(A) WinBUGS Program 

A WinBUGS program to fit a Corrected Ordinal Logistic Model to
the Signal Tandmobiel® study. There are two models arkov chain:-

    - Main Data Model       : Sampling a Markov chain pertaining 
                              to the regression parameters using 
                              correction term sampled from the
                              calibration model   
                              
    - Calibration Data Model: A Markov chain Sampling the correction
                              terms using the calibration data
                              
The Wibugs porgram '.odc' file  can be obtained by writing an e-mail to
emmanuel.lesaffre@med.kuleuven.ac.be

model
 { 
  # MAIN DATA MODEL
  for(i in 1:N)
   { 
    age2[i] <- age[i]-mean(age[]) # center age
    mu[i]   <- beta[1]*xcen[i]    + beta[2]*ycen[i] +
               beta[3]*gender[i]  + beta[4]*age2[i] + bs[schocode[i]]                  
            
  # Cumulative piability of  response <= r
     for(r in 1 : Ncut) { logit(F[i, r]) <- (lambda[r] - mu[i] ) }

  # Probability of  response = r
     Q[i,1]<-F[i, 1]        ;  Q[i,2]<-F[i, 2]-F[i, 1];
     Q[i,3]<-F[i, 3]-F[i, 2];  Q[i,4]<-1-      F[i, 3]; 

  # Corrected  piability of  response <= j
    for(a in 1:4)
    {
     Pr[i,a]<- phi.cut[examiner[i],a,1]*Q[i,1] +
               phi.cut[examiner[i],a,2]*Q[i,2] +
               phi.cut[examiner[i],a,3]*Q[i,3] +
               phi.cut[examiner[i],a,4]*Q[i,4]
    }
    dmf_cat[i] ~ dcat(Pr[i, ])
  }# end i
  # random school  and  examienr effects
     for(j in 1:Ns) { bs[j] ~ dnorm(0.0 ,tau) }

  # ordered cut points for underlying continuous latent variable  
    lambda[1] ~ dnorm(0, 1.0E-06)I(         ,lambda[2])
    lambda[2] ~ dnorm(0, 1.0E-06)I(lambda[1],lambda[3])
    lambda[3] ~ dnorm(0, 1.0E-06)I(lambda[2],) 

  # vague prior on regression and precision parameters
  for(k in 1:4) {   beta[k ]~ dnorm(0, 1.0E-06) }
                       tau  ~ dgamma(0.01, 0.01)
		     sigma2 <- 1 / tau 
 # Bayesian  p-values
 # if mean(paramater)< 0 then pvalue=1-pvalue else pvalue=pvalue
    pvalue[1]<- 1-step(lambda[1]); pvalue[2]<- 1-step(lambda[2]);
    pvalue[3]<- 1-step(lambda[3]); pvalue[4]<- 1-step(beta[1])  ;
    pvalue[5]<- 1-step(beta[2])  ; pvalue[6]<- 1-step(beta[3])  ;
    pvalue[7]<- 1-step(beta[4])  ; pvalue[8]<- 1-step(sigma2)   ;
		
# CALIBRATION DATA
# Loop over cabibration exercise   
 for(j in 1:16){ 
  for(a in 1:4){
   M[j,a,1:4] ~ dmulti(tphi[j,a,1:4], m[j,a])
   m[j,a]    <- sum(M[j,a,1:4])    
   for(b in 1:4){
     tphi[j,a,b] <- w[j]*equals(a,b)+ (1-w[j])*pi[a,b]
     phi[j,a,b]  <- tphi[j,b,a]
                }}} 
 # gold standard
  for(a in 1:4)  { 
     for(b in 1:4) {
      phi[17,a,b]  <- 1*equals(a,b) }}
 # prior for w
   for(j in 1:16){
            w[j] ~ dbeta(1,1) }
 # a ddirch prior for pi using ratio of gamma trick 
   for(a in 1:4)  { 
     for(b in 1:4) {  
     pi[a,b] <- delta[a,b]/sum(delta[a,])
     delta[a,b] ~ dgamma(1,1)
         }} 
 # use of 'cut' to ensure indepence of phi from main study parms
   for(j in 1:17){D
    for(a in 1:4)  { 
      for(b in 1:4) {
        phi.cut[j,a,b]  <- cut(phi[j,a,b]) 
  }}}  
}# end model


(B) DATA SET 

A subset of 435 children, about 10% of the complete dataset. 
The complete dataset can be obtained by writing an e-mail to
emmanuel.lesaffre@med.kuleuven.ac.be

