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.Iparraguirre@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-bounces@r-project.org [mailto:r-help-bounces@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
>
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