Thanks for the information.
Ben Adarkwa Dwamena, MD
Assistant Professor of Radiology
Division of Nuclear Medicine
Department of Radiology
University of Michigan Medical School
1500 E. Medical Center Drive
B1 G505 University Hospital
Ann Arbor, MI 48109-0028
[email protected]
http://sitemaker.umich.edu/metadiagnosis
http://sitemaker.umich.edu/oncopet
Staff Physician
D748 Nuclear Medicine Service (115),
VA Ann Arbor Health Care System
2215 Fuller Road
Ann Arbor, MI 48105
734-761-7886 Phone
734-761-5229 Fax
>>> [email protected] 12/5/2004 11:52:08 AM >>>
Hi Ben,
Unfortunately this "HSROC" model can't be fitted in -gllamm- due to the
nonlinear nature of the "exp(betai*disij)" term. We checked this with
one of
the authors of -gllamm-. WinBUGS and the NLMIXED procedure in SAS
appear to
be the only ways to fit this model at present.
Best wishes,
Roger.
--On 02 December 2004 12:26 -0500 Ben Dwamena <[email protected]>
wrote:
> Described below is a multilevel model basd on ordinal regression for
> diagnostic meta-analysis (SROC) for which codes are available for
SAS
> and WinBUGS and wanted to now how this may be modeled using gllamm?
>
> I know how to model the expression logit n=thetai+alphai*disij
> However, I am not sure how to include the scale parameter so that
the
> above is multiplied by exp(betai*disij ) .
>
>
> HSROC MODEL
> LEVEL 1
> For each study (i), the number testing positive is assumed to follow
a
> binomial distribution
> yij ~B(nij,, alphaij)
>
> where j=1 represents diseased group; j=2 represents non-diseased
> group; nij represents the number in group; nij represents the
> probability of a positive test result in group j
>
> The model is based on the ordinal logistic regression proposed by
> McCullagh and takes the form: logit (nij) =(thetai+alphai*disij)*
> exp(-beta*disij)
> where disij represents the "true" disease status (coded as -0.5
> for the non-diseased and 0.5 for the diseased).
> thetai (threshold parameter) and alphaI (accuracy measure) are
modeled
> as random effects while beta(modeling dependence of accuracy on
> threshold) is a fixed effect.
>
> When beta= 0, the model reduces to a logistic regression model and
> thetai is estimated by (logit(tpri) + logit(fpri))/2 ( = Si/2)
> alphai is estimated by logit (tpri) -logit (fpri) ( = Di)
>
> Study level covariates may be added to explore associations with
> threshold and/or accuracy and/or SROC shape
>
> LEVEL 2
> The random effects are assumed to be independent and normally
> distributed:
>
> thetai ~ N(omega, tau-squared ); alphai ~ N(lamda, tau-squared )
>
> The SROC curve is computed using
> E (tpr) = invlogit [logit (fpr) exp (- beta+ lamda* exp (-0.5 lamda]
> for chosen values of fpr
>
> When beta= 0, theta provides a global estimate of the expected test
> accuracy (lnDOR) and the resulting SROC is symmetric.
>
> The expected tpr is given by 1/[1+exp(-(omega+0.5*lamda)*exp(-
> 0.5*beta))]
> The expected fpr is given by 1/[1+exp(-(omega-0.5*lamda)*exp(-
> 0.5*beta))]
>
>
>
> How may this be modeled using gllamm?
> I know how to model the expression logit n=thetai+alphai*disij
> However, I am not sure how to include the scale parameter so thatthe
> above is multiplied by exp(betai*disij ) .
>
> Thanks
> Ben Dwamena
>
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