Hello everyone,

I have a dataset whose dependent variable is heavily skewed to the left. The independent variables are all categorical. Although the residuals are normally distributed, there is strong evidence of heteroskedasticity. The number of observations is over 500. The dependent variable was collected using on a Likert-Scale calibrated instrument. So basically, I am running a predictive model, using the xi: pr(0.15) pe(0.1): reg .... to obtain the determinants/predictors of the outcome. One of my supervisors suggests I used the nonparametric tests and provide the median and the inter-quartile ranges. When I use the "npregress kernel y i.x1 i.x2...i.xn" Stata command, I get the output with the following warning "Convergence not achieved". I have also used other median Stata commands such as sqreg, iqreg, qreg, rreg and reg y i.x1 i.x2,...i.xn, robust. These are giving me different results.

Anyone guide me on the best way to handle such a problematic dataset? Which of the stata commands produces near-valid results? How does one maximise the npregress kernel command - the instructions on Stata are not clear and when I try, Stata produces the error output.

Thank you