For example: Cardiometabolic risk factors (Hypertension, Obesity, Dyslipidemia and fasting hyperglycemia) as outcomes
Well, it depends on what are you looking for. If ror example, you would like to examine these outcomes as risk factors for cardiac disease, then here the population of interest will be people with cardiac diseases. Thus you can estimate your sample size using population formula in case your population at risk are known, or you might use the probability formula to estimate the sample size.
Hi Godfrey Katamba ,
It's depend on the purposes or the models that you use, the sample size will be determined accordingly. The larger sample size for one outcome can be valid for other outcomes.
You might be referred to the rule of thumb for determining the sample size as N > 104 + m for testing individual predictors (where m is the number of IVs).
Wilson Van Voorhis, C.R., & Morgan, B.L. (2007, 2007/09/01). Understanding Power and Rules of Thumb for Determining Sample Sizes. Understanding Power and Rules of Thumb for Determining Sample Sizes, 3(2), 43-50. https://doi.org/10.20982/tqmp.03.2.p043
OR using the formula as mentioned in
Pourhoseingholi, M.A., Vahedi, M., & Rahimzadeh, M. (2013). Sample size calculation in medical studies. Gastroenterol. Hepatol. Bed Bench, 6(1), 14-17. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4017493/
Hope this could be helpful,
Duong,
It depends on your research question. For example: Do risk factors (Hypertension, Obesity, Dyslipidemia, fasting hyperglycemia) increase the incidence of heart attacks? If you want to compare those 4 risk factors, you need to have enough participants in all groups. So your sample size will be e.g. 4x 20 individuals.
Here you have the best program to determine sample size: https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower.html. You will find many tutorials on how to use it on youtube.
You can read: Methods of sample size calculation in descriptive retrospective burden of illness studies https://doi.org/10.1186/s12874-018-0657-9
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