Because if you use t-values instead, you need to know the degrees of freedom, which means that you need to know the sample size. Thus, you need to know the sample size to calculate the sample size. However, there are methods, such as the one in the “pwr.t.test” function in R that can compute this. The estimated sample size from this function is a bit higher compared to the calculations shown in this video.
Is it valid to use the mean and standard deviation from a similar, but not exactly the same, study to estimate the sample size for a retrospective study? For example, the reference study was done in patients with diabetes, but the retrospective research will be done in patients who had a stroke.
your channel is a gift, really
Thanks, It really helps me to understand power and type 2 error. Wish you can keep producing new videos
If I want to estimate the sample size for a t test, why using Z values?
Because if you use t-values instead, you need to know the degrees of freedom, which means that you need to know the sample size. Thus, you need to know the sample size to calculate the sample size. However, there are methods, such as the one in the “pwr.t.test” function in R that can compute this. The estimated sample size from this function is a bit higher compared to the calculations shown in this video.
@tilestats thanks for the super fast reply!
Is it valid to use the mean and standard deviation from a similar, but not exactly the same, study to estimate the sample size for a retrospective study? For example, the reference study was done in patients with diabetes, but the retrospective research will be done in patients who had a stroke.
If you measure the same variable and assume that the two diseases cause similar effects on this variable, it seems resonable.