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Date:         Tue, 7 Sep 2010 16:55:02 +0200
Reply-To:     "Ginkel, Joost van" <JGinkel@fsw.leidenuniv.nl>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         "Ginkel, Joost van" <JGinkel@fsw.leidenuniv.nl>
Subject:      Re: Imputation Question
Comments: To: "Courtney M. Cronley" <cronley@rci.rutgers.edu>
In-Reply-To:  A<679429446.14230.1283870462355.JavaMail.tomcat@aurora>
Content-Type: text/plain; charset="us-ascii"

Dear Courtney,

You can either change the measurement level of those ordinal variables of which it wouldn't do much harm to treat them as numeric. You can do this by changing the Measure of the specific variables in variable view. Or you can change the maximum number of modelparameters in the syntax (for example, MAXMODELPARAM = 100000). However, the latter will take a lot of computation time. Good luck!

Best regards,

Joost van Ginkel

Joost R. van Ginkel, PhD Leiden University Faculty of Social and Behavioural Sciences PO Box 9555 2300 RB Leiden The Netherlands Tel: +31-(0)71-527 3620 Fax: +31-(0)71-527 1721

-----Original Message----- From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of Courtney M. Cronley Sent: Tuesday, September 07, 2010 4:41 PM To: SPSSX-L@LISTSERV.UGA.EDU Subject: Imputation Question

I am trying to imputem missing values. I have a data set with 500 variables, both interval and ordinal. When I run the imputation, I get this error message:

The imputation model for r022q1C contains more than 100 parameters. No missing values will be imputed. Reducing the number of effects in the imputation model, by merging sparse categories of categorical variables, changing the measurement level of ordinal variables to scale, removing two-way interactions, or specifying constraints on the roles of some variables, may resolve the problem. Alternatively increase the maximum number of parameters allowed on the MAXMODELPARAM keyword of the IMPUTE subcommand. Execution of this command stops.

Any ideas on what I can do? The ro22q1C variable is an ordinal variable.

Thanks!

Courtney

Courtney Cronley, Ph.D. Postdoctoral Associate Center of Alcohol Studies Rutgers University cronley@rci.rutgers.edu

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