The dataset is given in LIST format, a common format of WinBUGS input dataset.

list(
N=435, Ns=150, Ncut=3, 
examiner=c(12, 7, 9, 15, 13, 5, 4, 14, 6, 6, 8, 15, 2, 7, 2, 1, 9, 7, 6, 5, 15, 14, 13, 12, 5, 2, 6, 4, 15, 6, 6, 14, 1, 6, 10, 15, 1, 9, 11, 15, 3, 9, 9, 8, 6, 6, 7, 9, 6, 10, 11, 4, 7, 15, 15, 12, 15, 16, 2, 4, 1, 15, 11, 2, 6, 16, 11, 15, 7, 2, 2, 13, 15, 12, 10, 15, 9, 4, 16, 15, 10, 6, 4, 10, 8, 7, 2, 2, 15, 2, 5, 4, 16, 9, 7, 2, 2, 9, 1, 5, 15, 6, 1, 10, 6, 15, 13, 1, 11, 10, 15, 10, 16, 16, 1, 2, 13, 14, 5, 8, 16, 15, 8, 14, 13, 15, 6, 6, 6, 2, 1, 5, 14, 7, 13, 15, 12, 6, 11, 15, 2, 6, 10, 7, 1, 9, 6, 16, 5, 16, 1, 15, 1, 15, 2, 8, 15, 15, 13, 5, 15, 16, 11, 16, 4, 11, 11, 15, 10, 9, 1, 15, 3, 7, 6, 2, 6, 2, 4, 16, 7, 6, 6, 12, 14, 5, 6, 16, 2, 6, 8, 4, 13, 8, 15, 15, 14, 15, 2, 4, 12, 11, 2, 5, 15, 3, 8, 5, 7, 14, 12, 1, 13, 6, 7, 13, 13, 14, 2, 6, 16, 5, 3, 4, 15, 2, 16, 6, 8, 15, 15, 17, 8, 4, 2, 15, 6, 15, 9, 6, 1, 6, 6, 15, 12, 4, 3, 6, 6, 3, 13, 12, 5, 10, 15, 4, 11, 3, 11, 10, 4, 14, 5, 15, 1, 15, 5, 2, 16, 15, 3, 2, 16, 15, 15, 6, 15, 15, 11, 15, 8, 15, 6, 16, 11, 13, 6, 15, 9, 15, 4, 13, 11, 8, 9, 6, 16, 15, 1, 9, 15, 10, 1, 13, 16, 11, 4, 15, 11, 13, 11, 15, 2, 3, 5, 12, 16, 6, 12, 1, 2, 11, 4, 6, 15, 9, 13, 15, 2, 2, 6, 8, 7, 4, 14, 15, 5, 16, 7, 4, 11, 3, 1, 10, 16, 2, 12, 2, 4, 7, 11, 15, 15, 6, 14, 12, 2, 1, 4, 11, 16, 13, 15, 15, 4, 6, 13, 10, 1, 14, 13, 4, 8, 4, 16, 11, 15, 1, 14, 15, 15, 2, 6, 10, 3, 15, 15, 3, 5, 2, 15, 2, 11, 1, 7, 15, 15, 7, 11, 4, 8, 6, 10, 3, 8, 11, 1, 11, 15, 3, 9, 11, 1, 4, 8, 6, 13, 16, 17, 6, 7, 12, 4, 7, 15, 10, 12, 2, 7, 15, 15, 6, 16, 11, 15), 
age     =c(7.08008214, 7.26899384, 7.87405886, 7.37029432, 6.99520876, 6.74058864, 6.84462697, 7.20328542, 7.18685832, 7.51813826, 7.40314853, 6.51334702, 7.09924709, 6.86652977, 7.19507187, 6.50239562, 6.88843258, 7.13483915, 7.23066393, 7.16221766, 7.26899384, 7.55646817, 6.68035592, 7.10198494, 6.57631759, 6.93497604, 7.06913073, 6.85557837, 7.16495551, 6.58179329, 7.50171116, 6.45859001, 6.49965777, 6.85010267, 6.94592745, 6.61190965, 6.94045175, 6.85010267, 6.91033539, 7.12936345, 7.33470226, 6.93771389, 7.00342231, 6.64202601, 6.81724846, 7.17590691, 6.86926762, 7.1321013, 6.80903491, 6.85557837, 7.49075975, 7.43600274, 6.80903491, 7.58658453, 7.24709103, 7.20328542, 7.11019849, 7.87679671, 7.08555784, 6.99794661, 7.56194387, 7.70431211, 6.7816564, 7.51266256, 6.4202601, 7.71252567, 6.9596167, 6.48049281, 7.57015743, 7.29637235, 7.01437372, 7.62765229, 6.39835729, 7.06913073, 7.70431211, 7.41409993, 7.1430527, 7.07460643, 7.68240931, 7.62217659, 6.45311431, 6.65023956, 7.37577002, 7.2991102, 7.17043121, 6.84736482, 6.72416153, 6.37919233, 6.99520876, 7.57563313, 6.59000684, 7.06365503, 7.18412047, 7.31279945, 6.83093771, 7.49897331, 