[R] who can explain the difference between the R and SAS on the results of GLM

From: zhijie zhang <epistat_at_gmail.com>
Date: Wed 05 Jul 2006 - 00:44:38 EST


Dear friends,
 I used R and SAS to analyze my data through generalized linear model, and there is some difference between them.

Results from R:

glm(formula = snail ~ grass + gheight + humidity + altitude + soiltemr + airtemr, family = Gamma)

Deviance Residuals:

     Min 1Q Median 3Q Max

-1.23873 -0.41123 -0.08703 0.24339 1.21435

Coefficients:

                   Estimate Std. Error t value Pr(>|t|)


(Intercept) 2.024e-02 1.655e-02 1.223 0.22320

grasshuanghuacai 1.321e-02 5.053e-03 2.615 0.00982 **

grasshucao 1.962e-04 1.971e-03 0.100 0.92083

grassyuhao -1.881e-03 2.041e-03 -0.922 0.35810

gheight -1.275e-04 6.288e-05 -2.027 0.04441 *

humidity 6.797e-02 2.278e-02 2.983 0.00332 **

altitudelow -5.090e-03 1.905e-03 -2.671 0.00837 **

soiltemr -8.584e-04 5.165e-04 -1.662 0.09858 *.* #is it show that soiltemr maybe significant at a=0.05???

airtemr 6.547e-05 1.803e-04 0.363 0.71695

---

Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1




(Dispersion parameter for Gamma family taken to be 0.2745989)
Null deviance: 63.635 on 161 degrees of freedom Residual deviance: 43.214 on 153 degrees of freedom AIC: 1527.6 Results From SAS *proc* *genmod* data=a order=data; class grass altitude; model snail = grass gheight humidity altitude soiltemr airtemr / dist=gamma type3; *run*; Analysis Of Parameter Estimates Standard Wald 95% Confidence Chi- Parameter DF Estimate Error Limits Square Pr > ChiSq Intercept 1 0.0202 0.0160 -0.0111 0.0516 1.60 0.2052 grass hucao 1 0.0002 0.0019 -0.0035 0.0039 0.01 0.9179 grass yuhao 1 -0.0019 0.0020 -0.0057 0.0020 0.91 0.3397 grass huanghuacai 1 0.0132 0.0049 0.0037 0.0228 7.34 0.0068 grass diluo 0 0.0000 0.0000 0.0000 0.0000 . . gheight 1 -0.0001 0.0001 -0.0002 -0.0000 4.41 0.0358 humidity 1 0.0680 0.0220 0.0249 0.1111 9.55 0.0020 altitude low 1 -0.0051 0.0018 -0.0087 -0.0015 7.66 0.0057 altitude high 0 0.0000 0.0000 0.0000 0.0000 . . soiltemr 1 -0.0009 0.0005 -0.0018 0.0001 2.96 0.0852 airtemr 1 0.0001 0.0002 -0.0003 0.0004 0.14 0.7067 Scale 1 3.9077 0.4170 3.1702 4.8167 NOTE: The scale parameter was estimated by maximum likelihood. The GENMOD Procedure LR Statistics For Type 3 Analysis Chi- Source DF Square Pr > ChiSq grass 3 17.60 0.0005 gheight 1 4.26 0.0390 humidity 1 9.11 0.0025 altitude 1 7.67 0.0056 soiltemr 1 2.89 0.0889 airtemr 1 0.14 0.7050 Questions: 1.About the variable soiltemr: R could say it maybe significant at 0.05, while SAS don't give this information,why was that in R? 2.Their dispersion parameters are different, although they are estimated automatically,why? 3.From R's Results, i can write my model like this: snail=1.321e-02* grasshuanghuacai+1.962e-04* grasshucao-1.881e-03* grassyuhao-1.275e-04*gheight+6.797e-02*humidity-5.090e-03*altitudelow-8.584e-04*soiltemr is it correct? thanks very much! -- Kind Regards, Zhi Jie,Zhang ,PHD Department of Epidemiology School of Public Health Fudan University Tel:86-21-54237149 [[alternative HTML version deleted]] ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Received on Wed Jul 05 00:49:13 2006

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