Hi, I am writing my final dissertatation for my master degree.
The objective is to create an index of performance evaluation of professional car racing drivers. I am doing so through statistical data mining techniques, but I am a novice with SAS.
I was wondering if it is possible to receive some instructions on how to do it, or just directions on where I can find some useful material to learn more about that.
Thanks
There are many directions to take your question but one technique you might want to consider is Stochastic Frontier Modeling. The underlying model assumes there is a maximum efficiency that can be obtained. Agents in the model can be evaluated based on their "closeness" to maximum efficiency.
Here is a link to its implementation in SAS. SAS/ETS(R) 12.3 User's Guide
Also, here a link to paper you might mind useful. http://isbm.smeal.psu.edu/library/working-paper-articles/2004-working-papers/06-2004-measuring-perfo...
It doesn't sound as if your data are confidential. Would you like to share them?
There are many directions to take your question but one technique you might want to consider is Stochastic Frontier Modeling. The underlying model assumes there is a maximum efficiency that can be obtained. Agents in the model can be evaluated based on their "closeness" to maximum efficiency.
Here is a link to its implementation in SAS. SAS/ETS(R) 12.3 User's Guide
Also, here a link to paper you might mind useful. http://isbm.smeal.psu.edu/library/working-paper-articles/2004-working-papers/06-2004-measuring-perfo...
It doesn't sound as if your data are confidential. Would you like to share them?
Being that you are a newbie, it should be pointed out that ETS is not part of Base SAS license, but optional at extra cost.
This sounds like a very good starting point, I'll take a deeper look into that.....however, you were mentioning that many techniques exist; which other would you recommend me to consider?
Thanks a lot.
PS: yes, my data are not confidential...my database is still "under construction", I'd love to share it once it's done
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