7.43052704, 7.78644764, 7.18685832, 6.78986995, 6.9486653, 6.7871321, 6.94592745, 7.03353867, 7.4880219, 6.81998631, 6.88569473, 7.08281999, 6.69404517, 7.45790554, 6.34633812, 6.91854894, 6.81998631, 7.76454483, 6.57905544, 6.66392882, 7.01711157, 6.83915127, 6.32169747, 7.37303217, 7.51540041, 7.39767283, 7.58110883, 7.2936345, 7.40588638, 6.63107461, 7.39219713, 7.21423682, 6.93223819, 7.89048597, 7.2881588, 6.82272416, 7.07186858, 6.41752225, 6.53798768, 6.86652977, 7.41136208, 7.2936345, 7.74537988, 7.19507187, 7.8384668, 6.35455168, 6.94045175, 6.93771389, 6.68856947, 7.51813826, 6.88295688, 7.42231348, 6.46680356, 7.2881588, 7.23887748, 7.70431211, 7.33744011, 6.94045175, 6.93497604, 6.16016427, 7.24435318, 6.48596851, 7.17316906, 6.72689938, 6.93771389, 7.15947981, 7.17316906, 7.64681725, 7.06365503, 6.57357974, 7.19507187, 6.97878166, 7.1266256, 6.34907598, 6.93497604, 7.19507187, 7.54004107, 6.86379192, 7.15126626, 7.31279945, 7.28268309, 6.47501711, 6.32717317, 7.03353867, 6.76249144, 7.33196441, 7.89048597, 7.85763176, 6.91033539, 6.87748118, 6.78439425, 7.29637235, 7.14579055, 6.86926762, 7.35934292, 7.03627652, 7.70157426, 7.24161533, 7.24709103, 7.23613963, 7.27446954, 7.46338125, 7.00616016, 7.44969199, 6.99247091, 7.06091718, 6.93223819, 6.954141, 6.94045175, 6.72142368, 6.56262834, 6.50787132, 6.37645448, 7.1321013, 7.09103354, 6.56262834, 6.76249144, 6.47775496, 7.01163587, 6.51334702, 6.770705, 7.58932238, 6.86926762, 6.52703628, 6.95687885, 7.05544148, 7.47433265, 7.03353867, 7.37577002, 7.17590691, 7.26351814, 7.35386721, 6.83367556, 7.6495551, 7.25530459, 6.61190965, 7.67145791, 6.99247091, 7.18685832, 6.94045175, 7.49623546, 6.49418207, 7.61943874, 6.64750171, 7.55646817, 7.1321013, 7.36208077, 7.2991102, 7.07460643, 7.57289528, 6.90485969, 6.89664613, 7.04722793, 6.74880219, 6.77344285, 7.72073922, 7.16495551, 7.09924709, 6.35455168, 7.01711157, 7.66872005, 7.65776865, 6.64476386, 6.83641342, 7.70431211, 7.20602327, 6.70773443, 7.18412047, 7.26899384, 6.86926762, 6.60643395, 7.6495551, 7.43874059, 6.90759754, 7.28268309, 7.20328542, 7.52361396, 6.96235455, 7.11841205, 7.41957563, 7.49075975, 6.69678303, 7.46885695, 6.91854894, 7.60574949, 6.92128679, 6.88843258, 7.6659822, 6.85557837, 7.00342231, 7.37577002, 7.09924709, 7.93155373, 7.18412047, 7.16495551, 7.03627652, 7.14852841, 7.27446954, 6.29979466, 7.08008214, 7.4880219, 6.47227926, 7.38398357, 6.46406571, 7.23340178, 7.75906913, 7.60027379, 7.00068446, 6.91033539, 6.42847365, 6.72689938, 6.78439425, 7.32648871, 6.22587269, 7.15400411, 7.29637235, 6.9705681, 7.6440794, 6.54346338, 7.37850787, 7.4825462, 6.81177276, 7.20876112, 7.34017796, 7.95345654, 7.00889802, 6.52156057, 6.65023956, 6.86105407, 7.3100616, 6.88021903, 7.24435318, 6.61190965, 7.17864476, 7.50992471, 