topic Query of Response Screening in New England JMP Users Group https://community.jmp.com/t5/New-England-JMP-Users-Group/Query-of-Response-Screening/m-p/19250#M2 <HTML><HEAD></HEAD><BODY><P>I have an interactive database of 67 gene levels in multiple specimens ~100. These genes were chosen for probable activity. Many of the genes are interactive with others. I am trying to determine the best group of genes that correlate with each individual gene. Using various platforms (predictor screening utility, boosted tree/forest in partition, response screening in modeling, and screening in modeling), I get a similar hierarchy of genes, which make biological sense. However, using response screening in fit model, I get a very different hierarchy, which makes much less biological sense. Any ideas why the response screening in fit model is so different.</P><P></P><P>Thanks, Neal</P></BODY></HTML> Mon, 27 Jun 2016 14:45:24 GMT rexneal 2016-06-27T14:45:24Z Query of Response Screening https://community.jmp.com/t5/New-England-JMP-Users-Group/Query-of-Response-Screening/m-p/19250#M2 <HTML><HEAD></HEAD><BODY><P>I have an interactive database of 67 gene levels in multiple specimens ~100. These genes were chosen for probable activity. Many of the genes are interactive with others. I am trying to determine the best group of genes that correlate with each individual gene. Using various platforms (predictor screening utility, boosted tree/forest in partition, response screening in modeling, and screening in modeling), I get a similar hierarchy of genes, which make biological sense. However, using response screening in fit model, I get a very different hierarchy, which makes much less biological sense. Any ideas why the response screening in fit model is so different.</P><P></P><P>Thanks, Neal</P></BODY></HTML> Mon, 27 Jun 2016 14:45:24 GMT https://community.jmp.com/t5/New-England-JMP-Users-Group/Query-of-Response-Screening/m-p/19250#M2 rexneal 2016-06-27T14:45:24Z