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10-12-2015 03:18 PM

My dependent variable contains positive integers truncated at 1. It is also quite skewed. The n is small with 48 observations. My first try was a multiplicative (log-log) model. Thinking I could improve on the Mean Squared Error, I tried quantile regression at the 25th percentile. This had the positive effect of reducing the MSE by 33% versus the OLS multiplicate model, but had the undesireable result of producing some negative predictions. So, I tried Proc QLIM specifying a truncated lower bound equal to 1, thinking that any predictions from this procedure would be constrained at the lower bound.

I was wrong. Proc QLIM produces negative predictions in spite of a lower bound at 1. This result is unexpected and surprising. The documentation doesn't address the issue.

What am I missing here?

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Posted in reply to xtc283x

10-12-2015 03:51 PM

Have you tried Poisson and negaiive binomial counts models (available with many procedures, such as COUNTREG)?

PG

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Posted in reply to PGStats

10-12-2015 03:58 PM

I have not tried those but they are good suggestions which I will pursue. Regardless, I'm still curious about why QLIM is giving me negative predictions. Any insights?