There are several cohort studies published in reputed journals without sample size calculation. Please share ideas on cohort studies then the budding researchers will get proper knowledge about this type of research design. If the required sample size is not there then how the statistical findings will be valid?
It is not always important to do a sample size calculation. However determining a sample size guides recruitment of participants and adds validity and power to the study
This is a common problem in many ecological studies for many reasons: 1) limited availability of endangered animals for experimentation, 2) limited budgets, 3) uncontrolled study conditions. However, this does not mean that subsequent inferences are worthless form uncontrolled sample sizes among cohorts. For example, here is a 'cohort' study on fish, yet are its inferences invalid because of uncontrolled sample sizes a priori?
Article Estimating and Predicting Collection Probability of Fish at ...
It is important to calculate [minimum] sample size for any study no matter the design & including Cohort studies. Even in total population studies, calculation of minimum sample size is desirable. There are laid down formulas for this exercise depending on the type of epidemiological design. If a sample size below the estimated minimum is used in any study, the researcher is faced with the problem of loss of internal validity for the study outcome. Smaller number of subjects than required for a study will make an otherwise statistically significant finding insignificant. Therefore minimum sample size is essential for all study types to serve as a guide for the number of study subjects required to produce a valid result. Hope this is understood.
Some cohort analyses are without calculating sample sizes likely to be because of retrospective nature. But if you are going to deal with prospective studies, then it is the question of precision. Without calculating sample size, you are unable (atleast) to know about effect size or margin of error due to which you can go away from precision.
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