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issac
Fluorite | Level 6

Hi folks;

I've run gam procedure to a data set and got the following output table. I wonder how I can calculate a pseudo R-Squared with the help of deviance.

Number of Observations49988
Number of Missing Observations12
DistributionGaussian
Link FunctionIdentity

Final Number of Backfitting Iterations4
Final Backfitting Criterion1.6618101E-9
The Deviance of the Final Estimate240768.87317

  
The backfitting algorithm converged.

Thanks!

Issac

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Accepted Solutions
AllenMcDowell
SAS Employee

One possibility is discussed in Cameron and Trevedi's "Regression Analysis of Count Data" which describes the deviance as the GLM generalization of the sum of squares. They refer to two papers by Cameron and Windmeijer where a pseudo-R-squared is proposed based on a decomposition of the deviance. In essence, the proposal is to use R2 = 1-(D(intercept-only-model)/D(full-model)). I would recommend reviewing the original papers to verify that the interpretation is appropriate for your particular model before using the result.

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AllenMcDowell
SAS Employee

One possibility is discussed in Cameron and Trevedi's "Regression Analysis of Count Data" which describes the deviance as the GLM generalization of the sum of squares. They refer to two papers by Cameron and Windmeijer where a pseudo-R-squared is proposed based on a decomposition of the deviance. In essence, the proposal is to use R2 = 1-(D(intercept-only-model)/D(full-model)). I would recommend reviewing the original papers to verify that the interpretation is appropriate for your particular model before using the result.

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