7.1321013, 7.37577002, 6.68035592, 7.24982888, 6.954141, 7.32922656, 7.93429158, 7.60301164, 6.92950034, 7.52908966, 7.32922656, 6.95687885, 7.50992471, 7.33470226, 6.93771389, 7.51813826, 7.36208077, 6.99520876, 7.29637235, 6.35181383, 6.89664613, 7.07734428, 7.72073922, 6.58179329, 7.12388775, 6.72689938, 6.55989049, 7.00616016, 6.68309377, 7.11019849, 6.93223819, 7.04722793, 6.74332649, 7.1211499, 6.97330595, 6.96235455, 6.46132786, 6.50513347, 7.8110883, 6.93223819, 7.27173169, 6.7652293, 6.7816564, 6.90759754, 6.38466804, 6.32169747, 7.37303217, 7.07734428, 6.97604381, 7.22792608, 7.33470226, 7.42231348, 6.31895962, 6.88021903, 7.41136208, 7.08829569, 7.04175222, 7.24161533, 6.59548255, 6.73785079, 7.137577, 6.89390828, 7.77823409, 7.74264203, 7.816564, 7.6495551, 7.137577, 7.62491444, 6.91854894, 6.74880219, 6.46954141, 6.81998631, 6.69678303, 6.91854894, 6.48323066, 6.40383299, 7.22792608, 7.4770705, 6.81724846, 6.37097878, 6.53798768, 7.26078029, 7.08281999, 7.6440794, 7.26625599, 7.35112936, 7.36481862, 6.83641342, 7.80013689, 6.85284052, 7.80561259, 6.90485969, 7.10198494, 7.06639288, 6.37097878, 7.35660507, 6.68583162, 6.64202601, 7.83572895, 7.6605065, 6.58453114, 7.18412047, 7.28542094, 7.45516769), 
gender  =c(0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1), 
xcen    =c(-1.9219479, -1.9219479, 0.17931588, 1.72102211, 0.28175057, 0.27263838, 0.28175057, -0.670646, -0.5384439, -1.1940691, -0.8405886, -1.443987, 0.72198563, -1.9219479, 1.7064039, 0.34071773, -0.5384439, -1.6383525, -0.2807068, 0.27263838, 1.03369088, -1.443987, 0.17383375, -1.5391286, 1.4863785, 1.7064039, 0.26162659, 0.78686821, 1.72102211, -1.5571076, -0.5972507, -1.4277329, -0.0894482, -0.2387267, 1.24285223, 0.44634756, -0.0894482, -0.5384439, -0.7747624, -0.7747624, 0.2772178, -0.5384439, -0.5384439, 0.26162659, -0.3431117, 0.19658054, -1.9219479, -0.3127967, -0.5972507, 0.36464866, 0.36464866, 1.01608353, -1.5391286, 1.03369088, 1.17691305, -0.7747624, 0.17383375, 0.08434228, 1.31781917, -0.0583625, 0.09966277, 1.24285223, -0.0684191, 1.7064039, -0.2387267, 1.15600264, -1.3704283, 0.86672071, -0.7747624, 1.31781917, 1.41354681, 0.28175057, -1.443987, -1.1244888, 1.24285223, 0.17383375, -0.5384439, 0.08434228, 0.8895256, 0.79980545, 0.09002454, 0.26162659, 0.08434228, 0.2772178, -1.9244366, -1.241974, 1.34310432, 1.6504922, -0.412351, 0.72198563, 0.86672071, 0.08434228, 1.15600264, 0.09966277, -1.9219479, 1.24285223, 1.7064039, 0.17931588, 0.08434228, 1.34310432, 0.22503794, 0.26162659, 0.17553137, 0.36464866, -0.6527038, 1.34310432, 0.91630527, 0.34071773, -0.6552107, 0.36464866, 0.44634756, 0.36464866, 1.06290592, 0.4698561, 0.86236234, 1.30254427, -0.0181246, -1.4277329, 0.86672071, -1.1340611, 0.4698561, 1.17691305, -0.8405886, -0.670646, 