The only time one might always consider using a transformation on a response is when it's a ratio. There are 2 reasons for this. Firstly, many methods will favour the part of the ratio that is above 1 since it is larger. And secondly ratios aren’t symmetric and are dependent on how we define it e.g. if we have 2 numbers 2 and 1 then it can be expressed as 2 ratios either 2/1 =2 or 1/2 = 0.5. So taken together this means we can get very different models depending on how we define the ratio.
One way around this is to take the log of the ratio. The result is now symmetric about 0 and we should get the same\similar model irrelevant to how we define the ratio. E.g. log(1/2) = 0.3 and log(2) = -0.3. (although the parameters might have reversed signs). Chris Howden B.Sc. (Hons) GStat. Founding Partner Data Analysis, Modelling and Training Evidence Based Strategy/Policy Development, IP Commercialisation and Innovation (mobile) +61 (0) 410 689 945 (skype) chris.howden ch...@trickysolutions.com.au Disclaimer: The information in this email and any attachments to it are confidential and may contain legally privileged information. If you are not the named or intended recipient, please delete this communication and contact us immediately. Please note you are not authorised to copy, use or disclose this communication or any attachments without our consent. Although this email has been checked by anti-virus software, there is a risk that email messages may be corrupted or infected by viruses or other interferences. No responsibility is accepted for such interference. Unless expressly stated, the views of the writer are not those of the company. Tricky Solutions always does our best to provide accurate forecasts and analyses based on the data supplied, however it is possible that some important predictors were not included in the data sent to us. Information provided by us should not be solely relied upon when making decisions and clients should use their own judgement. -----Original Message----- From: r-sig-ecology-boun...@r-project.org [mailto:r-sig-ecology-boun...@r-project.org] On Behalf Of Scott Foster Sent: Friday, 5 September 2014 9:04 AM To: r-sig-ecology@r-project.org Subject: Re: [R-sig-eco] Standardising and transformation of explanatory/independent/predictor variables for multiple regression analysis Hi again Sam, I think that you have it. Extreme values will have more influence, due to their placement in covariate space. This is often countered with transformation (of the covariates) but I tend to think that altering your data for the sake of the model is the wrong way around. Nevertheless, it can be effective. Especially when there is a reason (from the application) to do so. Using other methods may also help, without the need to transform. Note that this is not the same issue as transforming the outcomes (responses). There I would try my hardest not to transform at all -- transformation can do funny things to the statistical properties of the outcomes (and it is those statistical properties that are of direct interest). Good luck, Scott On 05/09/14 01:12, SamiC wrote: > Thanks Scott, > > That does help to clarify things. > > So if a covariate is highly skewed, extreme values will be more influential. > And this can be reduced through a transformation (which can be > justified) or through other techniques (e.g. bootstrapping). > > Cheers > > Sam > > > > -- > View this message in context: > http://r-sig-ecology.471788.n2.nabble.com/Standardising-and-transforma > tion-of-explanatory-independent-predictor-variables-for-multiple-regre > sss-tp7579048p7579052.html Sent from the r-sig-ecology mailing list > archive at Nabble.com. > > _______________________________________________ > R-sig-ecology mailing list > R-sig-ecology@r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-ecology > -- Scott Foster CSIRO E scott.fos...@csiro.au T +61 3 6232 5178 Postal address: CSIRO Marine Laboratories, GPO Box 1538, Hobart TAS 7001 Street Address: CSIRO, Castray Esplanade, Hobart Tas 7001, Australia www.csiro.au _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology