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
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