0.28175057, -1.443987, -1.5571076, -0.2807068, -0.3431117, 1.24285223, 0.08434228, 1.34310432, -1.3774618, -1.9219479, 0.08434228, 1.17691305, -1.9244366, -0.7747624, -1.241974, -0.7747624, 1.41354681, -0.5384439, 0.6303214, -1.241974, 0.08434228, 0.09966277, -0.5972507, 0.08434228, 0.86672071, 0.8895256, 0.08434228, 1.24285223, 0.08434228, 1.17691305, 1.30254427, -1.5571076, 1.24285223, -1.443987, 0.91630527, 0.86672071, 1.34310432, 0.36093265, -0.7747624, 0.4698561, 0.78686821, -1.6147936, -1.3704283, -0.7747624, 0.2772178, -0.5384439, 0.17553137, 1.03369088, -0.5972507, -2.1610453, -0.5384439, 1.41354681, -0.5972507, 1.30254427, -0.0583625, 1.15600264, -1.9219479, -1.5571076, -1.1940691, -1.241974, -1.4277329, 1.4863785, 0.19658054, 0.8895256, 1.41354681, -0.5972507, -0.2431152, 0.08434228, 0.28175057, -0.2431152, 1.54464023, 1.17691305, -0.7747624, 0.22503794, 1.6504922, 0.08434228, -1.4609936, -0.7747624, 1.31781917, 1.34310432, 1.17691305, 0.59193246, -1.9244366, 1.4863785, -1.241974, -0.670646, -1.5391286, 0.34071773, 0.7642292, 0.19658054, -1.9219479, 0.91630527, 0.91630527, -1.1176607, 1.30254427, -0.2387267, 1.15600264, 1.4863785, -0.4539371, 0.08434228, 0.17383375, 1.17920878, 0.8895256, -0.5972507, 0.26162659, 1.24285223, 1.34310432, 0.01346966, -1.0494134, 0.78686821, 1.17920878, -0.7747624, -0.2807068, 1.34310432, 0.17931588, 0.19658054, 0.09966277, 0.19658054, -0.3431117, 1.7064039, -1.4609936, 0.28175057, 0.77487195, -0.3431117, -1.5571076, -0.5972507, 0.17383375, -1.9219479, 0.27263838, 1.15420052, 0.86672071, 0.08434228, -1.241974, -0.4539371, -0.7747624, 0.2772178, 0.08434228, -1.4277329, 0.27263838, 0.09966277, 0.08434228, -1.443987, 0.86672071, 1.7064039, 1.34310432, 1.7064039, 0.59193246, 0.79980545, 0.8895256, 1.54464023, 0.79980545, -1.1940691, 0.17383375, 0.86672071, -1.241974, 1.7064039, -1.1340611, -0.412351, -0.3431117, 1.34310432, -1.3704283, 0.08434228, -0.8405886, 1.34310432, 0.17931588, 0.22503794, 0.08434228, 0.7642292, -1.5391286, -0.2431152, -0.1170164, 0.19658054, 1.34310432, 1.72102211, 0.08434228, -0.5384439, 1.34310432, 0.6303214, 0.17553137, 0.08434228, 1.91309976, -1.3704283, 0.08434228, 1.34310432, -1.7378458, 0.17383375, -1.7378458, 1.03369088, 1.41354681, -0.4539371, 1.4863785, -1.1244888, 0.08434228, -1.5571076, -1.9244366, 0.60943028, 1.30254427, -1.6147936, 0.08434228, 0.26162659, 1.17691305, 0.17931588, 0.70320754, 1.17691305, 1.30254427, 1.31781917, -0.7747624, -1.1340611, -0.7432247, 0.78686821, -1.3774618, -0.7747624, 1.34310432, 0.36093265, -1.443987, 0.28175057, -0.7747624, 0.59193246, 0.34071773, 1.24285223, 0.69773568, 1.30254427, -1.241974, 0.72198563, 1.01608353, -0.7747624, -1.6147936, 0.44634756, 0.44634756, -0.7747624, -0.7747624, -0.7747624, 1.6504922, 0.34071773, 0.08434228, -1.3704283, -0.0273197, 