Save Individual growth Parameters

[William Dudley WNDUDLEY]

I need to save individual growth parameters for a growth curve model using the linear mixed model.
That is, I need to save (in a spss data set)  for each individual his or her intercept, slope etc...
Does version 17 have this capacity.

Thanks in advance


William N. Dudley, PhD
Associate Dean for Research
The School of Health and Human Performance Office of Research
The University of North Carolina at Greensboro
126 HHP Building, PO Box 26170
Greensboro, NC 27402-6170
VOICE 336.2562475
FAX [phone]

[Zdaniuk, Bozena-2]

HLM software does it but I don't know about SPSS.

bozena

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From: SPSSX(r) Discussion [[hidden email]] On Behalf Of William Dudley WNDUDLEY [[hidden email]]
Sent: Tuesday, October 27, 2009 12:22 PM
To: [hidden email]
Subject: Save Individual growth Parameters

I need to save individual growth parameters for a growth curve model using the linear mixed model.
That is, I need to save (in a spss data set)  for each individual his or her intercept, slope etc...
Does version 17 have this capacity.

Thanks in advance


William N. Dudley, PhD
Associate Dean for Research
The School of Health and Human Performance Office of Research
The University of North Carolina at Greensboro
126 HHP Building, PO Box 26170
Greensboro, NC 27402-6170
VOICE 336.2562475
FAX [phone]

[Bruce Weaver]

William Dudley WNDUDLEY wrote

I need to save individual growth parameters for a growth curve model using
the linear mixed model.
That is, I need to save (in a spss data set)  for each individual his or
her intercept, slope etc...
Does version 17 have this capacity.

Thanks in advance

SAVE Subcommand (MIXED command) -- From the version 17 Help

Use the SAVE subcommand to save one or more casewise statistics to the active dataset.

• Specify one or more temporary variables, each followed by an optional new name in parentheses.

• If new names are not specified, default names are generated.

FIXPRED - Fixed predicted values. The regression means without the random effects.

PRED - Predicted values. The model fitted value.

RESID - Residuals. The data value minus the predicted value.

SEFIXP - Standard error of fixed predicted values. These are the standard error estimates for the fixed effects predicted values obtained by the keyword FIXPRED.

SEPRED - Standard error of predicted values. These are the standard error estimates for the overall predicted values obtained by the keyword PRED.

DFFIXP - Degrees of freedom of fixed predicted values. These are the Satterthwaite degrees of freedom for the fixed effects predicted values obtained by the keyword FIXPRED.

DFPRED - Degrees of freedom of predicted values. These are the Satterthwaite degrees of freedom for the fixed effects predicted values obtained by the keyword PRED.

Example
MIXED  SCORE BY SCHOOL CLASS WITH AGE
  /FIXED = AGE
  /RANDOM = SCHOOL CLASS(SCHOOL)
  /SAVE = FIXPRED(BLUE) PRED(BLUP) SEFIXP(SEBLUE) SEPRED(SEBLUP).

• The SAVE subcommand appends four variables to the active dataset: BLUE, containing the fixed predicted values, BLUP, containing the predicted values, SEBLUE, containing the standard error of BLUE, and SEBLUP, containing the standard error of BLUP.