Hi Yilak, you can still proceed by making some reasonable estimates. One option in this situation is to rely on data from similar studies conducted in comparable settings or neighboring countries. This helps you approximate the key parameters you need, such as the expected difference between means (effect size) and the standard deviation.

You can then use the "two-sample t-test sample size" formula for comparing two means or an online tool like G*Power to make the calculation.

If there's still uncertainty, consider conducting a small pilot study to get preliminary data on variability. Additionally, it is advisable to adjust the final sample size to account for potential non-response. This can typically be achieved by inflating the sample size by 10-20%, depending on the expected rate of non-participation.

Also, it is important to recognize that differences in sociodemographic and contextual factors can affect the appropriateness of the parameter estimates. Therefore, such estimations should be approached with caution.

Hope this helps!

Search literature and find a study related to your research area conducted in similar context may be in other African countries. If not find parameters from a systematic review & meta analysis and justify why your sample size calculation based on those parameters.

First, use G*Power (it's user-friendly); insert your parameters (select "a priori" as you want to "predict" the sample size). You can consider the output as the sample size. However, if the results aren't acceptable, you can add extra samples step by step to achieve the desired power.

Hello dear doctor. As prof. doctors answered you will use G*power statistical package and determine effect size acc. to cohen or eta or etc.... I advice for you to study effect size.