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Date:         Thu, 4 Feb 1999 16:12:33 -0600
Reply-To:     Gullion Christina <Christina.Gullion@COLUMBIA.NET>
Sender:       "SAS(r) Discussion" <SAS-L@UGA.CC.UGA.EDU>
From:         Gullion Christina <Christina.Gullion@COLUMBIA.NET>
Subject:      Re: IML
Comments: To: "hwang@ZSASSOCIATES.COM" <hwang@ZSASSOCIATES.COM>
Content-Type: text/plain

I've done monte carlo studies of number of factors criteria and nonorthogonal rotation criteria in factor analysis using SAS matrix language. Most of the criteria and rotation methods were and are not available in SAS PROC FACTOR. I needed to do matrix multiplication, inversions, rescaling (normalization) to column and or row sums of squares. All are simple in IML because it operates on whole rows or columns with equal ease. It can take a lot less programming to format printing large matrices too, e.g., partitioning a 100 x 100 correlation matrix together with its 100-item variable name vector to give row and column labels into page-size chunks. It's also rather handy for inputting the lower triangular of a symmetric matrix, then getting the full matrix with a simple transpose and matrix addition. And finally, if you want to do anything statistical that SAS hasn't implemented yet and that involves >1 variable, you might find it's a lot easier to do in IML than a data step. I've seen IML routines for doing survival analysis with time-dependent status, robust regression, power analysis, etc. Or you could test a SAS PROC by writing your own IML routine and verifying that it's handling certain feature of the data the way you expect it to. It's an all-around fun product. Too bad it's not in SAS/STAT.

Chris Christina M. Gullion, Ph.D. Biostatistician and Supervisor, Clinical Research Department of Clinical Research Medical City Dallas Hospital 972/566-4718 fax 972/566-4715

> -----Original Message----- > From: hongjie Wang [SMTP:hwang@ZSASSOCIATES.COM] > Sent: Thursday, February 04, 1999 8:49 AM > To: SAS-L@UGA.CC.UGA.EDU > Subject: IML > > Dear Friends, Can any one offer me some insights on the usefulness of IML? > Other than its matrix operations, does it offer anything else? > In lots of textbooks and tutorials on SAS, I notice that IML is introduced > in the context of regression. > Authors show how one can implement the regression using IML directly, > instead of proc reg. > I sense it must have some other features that can not be accomplished in > base sas. > > Your input is greatly apprecaited. > > Hongjie


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