José,
I get the following error message:
> m1<-clm(sym_bin ~ phq_index, data=data2)
> m2<-clm(sym_bin ~ 1, data=data2)
> anova(m1,m2,test="Chisq")
> Error in anova.clm(m1, m2, test = "Chisq") :
> only 'clm' and 'clmm' objects are allowed
My dependent variable is binary, so I don't know what the problem could be.
See below the model summaries. Thank you! Eiko
> summary(m1)
formula: sym_bin ~ phq_index
data: data2
link threshold nobs logLik AIC niter max.grad cond.H
logit flexible 12348 -4846.49 9710.97 7(0) 2.53e-08 1.4e+02
Coefficients:
Estimate Std. Error z value Pr(>|z|)
phq_index2 -0.29705 0.11954 -2.485 0.013 *
phq_index3 0.63382 0.10262 6.176 6.56e-10 ***
phq_index4 1.53022 0.09664 15.834 < 2e-16 ***
phq_index5 0.90720 0.09996 9.075 < 2e-16 ***
phq_index6 -0.03855 0.11337 -0.340 0.734
phq_index7 -0.06488 0.11394 -0.569 0.569
phq_index8 -1.15618 0.15156 -7.628 2.38e-14 ***
phq_index9 -2.50064 0.25670 -9.741 < 2e-16 ***
---
Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1
Threshold coefficients:
Estimate Std. Error z value
0|1 1.87770 0.07959 23.59
> summary(m2)
formula: sym_bin ~ 1
data: data2
link threshold nobs logLik AIC niter max.grad
logit flexible 12348 -5472.48 10946.96 5(0) 1.01e-11
Threshold coefficients:
0|1
1.642
On 11 September 2013 18:03, Jose Iparraguirre <
jose.iparragui...@ageuk.org.uk> wrote:
> Hi Eiko,
>
> How about this?
>
> > anova (m1, m2, test="Chisq")
>
> See: ?anova.glm
>
> Regards,
> José
>
>
> Prof. José Iparraguirre
> Chief Economist
> Age UK
>
>
>
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
> On Behalf Of Torvon
> Sent: 11 September 2013 16:48
> To: r-help@r-project.org
> Subject: [R] Chi-square values in GLM model comparison
>
> Hello --
> I am comparing two
> GLMs (binomial dependent variable)
> , the results are the following:
> > m1<-glm(symptoms ~ phq_index, data=data2) m2<-glm(symptoms ~ 1,
> > data=data2)
>
> Trying to compare these models using
> > anova (m1, m2)
> I do not obtain chi-square values or a chi-square difference test;
> instead, I get loglikelihood ratios:
>
> > Likelihood ratio tests of cumulative link models:
> > formula: link: threshold:
> > m2 sym_bin ~ 1 logit flexible
> > m1 sym_bin ~ phq_index logit flexible
> > no.par AIC logLik LR.stat df Pr(>Chisq)
> > m2 1 10947 -5472.5
> > m1 9 9711 -4846.5 1252 8 < 2.2e-16 ***
>
> Since reviewers would like me to report chi-square values: how to I obtain
> them when comparing GLMs? I'm looking for an output similar to the output
> of the GLMER function in LME4, e.g.:
>
> > anova(m3,m4)
> ...
> > Df AIC BIC logLik Chisq Chi Df Pr(>Chisq)
> > m3 13 11288 11393 -5630.9
> > m4 21 11212 11382 -5584.9 92.02 8 < 2.2e-16 ***
>
> Thank you!
> Eiko
>
> [[alternative HTML version deleted]]
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