0.28175057, -1.443987, 0.22503794, 0.78686821, 0.19658054, 0.28175057, 1.15420052, -0.0894482, -1.1176607, 0.91630527, 0.08434228, -1.0494134, 0.78686821, 0.69773568, -1.3704283, 0.86672071, 0.17553137, -1.4277329, -1.443987, 0.44634756, 1.41354681, -1.5571076, 0.09002454, 0.59193246, 1.24285223, 0.22503794, 0.24060299, 0.86672071, 1.6504922, 0.44634756, 1.7064039, -1.7378458, 0.09966277, -1.5391286, -0.412351, 1.03369088, -0.7432247, -1.5391286, 1.01608353, -1.9244366, 0.26162659, 0.2772178, -0.2387267, -1.5571076, -0.6552107, 0.08434228, -1.3704283, 1.24285223, 0.59193246, -0.5384439, -1.6147936, 0.60943028, 0.78686821, -0.8405886, -0.6527038, -0.0181246, 0.36093265, 0.01346966, -0.2807068, -0.7747624, -1.241974, 0.28175057, -0.7747624, -0.7747624, 0.09002454, -1.5391286, 1.34310432, -1.241974, 0.17383375, -0.7747624, 0.19658054, 0.36093265, -1.241974, -0.7747624), 
ycen    =c(-1.134696, -1.134696, 0.46695154, -0.202989, 0.26465061, -0.8022717, 0.26465061, -0.6694241, -1.6404937, -0.9883439, -0.3843434, 1.18274467, 1.26521713, -1.134696, -0.0015344, -0.6878682, -1.6404937, 1.35781312, -0.1421793, -0.8022717, 1.74839098, 1.18274467, 0.66157603, -1.5530081, -0.8356832, -0.0015344, 1.58252876, -0.7891998, -0.202989, 0.47204151, 0.30322227, -0.9591754, -1.2035103, 0.7073776, 0.109489, -0.5093238, -1.2035103, -1.6404937, 0.14747808, 0.14747808, 1.33460205, -1.6404937, -1.6404937, 1.58252876, 1.04037403, -0.1148899, -1.134696, -0.6280037, 0.30322227, 2.12882764, 2.12882764, -0.2861792, -1.5530081, 1.74839098, -0.3025594, 0.14747808, 0.66157603, 1.31434113, -0.995043, 0.26107563, -1.1630531, 0.109489, 1.11434781, -0.0015344, 0.7073776, 0.74272877, -1.5793305, -1.3935942, 0.14747808, -0.995043, 0.56707771, 0.26465061, 1.18274467, -1.3274744, 0.109489, 0.66157603, -1.6404937, 1.31434113, -0.2859873, 2.31183345, 1.72142396, 1.58252876, 1.31434113, 1.33460205, 0.0181838, -1.5615644, -0.6644206, -1.0849611, -1.0101967, 1.26521713, -1.3935942, 1.31434113, 0.74272877, -1.1630531, -1.134696, 0.109489, -0.0015344, 0.46695154, 1.31434113, -0.6644206, 2.1888502, 1.58252876, -0.7466483, 2.12882764, -0.0523183, -0.6644206, 0.18854087, -0.6878682, -1.107657, 2.12882764, -0.5093238, 2.12882764, -1.3405999, 0.37172026, -1.1378194, 1.09514215, 0.11947229, -0.9591754, -1.3935942, 0.1493624, 0.37172026, -0.3025594, -0.3843434, -0.6694241, 0.26465061, 1.18274467, 0.47204151, -0.1421793, 1.04037403, 0.109489, 1.31434113, -0.6644206, -0.2572986, -1.134696, 1.31434113, -0.3025594, 0.0181838, 0.14747808, -1.5615644, 0.14747808, 0.56707771, -1.6404937, 2.4007111, -1.5615644, 1.31434113, -1.1630531, 0.30322227, 1.31434113, -1.3935942, -0.2859873, 1.31434113, 0.109489, 1.31434113, -0.3025594, 1.09514215, 0.47204151, 0.109489, 1.18274467, 0.18854087, -1.3935942, -0.6644206, 