Rate; BMI; Socio-Economic Status (SES)
What would the minimum sample size requirement be for this study?
Employing the rule of thumb, we obtain the minimum sample size required as:
Total number of variables: 5.
Therefore, minimum sample size required is
5 x 20 = 100 subjects
Why take 20 subjects per additional variable? Why not 10 or 15?
I’m guessing it has to do with the Chi-square test.
The Chi-square test employs a 2×2 contingency table. Thus, there are 4 cells. One of the guidelines states that the number of observations/ value of any cell should not be less than 5. This means that we should have at least 5 in each cell. Multiplying, we get the minimum number of total observations as 5 x 4 = 20.
Sample size obtained by the rule of thumb will be adequate for any situation involving the Chi-square test during analysis. In addition, it is unlikely that one would under-estimate the required sample size using this approach.
Bottomline: Adding 20 subjects for each additional variable will yield a reasonable estimate of the required sample size.
Great idea. But the justification for 20 is oversimplified because, with the number 20, the chance of any cell in 2×2 table being less than 5 is more than 90%.
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Dear Someone,
Thanks for the feedback. I was guessing the justification for 20, but it seems my guess was off-track. Would you please elaborate on the justification for everyone’s benefit?
Thanks in advance.
Best,
Roopesh
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