Dear all First of all apologies for the off-topic question and for not respecting the other points. Second, thanks for your advice and opinion I will definitely consult a statistician.
Regards, Alessandra On Sun, May 10, 2020 at 4:57 PM Abby Spurdle <spurdl...@gmail.com> wrote: > Well, this is 100% off-topic... > And I wasn't planning to answer the OP's question. > > However, I disagree with your answer. > > > There is no requirement that the dependent variable in a "regression" > type > > estimation follows a gaussian distribution. > > False. > It's depends on what type of '"regression" type estimation' one uses, > among other things. > > > You need a model of the > > process and then use an estimation technique to estimate your model. If > > effects in your model are additive do not use a log transformation. If > > effects are multiplicative then use a log transformation. > > The main question is, does the model satisfy the *assumptions*. > > > The choice > > should be determined by the mechanics of the problem and not by the > > statistics. > > While a mechanistic understanding is definitely valuable... > If the criteria for a good model vs a bad model, was whether the model > was consistent with mechanistic theory/understanding, then nearly > every statistical model I've seen would be a bad model. > I would say, a good model is one that is useful... > > > If you do use a log transformation the trying to reverse the > > process using an exponential transformation will be biased. > > The extent of > > that bias depends on your problem and it would not be possible to > estimate > > the significance of the bias without a much greater knowledge of the > > process and data. > > Never heard of this before... > But I do note back-transformation is not trivial, and I'm not an > expert on back-transformations. > > > I would suggest that you consult a competent > > statistician. > > I agree on that part... > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.