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Date:   Thu, 2 Jul 1998 16:15:49 -0500
Reply-To:   "Nichols, David" <nichols@SPSS.COM>
Sender:   "SPSSX(r) Discussion" <SPSSX-L@UGA.CC.UGA.EDU>
From:   "Nichols, David" <nichols@SPSS.COM>
Subject:   Re: Non Linear Relationships and Factor Analysis
Comments:   To: Joel KADDOUR <kaddour@CLSH.U-NANCY.FR>

Nonlinear principal components analysis in PRINCALS in SPSS allows multiple options for the measurement levels of the variables, but it's really for categorical data (the values have to be positive integers). The ALSCAL multidimensional scaling procedure also allows the ability to specify interval or ratio as the measurement level, though only for dissimilarity data. SPSS does not have a nonlinear factor analysis procedure.

David Nichols Principal Support Statistician and Manager of Statistical Support SPSS Inc.

---------- From: Joel KADDOUR [SMTP:kaddour@CLSH.U-NANCY.FR] Sent: Wednesday, June 17, 1998 6:32 AM To: SPSSX-L@UGA.CC.UGA.EDU Subject: Non Linear Relationships and Factor Analysis

To study relationships between variables that are Non Linear Related we can use Non Linear Regression or Linear regression if this relation can be linearized (f.i. Log-Linear or Power models).

Usually to extract a latent variable or a component we can use Factor Analysis or Principal Components Analysis. But in this two models equations are linear.

1) How does PCA or FA deals with curvilinear relationships, it seems difficult to linearize relationships between two variables without curvilinearizing (sorry for this ugly word) the relations with other variables.

A solution is to use other models to study the structure such as MultiDimensional Scaling, or Non Linear Principal Components Analysis, but doing this, i loose benefits of metrics property of my measure (scores at subtests).

2) Can I extract factors or principal components from variables that are curvilinear related, keeping metrics property of my measure ?

Errors certainly occured in this line, references of articles are welcome (not for my poor english but for Non Linear Relationships )!

Regards

Joel KADDOUR Groupe d'Analyse Psychometrique des COnduites (GRAPCO) Universite Nancy 2 B.P. 33-97 F - 54015 Nancy Cedex kaddour@clsh.u-nancy.fr


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