regression -- predicted values

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regression -- predicted values

Dogan, Enis
Dear list

 

I hope this email finds you all well on this late Friday afternoon.
Quick question:

I ran a simple regression and saved Unstandardized Predicted Value;
Adjusted Predicted Value; and Standardized Predicted Value

 

What is the difference between Unstandardized Predicted Value and
Adjusted Predicted Value?

I get almost identical values on these variables, correlation = 1.00
almost however they are not necessarily 100% equal.

 

Any ideas?

 

Enis

 
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Re: regression -- predicted values

statisticsdoc
Stephen Brand
www.statisticsdoc.com

Enis,

The Unstandardized Predicted Value and the Standardized Predicted Value have
a perfect correlation  because they are simple linear transformations of one
another.  Illustrattively, the standardized predicted value involves the
subtraction of a constant (the mean predicted value) from each predicted
value, and division by a constant (the standard deviation of the predicted
values).

The adjusted predicted value is somewhat more complicated.  This is the
predicted value for a case when it is excluded from the computation of the
regression coefficients.

HTH,

Stephen Brand


For personalized and professional consultation in statistics and research
design, visit
www.statisticsdoc.com


-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]]On Behalf Of
Dogan, Enis
Sent: Friday, July 14, 2006 3:52 PM
To: [hidden email]
Subject: regression -- predicted values


Dear list



I hope this email finds you all well on this late Friday afternoon.
Quick question:

I ran a simple regression and saved Unstandardized Predicted Value;
Adjusted Predicted Value; and Standardized Predicted Value



What is the difference between Unstandardized Predicted Value and
Adjusted Predicted Value?

I get almost identical values on these variables, correlation = 1.00
almost however they are not necessarily 100% equal.



Any ideas?



Enis
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Re: regression -- predicted values

Hector Maletta
Agree with Stephen. Moreover, even the adjusted predicted values are
practically the same as the unadjusted, except in the case of outliers with
a disproportionate influence on the estimated coefficients. In many datasets
there are no cases with enough influence as to cause the correlation to be
less than (nearly) perfect.
Hector

-----Mensaje original-----
De: SPSSX(r) Discussion [mailto:[hidden email]] En nombre de
Statisticsdoc
Enviado el: Friday, July 14, 2006 11:12 PM
Para: [hidden email]
Asunto: Re: regression -- predicted values

Stephen Brand
www.statisticsdoc.com

Enis,

The Unstandardized Predicted Value and the Standardized Predicted Value have
a perfect correlation  because they are simple linear transformations of one
another.  Illustrattively, the standardized predicted value involves the
subtraction of a constant (the mean predicted value) from each predicted
value, and division by a constant (the standard deviation of the predicted
values).

The adjusted predicted value is somewhat more complicated.  This is the
predicted value for a case when it is excluded from the computation of the
regression coefficients.

HTH,

Stephen Brand


For personalized and professional consultation in statistics and research
design, visit
www.statisticsdoc.com


-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]]On Behalf Of
Dogan, Enis
Sent: Friday, July 14, 2006 3:52 PM
To: [hidden email]
Subject: regression -- predicted values


Dear list



I hope this email finds you all well on this late Friday afternoon.
Quick question:

I ran a simple regression and saved Unstandardized Predicted Value;
Adjusted Predicted Value; and Standardized Predicted Value



What is the difference between Unstandardized Predicted Value and
Adjusted Predicted Value?

I get almost identical values on these variables, correlation = 1.00
almost however they are not necessarily 100% equal.



Any ideas?



Enis
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Re: regression -- predicted values

Dogan, Enis
In reply to this post by Dogan, Enis
Thank you for the answers
One more related question:
I wanted adjust my DV for a covariate and plot the means of three
different groups on Y after this adjustment. I ran a simple regression
with the covariate as the only predictor. I saved the adjusted predicted
values (and I understand this adjustment is not the same adjustment I am
after) and plotted the mean 'adjusted predicted values' for three
groups.
Is this an OK procedure?
My hesitation is that these predicted values are "predicted" after all
and the accuracy of that prediction depends on the nature of the
relationship between the covariate and the DV; I don't think one can
pretend as of these are observed scores and compare the groups according
to their mean  adj predicted score.
I know I should be checking group by covariate interaction (and I did
actually)  but I am not sure that addresses my issue.\

