[hidden email] wrote:

> Hi,

>

> This problem may be very easy, but I can't think of how to do it. I have constructed histograms of various variables in my dataset. Some of them are negatively skewed, and hence need data transformations applied. I know that you first need to reflect the negatively skewed data and then apply another transformation such as log, square root etc to bring it towards normailty. How is it that I reflect data in R? I'm sorry if this seems a very simple task, I think it involves going back to Maths GCSE and relearning reflection, rotation, translation etc! I have searched the internet, but cannot come up with anything useful on how to reflect data.

>

>> hist(Lsoc) #how do I reflect Lsoc in R?

>

> I am grateful for any help regarding this matter, it is just a very small part of my analysis and doesn't seem worth agonising hours over. I will probably kick myself when someone tells me the answer!

>

> Thank you very much,

>

> Zoe

To add further complication, if the transformation to normality is

empirically based, the true variance of resulting estimates will inherit

the variance from the empirical assessment. For example, if you use a

histogram or empirical CDF to find the transformation, the imprecision

of the empirical CDF will add a good deal of true variance to the final

estimates so that they are no more precise than sample quantiles on the

original scale. To put it another way, the sample median seems to be

inefficient (efficiency 2/pi) compared to the sample mean if normality

holds, but that relative efficiency rises if normality were "rigged".

--

Frank E Harrell Jr Professor and Chair School of Medicine

Department of Biostatistics Vanderbilt University

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https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide

http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.

Frank Harrell

Department of Biostatistics, Vanderbilt University