[R] Chi-square values in GLM model comparison

Wed Sep 11 19:50:10 CEST 2013

There is no argument 'test' to anova.clm hence the error message.

The likelihood ratio statistic (or, alternatively, G^2 statistic or
Deviance statistic) has an asymptotic chi-square distribution, so it
is the size of that statistic your reviewers are asking for. It is
printed in the anova output under the name 'LR.stat' (1252 on 8 df in
your case it seems).

Cheers,
Rune

On 11 September 2013 18:17, Torvon <torvon at gmail.com> wrote:
> 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 at 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 at r-project.org [mailto:r-help-bounces at r-project.org]
>> On Behalf Of Torvon
>> Sent: 11 September 2013 16:48
>> To: r-help at 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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>         [[alternative HTML version deleted]]
>
>
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