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st: GLLAMM -- soprobit link


From   George Bouliotis <g.bouliotis@bham.ac.uk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: GLLAMM -- soprobit link
Date   Fri, 17 Feb 2012 12:05:26 +0000

Dear Statalist members,

I am using a dataset of 30 rates evaluating 34 items in an attempt to implement a polytomous ordered probit model with rater-specific measurement errors and thresholds, as it is described in the section 7.12 , book "Multilevel and Longitudinal Modeling Using Stata; Hesketh and Skrondal".

Unfortunately, and despite numerous model modifications (e.g. nip(40), matrices, initial values etc)  , the Newton Raphson algorithm fails to converge although adaptive quadrature is reasonably stable. The usual error message "flat or discontinuous range" emerges any time I use the link "soprobit" whereas full convergence is achieved with "oprobit" links. Please see below some Stata output.

My questions are:
1.	Is there any other trick/way for achieving full convergence? Would it make any difference if I omit a particular rater or raters from the model? Note that I do not have missing values.
2.	Is there any other way for taking rater-specific thresholds with GLLAMM or other command without using "soprobit"? 
3.	Finally, could I base inference on only adaptive quadrature convergence?

Thank you in advance
George


Dr. George Bouliotis

Research Fellow in Biostatistics
MRC-MHTMR (Midland Hub for Trials Methodology Research) 
University of Birmingham


----------------MODEL SPECIFICATION WITH GLLAMM
gllamm   cat rtr1-rtr29, i(item) l(oprob) f(binom) adapt 
estimates store GLLAMM1
**COND.NO: 20.61

gllamm   cat rtr1-rtr29, i(item) l(oprob) f(binom)  
estimates store GLLAMM3
**COND.NO: 26.68

gllamm   cat rtr1-rtr29, i(item) l(oprob) f(binom) adapt iter(0)
estimates store GLLAMM5
***COND.NO: 28.12
*********Adaptive quadrature has not converged


***********
***********
***********


gllamm   cat rtr1-rtr29, i(item) l(soprob) f(binom) adapt 
estimates store GLLAMM2
**COND.NO:1191.92

gllamm   cat rtr1-rtr29, i(item) l(soprob) f(binom)  
estimates store GLLAMM4
**COND.NO: 4706.49

gllamm   cat rtr1-rtr29, i(item) l(soprob) f(binom)  from(M1) skip
estimates store GLLAMM6
***Condition Number = 3273.9524


***********
*********** HETEROSCEDASTIC ERRORS 
***********


eq het: rtr1-rtr16 rtr18-rtr30 //measurement error
gllamm   cat rtr1-rtr16 rtr18-rtr30, i(item) l(soprob) ///
fam(binom) adapt s(het) nip(20) iterate(20) from(M3) skip init

estimates store GLLAMM8
***NO convergence for adaptive ---Con number: NO




***********
*********** THRESHOLDS 
***********
eq thr: rtr1-rtr29 //thresholds
gllamm   cat rtr1-rtr29, i(item) l(oprob)  thres(thr) from(M3) skip  adapt
***Adaptive converged , Newton Raphson NO convergence ---Con number: NO

eq thr: rtr1-rtr16 rtr18-rtr30  //thresholds RATER17 ref-guy
gllamm   cat rtr1-rtr16 rtr18-rtr30 , i(item) l(oprob) f(binom) thres(thr) adapt init
***Adaptive converged , Newton Raphson NO convergence ---Con number: NO

eq thr: rtr1-rtr16 rtr18-rtr30  //thresholds RATER17 ref-guy
gllamm   cat rtr1-rtr16 rtr18-rtr30 , i(item) l(oprob) f(binom) thres(thr) adapt init
***Adaptive converged , Newton Raphson NO convergence ---Con number: NO




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