0.41216844, 0.14747808, 0.37172026, -0.7891998, -1.0438784, -1.5793305, 0.14747808, 1.33460205, -1.6404937, -0.7466483, 1.74839098, 0.30322227, 0.08777276, -1.6404937, 0.56707771, 0.30322227, 1.09514215, 0.26107563, 0.74272877, -1.134696, 0.47204151, -0.9883439, -1.5615644, -0.9591754, -0.8356832, -0.1148899, -0.2859873, 0.56707771, 0.30322227, -0.351084, 1.31434113, 0.26465061, -0.351084, -1.7018423, -0.3025594, 0.14747808, 2.1888502, -1.0849611, 1.31434113, -0.7009411, 0.14747808, -0.995043, -0.6644206, -0.3025594, 0.80565674, 0.0181838, -0.8356832, -1.5615644, -0.6694241, -1.5530081, -0.6878682, 0.01631713, -0.1148899, -1.134696, 0.18854087, 0.18854087, -0.6683423, 1.09514215, 0.7073776, 0.74272877, -0.8356832, 0.46530773, 1.31434113, 0.66157603, -0.7398994, -0.2859873, 0.30322227, 1.58252876, 0.109489, -0.6644206, -0.8627996, -0.3582154, -0.7891998, -0.7398994, 0.14747808, -0.1421793, -0.6644206, 0.46695154, -0.1148899, -1.1630531, -0.1148899, 1.04037403, -0.0015344, -0.7009411, 0.26465061, 0.37401803, 1.04037403, 0.47204151, 0.30322227, 0.66157603, -1.134696, -0.8022717, 0.34518844, -1.3935942, 1.31434113, -1.5615644, 0.46530773, 0.14747808, 1.33460205, 1.31434113, -0.9591754, -0.8022717, -1.1630531, 1.31434113, 1.18274467, -1.3935942, -0.0015344, -0.6644206, -0.0015344, 0.80565674, 2.31183345, -0.2859873, -1.7018423, 2.31183345, -0.9883439, 0.66157603, -1.3935942, -1.5615644, -0.0015344, 0.1493624, -1.0101967, 1.04037403, -0.6644206, -1.5793305, 1.31434113, -0.3843434, -0.6644206, 0.46695154, 2.1888502, 1.31434113, 0.01631713, -1.5530081, -0.351084, -0.8704954, -0.1148899, -0.6644206, -0.202989, 1.31434113, -1.6404937, -0.6644206, 2.4007111, -0.7466483, 1.31434113, -0.0214231, -1.5793305, 1.31434113, -0.6644206, -0.1234588, 0.66157603, -0.1234588, 1.74839098, 0.56707771, 0.46530773, -0.8356832, -1.3274744, 1.31434113, 0.47204151, 0.0181838, -1.3940771, 1.09514215, -1.0438784, 1.31434113, 1.58252876, -0.3025594, 0.46695154, 1.59845413, -0.3025594, 1.09514215, -0.995043, 0.14747808, 0.1493624, -0.4498087, -0.7891998, -0.2572986, 0.14747808, -0.6644206, 0.41216844, 1.18274467, 0.26465061, 0.14747808, 0.80565674, -0.6878682, 0.109489, 0.67502842, 1.09514215, -1.5615644, 1.26521713, -0.2861792, 0.14747808, -1.0438784, -0.5093238, -0.5093238, 0.14747808, 0.14747808, 0.14747808, -1.0849611, -0.6878682, 1.31434113, -1.5793305, -0.2455822, 0.26465061, 1.18274467, 2.1888502, -0.7891998, -0.1148899, 0.26465061, 0.34518844, -1.2035103, -0.6683423, 0.18854087, 1.31434113, -0.3582154, -0.7891998, 0.67502842, -1.5793305, -1.3935942, -0.7466483, -0.9591754, 1.18274467, -0.5093238, 0.56707771, 0.47204151, 1.72142396, 0.80565674, 0.109489, 2.1888502, 0.59535429, -1.3935942, -1.0849611, -0.5093238, -0.0015344, -0.1234588, -1.1630531, -1.5530081, -1.0101967, 