```Date: Thu, 14 May 1998 14:46:39 -0500 Reply-To: Max Martin Sender: "SPSSX(r) Discussion" From: Max Martin Subject: Re: SMCs Comments: To: "John A. Schinka, Ph.D." Content-Type: text/plain; charset="iso-8859-1" If I remember my grad training, Principal Axis Factoring uses the SMCs of the variables as initial estimates of communalities along the principal diagonal of the R matrix before factor extraction. These estimates are then changed at each iteration until the final communalities are calculated upon termination of the factor routine. Hence, there would be no reason to expect the SMCs to be identical with the final communalities. Hope this helps Max %&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%& Dr. Max R. Martin Senior Evaluator Department of Research, Evaluation, Info Systems & Technology Edgewood ISD, San Antonio, TX 210-431-9120 FAX: 210-433-5134 mmartin@edgewood-sa.k12.tx.us %&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%& Experience is a wonderful teacher-- it allows us to recognize a mistake after we've made it again! %&%&%&%&%&%&%&%&%&%&%&%&%&%&%&%& -----Original Message----- From: John A. Schinka, Ph.D. Newsgroups: bit.listserv.spssx-l To: SPSSX-L@UGA.CC.UGA.EDU Date: Thursday, May 14, 1998 8:13 AM Subject: SMCs > I am examining the characteristics of a personality scale >consisting of 33 items. The Reliability routine does not produce item >SMCs (squared multiple correlations) because the determinant of the >covariance matrix is essentially zero (this information provided via a >warning). Yet, the Factor routine, employing principal axis factoring + >promax, produces values for the communalities for each item. I believe >these communalities are the item SMCs. The calculated determinant for >this analysis is essentially zero. Can someone explain the >inconsistency here? Am I correct in assuming that the communalities are >the item SMCs? It seems unlikely, because the values are all <.70 and >I'm assuming the determinant problem is caused by multicollinearity. >Clarification? > > Is there an easy way to determine the SMC for each item in a >matrix? As I'm examining about 100 scales of length from 20-70 items, >using multiple linear regression procedures are out of the question from >a practical standpoint. Appreciate your comments! ```

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