# Transformation for negative skewness data

My analysis involved some behavioral data on swine. One measure we had was standing time (min) for pigs using accelerometers. Using SAS, I checked for normality, and results showed data to be non-normal (Shapiro–Wilk < 0.05). I then performed residual analysis, which again showed non-normal data. Skewness was -0.42. The reason for the negative skewness was probably because there was a set upper limit (60 min) for the variable measured. So I reflected the data and did a reflected SQRT. I then fit the transformed data through the model and re-checked the residuals. Results were still non-normal. Any suggestion on what I can do?

• What model are you fitting? What questions are you asking of the data? What sample size do you have? What do the residuals look like (e.g. on a QQ plot)? May 12, 2014 at 23:46
• Hi Glen, I am fitting my datas with mixed linear model using SAS's Proc Mixed (with assumptions that data are normally distributed). My experiment design.We would like to see if the stand time for each pig differs in the different treatments (3 treatment groups) with 20 pigs in each treatment. Q-q plot has a curved pattern
– FTan
May 13, 2014 at 0:17
• Is your question necessarily about the mean or just a general location, or is something like $P(X>Y)>\frac{_1}{^2}$ sufficient for your purpose? What does the distribution within each treatment look like? May 13, 2014 at 0:25
• Please note that "has a curved pattern" isn't much help; that it would be curved is obvious from your earlier discussion. How much it curves and where matters. It would help if you'd show rather than tell. May 13, 2014 at 4:28
• Hi Glen. I am basically just comparing the means of the different treatment groups. May I know how I can share the curve graph here? I have it in words form ( copied from SAS). thx!
– FTan
May 14, 2014 at 16:19