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I have one sample with values of sugar intake pre and post intervention. I transformed the values for t test as the change from pre to post was negatively skewed but now I dont know how to report the results from t test? Can I just square back the mean and CI?

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marked as duplicate by Michael Chernick, kjetil b halvorsen, gung Aug 16 '18 at 18:54

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    $\begingroup$ If a t test on the original (untransformed) data is still significant, I'd suggest reporting everything in terms of the original data. (Perhaps mention skewness in a one-sentence footnote, quoting the P-value from the t test on transformed differences.) // Advocates of transforming data seldom discuss how to report results in a way that is meaningful for a nonstatistical audience. $\endgroup$ – BruceET Aug 14 '18 at 23:30
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    $\begingroup$ This may be a bit of an X-Y problem. Given that the means of the square roots differ, this doesn't automatically guarantee that the means of the original variables do. You may be better using a test more directly related to your actual hypothesis (and a suitable model for the data on that scale). What is your actual question of interest (i.e. why are you doing a test in the first place -- what are you specifically trying to find out?) $\endgroup$ – Glen_b Aug 15 '18 at 2:16
  • $\begingroup$ Thank you so much for answering! I am trying to see if the participants decreased sugar intake after 2 years from the baseline. When I do the t-test with non-transformed values the mean is bigger than the baseline value so I have 350 (median baseline), 88 (median 2 years) but then t-test gives the mean -380 (CI). When i use sqrt of baseline and 2 yrs i get 15.9 mean in t-test so not sure how to report this $\endgroup$ – Masa Aug 15 '18 at 8:40
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    $\begingroup$ p.s. yes tests are significant, both transformed and non-transformed @BruceET $\endgroup$ – Masa Aug 15 '18 at 8:41
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    $\begingroup$ Good. Then I guess I'd use the test that is easy to report and include a footnote to indicate you are paying attention to assumptions. (I'd want to see the data to be absolutely sure, but in practice t tests get used in many cases where assumptions aren't met exactly.) $\endgroup$ – BruceET Aug 15 '18 at 9:20