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

[Nathan Pace]

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 at utah.edu



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