Best,

Enis


-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of
Hector Maletta
Sent: Friday, July 14, 2006 10:42 PM
To: [hidden email]
Subject: Re: regression -- predicted values

Agree with Stephen. Moreover, even the adjusted predicted values are
practically the same as the unadjusted, except in the case of outliers
with
a disproportionate influence on the estimated coefficients. In many
datasets
there are no cases with enough influence as to cause the correlation to
be
less than (nearly) perfect.
Hector

-----Mensaje original-----
De: SPSSX(r) Discussion [mailto:[hidden email]] En nombre de
Statisticsdoc
Enviado el: Friday, July 14, 2006 11:12 PM
Para: [hidden email]
Asunto: Re: regression -- predicted values

Stephen Brand
www.statisticsdoc.com

Enis,

The Unstandardized Predicted Value and the Standardized Predicted Value
have
a perfect correlation  because they are simple linear transformations of
one
another.  Illustrattively, the standardized predicted value involves the
subtraction of a constant (the mean predicted value) from each predicted
value, and division by a constant (the standard deviation of the
predicted
values).

The adjusted predicted value is somewhat more complicated.  This is the
predicted value for a case when it is excluded from the computation of
the
regression coefficients.

HTH,

Stephen Brand


For personalized and professional consultation in statistics and
research
design, visit
www.statisticsdoc.com


-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]]On Behalf Of
Dogan, Enis
Sent: Friday, July 14, 2006 3:52 PM
To: [hidden email]
Subject: regression -- predicted values


Dear list



I hope this email finds you all well on this late Friday afternoon.
Quick question:

I ran a simple regression and saved Unstandardized Predicted Value;
Adjusted Predicted Value; and Standardized Predicted Value



What is the difference between Unstandardized Predicted Value and
Adjusted Predicted Value?

I get almost identical values on these variables, correlation = 1.00
almost however they are not necessarily 100% equal.



Any ideas?



Enis
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UNSUBSCRIBE

Jeff Aquino
In reply to this post by Hector Maletta
jeff





>From: Hector Maletta <[hidden email]>
>Reply-To: Hector Maletta <[hidden email]>
>To: [hidden email]
>Subject: Re: regression -- predicted values
>Date: Fri, 14 Jul 2006 23:42:15 -0300
>
>Agree with Stephen. Moreover, even the adjusted predicted values are
>practically the same as the unadjusted, except in the case of outliers with
>a disproportionate influence on the estimated coefficients. In many
>datasets
>there are no cases with enough influence as to cause the correlation to be
>less than (nearly) perfect.
>Hector
>
>-----Mensaje original-----
>De: SPSSX(r) Discussion [mailto:[hidden email]] En nombre de
>Statisticsdoc
>Enviado el: Friday, July 14, 2006 11:12 PM
>Para: [hidden email]
>Asunto: Re: regression -- predicted values
>
>Stephen Brand
>www.statisticsdoc.com
>
>Enis,
>
>The Unstandardized Predicted Value and the Standardized Predicted Value
>have
>a perfect correlation  because they are simple linear transformations of
>one
>another.  Illustrattively, the standardized predicted value involves the
>subtraction of a constant (the mean predicted value) from each predicted
>value, and division by a constant (the standard deviation of the predicted
>values).
>
>The adjusted predicted value is somewhat more complicated.  This is the
>predicted value for a case when it is excluded from the computation of the
>regression coefficients.
>
>HTH,
>
>Stephen Brand
>
>
>For personalized and professional consultation in statistics and research
>design, visit
>www.statisticsdoc.com
>
>
>-----Original Message-----
>From: SPSSX(r) Discussion [mailto:[hidden email]]On Behalf Of
>Dogan, Enis
>Sent: Friday, July 14, 2006 3:52 PM
>To: [hidden email]
>Subject: regression -- predicted values
>
>
>Dear list
>
>
>
>I hope this email finds you all well on this late Friday afternoon.
>Quick question:
>
>I ran a simple regression and saved Unstandardized Predicted Value;
>Adjusted Predicted Value; and Standardized Predicted Value
>
>
>
>What is the difference between Unstandardized Predicted Value and
>Adjusted Predicted Value?
>
>I get almost identical values on these variables, correlation = 1.00
>almost however they are not necessarily 100% equal.
>
>
>
>Any ideas?
>
>
>
>Enis