[R] GLM result output..
David Winsemius
dwinsemius at comcast.net
Sun Sep 15 17:30:26 CEST 2013
On Sep 15, 2013, at 2:15 AM, Lutfor Rahman wrote:
> Thanks for that. Still I am a bit confused. Please advice me.
> Now, I have got minimal adequate model keeping all the those significant predictors in the model which is shown below:
> Coefficients:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) 5.846747 0.987461 5.921 3.2e-09 ***
> orgmatter -0.886985 0.235347 -3.769 0.000164 ***
> baresoil -0.935106 0.293838 -3.182 0.001461 **
> orgmatter:moistcont 0.009452 0.002759 3.426 0.000612 ***
> baresoil:moistcont 0.025640 0.009698 2.644 0.008194 **
> wood10:grass10 0.007433 0.003187 2.333 0.019667 *
> grass10:rdnet10 0.004822 0.001563 3.085 0.002036 **
> wood10:rdnet10 -0.045485 0.016890 -2.693 0.007081 **
>
> But when I do anova test of this minimal adequate model, only baresoil:moistcont, grass10:rdnet, wood10:rdnet10 were found significant.
>
> Df Deviance Resid. Df Resid. Dev Pr(>Chi)
> NULL 17 36.167
> orgmatter 1 2.4260 16 33.741 0.119334
> baresoil 1 1.0871 15 32.654 0.297104
> orgmatter:moistcont 1 2.5611 14 30.093 0.109526
> baresoil:moistcont 1 8.2976 13 21.795 0.003970 **
> wood10:grass10 1 0.0184 12 21.777 0.892042
> grass10:rdnet10 1 5.4520 11 16.325 0.019546 *
> wood10:rdnet10 1 8.1565 10 8.168 0.004291 **
>
> So, when I report the outcome of this model, should I show summary significance values or anova significance value (chi-square).
I don't think you should report anything. You need a consultation.
Rhelp is established to offer technical advice about running R code.
From the Posting Guide:
"Questions about statistics: The R mailing lists are primarily intended for questions and discussion about the R software. However, questions about statistical methodology are sometimes posted. If the question is well-asked and of interest to someone on the list, it may elicit an informative up-to-date answer. See also the Usenet groups sci.stat.consult (applied statistics and consulting) and sci.stat.math (mathematical stat and probability).
Basic statistics and classroom homework: R-help is not intended for these."
--
David.
>
> Regards
> Lutfor
>
>
>
>
>
> On Fri, Sep 13, 2013 at 7:42 PM, David Winsemius <dwinsemius at comcast.net> wrote:
>
> On Sep 13, 2013, at 9:38 AM, Lutfor Rahman wrote:
>
> Dear forum members,
>
> Please help me understanding significance value when GLM done in r.
>
> After doing minimal adequate model, I have found a number of independent
> values which are significant. But doing their anova significant values are
> different. Please find my result following. Which significant values should
> I use.
>
>
> glm(formula = richness ~ moistcont + orgmatter + baresoil + grass10 +
> wood10 + rdnet10 + moistcont:orgmatter + moistcont:baresoil +
> grass10:wood10 + grass10:rdnet10 + wood10:rdnet10, family = poisson,
> data = data)
>
> Deviance Residuals:
> Min 1Q Median 3Q Max
> -1.19112 -0.33682 0.09813 0.32808 0.70509
>
> Coefficients:
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) 11.384447 4.014170 2.836 0.00457 **
> moistcont -0.095813 0.084995 -1.127 0.25962
> orgmatter -1.810116 0.613688 -2.950 0.00318 **
> baresoil -1.636707 0.559129 -2.927 0.00342 **
> grass10 -0.018979 0.065647 -0.289 0.77250
> wood10 0.150683 0.128386 1.174 0.24053
> rdnet10 -0.011448 0.068090 -0.168 0.86648
> moistcont:orgmatter 0.025698 0.011521 2.231 0.02571 *
> moistcont:baresoil 0.044110 0.015799 2.792 0.00524 **
> grass10:wood10 0.010740 0.006498 1.653 0.09838 .
> grass10:rdnet10 0.011013 0.004412 2.496 0.01255 *
> wood10:rdnet10 -0.088297 0.027120 -3.256 0.00113 **
>
> The only p-value I would have expected to be the same would have been the last one in the avova output:
>
> Df Deviance Resid. Df Resid. Dev Pr(>Chi)
> .....
>
> wood10:rdnet10 1 10.7812 6 3.928 0.001025 **
>
> And that particular p-value is not far off from the 0.00113 value reported in the model summary. The other p-values are not of the same sort. The p-values above are basically reporting the "significance" of removing single predictors or interactions from the full model. The anova reported below is perfoming sequential addition of terms to a NULL model as well as doing a different test: LR tests instead of Wald statistics.
>
> --
> David.
>
>
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> (Dispersion parameter for poisson family taken to be 1)
>
> Null deviance: 36.1673 on 17 degrees of freedom
> Residual deviance: 3.9276 on 6 degrees of freedom
> AIC: 97.893
>
> Number of Fisher Scoring iterations: 4
>
> anova(data1, test="Chisq")
> Analysis of Deviance Table
>
> Model: poisson, link: log
>
> Response: richness
>
> Terms added sequentially (first to last)
>
>
> Df Deviance Resid. Df Resid. Dev Pr(>Chi)
> NULL 17 36.167
> moistcont 1 8.6322 16 27.535 0.003303 **
> orgmatter 1 2.1244 15 25.411 0.144966
> baresoil 1 0.0029 14 25.408 0.956986
> grass10 1 1.5251 13 23.883 0.216842
> wood10 1 3.6952 12 20.187 0.054570 .
> rdnet10 1 0.0001 11 20.187 0.990564
> moistcont:orgmatter 1 2.0482 10 18.139 0.152381
> moistcont:baresoil 1 2.8730 9 15.266 0.090076 .
> grass10:wood10 1 0.1431 8 15.123 0.705247
> grass10:rdnet10 1 0.4141 7 14.709 0.519883
> wood10:rdnet10 1 10.7812 6 3.928 0.001025 **
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
> David Winsemius, MD
> Alameda, CA, USA
>
>
David Winsemius
Alameda, CA, USA
More information about the R-help
mailing list