X-squared = 19.261, df = 5, p-value = 0.001718īut this does not say that scores are higher in the treatment group, only that the distributions differ-as one can readily That scores 0-5 are independent of group, with P-value 0.002. Is for the control group and the second for the treatment group,Ī chi-squared test would have rejected the null hypothesis It looks as if the counts from your previous experiment may haveīeen something like those in the table below, where the first row It would be the wilcoxon rank sum test then? I was actually going try to compare the means, but since the outcome distributions are not normally distributed I guess one has to use non parametric test. Okay, good to know! But how does one come up with the answer? Do I have to look for papers, where no significant difference was found? In many previous papers, the means were just compared. The outcomes represent the payouts that come with the reports done by the participants. I habe never done a power analysis before, so can anyone help? How do I process further in order to get a sample size, whit power of 80%, alpha. Is it common to use the effect size from previous studies or should one even lower the effect size for sample size calculation? Since the sample distribution is not normally distributed, does it still make sense to calculate the standard deviation? I have to calculate the sample size for an experimental study and took some sample distributions data from a previous similar research and calculated the means and standard variations for before and after the treatment (see picture).
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