[R-sig-ME] diagnostic test meta analysis using glmer

[Thierry Onkelinx]

Dear Nathan,

You can use the glht() function from the multcomp package to do post-hoc
tests on contrasts. You should create a custom K matrix. See
https://thebiobucket.blogspot.be/2011/06/glmm-with-custom-multiple-comparisons.html#more

Best regards,

Thierry


ir. Thierry Onkelinx
Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx op inbo.be
Kliniekstraat 25, B-1070 Brussel
www.inbo.be

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Van 14 tot en met 19 december 2017 verhuizen we uit onze vestiging in
Brussel naar het Herman Teirlinckgebouw op de site Thurn & Taxis.
Vanaf dan ben je welkom op het nieuwe adres: Havenlaan 88 bus 73, 1000
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2017-11-14 7:04 GMT+01:00 Nathan Pace <n.l.pace op utah.edu>:

> Hi,
>
> I am modeling the sensitivity and specificity of 7 diagnostic tests in a
> bivariate binomial model using glmer.
>
> glmer(formula = cbind(true, n - true) ~ 0 + seM + spM + seMM + spMM +
> seMouth + spMouth +
>                           seSM + spSM + seTM + spTM + seULBT + spULBT +
> seW + spW +
>                           (0 + sens + spec | studyName), data =
> Compare_DL.df, family = binomial, nAGQ = 1)
>
> The model without separating diagnostic tests is
>
> glmer(formula = cbind(true, n - true) ~  0 + sens + spec + (0 + sens +
> spec | studyName),
>                       data = Compare_DL.df, family = binomial, nAGQ = 1)
>
> The 7 test model assumes equal variances across tests.
>
> The dataset includes sens, spec, seM, spM, etc as dummy index variables.
> Both models can run and converge.
>
> ANOVA shows improved fit:
>
>                           Df   AIC      BIC        logLik     deviance
> Chisq Chi Df    Pr(>Chisq)
> Simple model    5 8987.8 9007.6 -4488.9   8977.8
> Separate tests 17 6878.5 6945.8 -3422.3   6844.5      2133.3     12     <
> 2.2e-16 ***
>
> I need to identify any separation of sensitivity and specificity
> properties among the 7 tests.
>
> One possibility would be to jointly contrast seTesti – seTestj  = 0 and
> spTesti – spTestj = 0 for all pairwise comparisons of the 7 tests (with
> multiplicity adjustment).
>
> However, I am unable to construct such tests in lme4. Is this possible in
> lme4? If so, what is the code?
>
> I have looked at other packages (multcomp) without success.
>
> As usual, all help will be appreciated.
>
> Nathan Pace, MD, MStat
> University of Utah
> Salt Lake City, UT
> n.l.pace op utah.edu
>
>
>
> ---
>
>
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