1.74839098, -0.4498087, -1.5530081, -0.2861792, 0.0181838, 1.58252876, 1.33460205, 0.7073776, 0.47204151, -1.107657, 1.31434113, -1.5793305, 0.109489, 0.80565674, -1.6404937, -1.0438784, -1.3940771, -0.7891998, -0.3843434, -0.0523183, 0.11947229, 0.41216844, -0.8627996, -0.1421793, 0.14747808, -1.5615644, 0.26465061, 0.14747808, 0.14747808, 1.72142396, -1.5530081, -0.6644206, -1.5615644, 0.66157603, 0.14747808, -0.1148899, 0.41216844, -1.5615644, 0.14747808), 
dmf_cat =c(3, 3, 1, 3, 2, 4, 2, 1, 3, 3, 3, 2, 4, 1, 1, 1, 1, 3, 1, 4, 4, 3, 3, 1, 1, 3, 1, 1, 1, 1, 4, 4, 2, 3, 2, 1, 1, 3, 1, 3, 1, 1, 4, 1, 3, 3, 1, 2, 1, 1, 3, 1, 4, 3, 4, 1, 3, 4, 1, 3, 1, 3, 1, 3, 2, 1, 2, 1, 4, 1, 1, 4, 3, 2, 1, 3, 4, 3, 1, 3, 1, 1, 1, 1, 3, 4, 1, 4, 3, 3, 4, 2, 3, 4, 1, 3, 4, 4, 1, 1, 1, 3, 1, 3, 4, 3, 2, 3, 1, 1, 1, 2, 1, 3, 2, 4, 1, 1, 1, 4, 1, 1, 1, 1, 4, 1, 1, 4, 3, 3, 1, 4, 4, 3, 2, 1, 3, 4, 4, 1, 4, 3, 1, 1, 4, 4, 2, 3, 1, 3, 1, 4, 1, 2, 4, 1, 2, 1, 3, 1, 4, 1, 2, 4, 1, 1, 3, 2, 3, 3, 4, 3, 4, 1, 3, 1, 2, 4, 3, 4, 4, 3, 2, 1, 4, 4, 2, 3, 1, 1, 1, 3, 1, 1, 2, 1, 2, 3, 1, 3, 3, 1, 3, 3, 1, 1, 1, 3, 4, 4, 3, 4, 3, 4, 3, 1, 1, 1, 3, 1, 4, 1, 2, 1, 1, 4, 3, 1, 4, 1, 1, 2, 3, 3, 3, 1, 1, 3, 2, 1, 3, 3, 1, 1, 1, 1, 4, 1, 1, 3, 3, 1, 1, 1, 2, 1, 1, 4, 1, 1, 1, 1, 3, 1, 1, 2, 1, 4, 3, 1, 3, 3, 3, 4, 4, 2, 1, 4, 1, 3, 1, 4, 3, 4, 4, 4, 1, 3, 3, 4, 3, 1, 1, 4, 4, 4, 2, 3, 4, 1, 4, 3, 1, 1, 4, 1, 4, 1, 4, 1, 4, 2, 1, 4, 1, 3, 3, 1, 1, 4, 4, 2, 3, 1, 4, 3, 2, 1, 3, 1, 1, 1, 4, 3, 4, 3, 3, 4, 1, 1, 2, 4, 2, 1, 4, 4, 2, 4, 2, 1, 4, 1, 1, 1, 1, 2, 3, 1, 1, 1, 1, 1, 1, 1, 4, 4, 1, 2, 3, 1, 1, 1, 4, 1, 1, 1, 1, 1, 1, 3, 1, 4, 3, 1, 1, 3, 3, 3, 3, 3, 4, 4, 1, 1, 3, 4, 4, 2, 1, 1, 3, 1, 3, 1, 4, 2, 1, 1, 1, 1, 2, 1, 1, 3, 1, 3, 1, 4, 2, 1, 1, 1, 1, 1, 2, 4, 3, 1, 1, 4, 4, 3, 1, 1, 3), 
schocode=c(117, 115, 37, 80, 38, 10, 38, 148, 141, 108, 147, 90, 22, 114, 79, 12, 143, 95, 137, 10, 28, 93, 41, 119, 75, 77, 48, 62, 80, 92, 131, 110, 5, 133, 72, 52, 5, 143, 122, 121, 46, 143, 143, 48, 136, 43, 114, 139, 131, 50, 51, 57, 118, 28, 69, 124, 42, 40, 71, 45, 4, 74, 134, 77, 133, 33, 96, 59, 123, 71, 87, 38, 90, 100, 72, 42, 143, 15, 55, 31, 49, 48, 15, 46, 101, 99, 66, 82, 142, 22, 58, 15, 34, 3, 114, 73, 78, 37, 18, 66, 47, 48, 8, 50, 130, 67, 32, 12, 144, 50, 52, 50, 63, 39, 61, 84, 44, 110, 58, 150, 39, 69, 147, 148, 38, 90, 92, 137, 136, 73, 18, 66, 107, 116, 14, 69, 103, 128, 97, 128, 87, 140, 26, 98, 18, 3, 131, 40, 58, 55, 18, 74, 18, 69, 83, 91, 74, 90, 32, 58, 65, 35, 125, 39, 62, 112, 96, 128, 46, 143, 8, 28, 131, 106, 140, 86, 131, 84, 45, 33, 115, 92, 109, 97, 110, 75, 43, 54, 86, 131, 138, 17, 38, 138, 81, 69, 127, 47, 82, 15, 111, 125, 71, 66, 69, 24, 101, 75, 99, 148, 119, 12, 20, 43, 115, 32, 32, 149, 83, 133, 33, 75, 135, 16, 42, 68, 54, 131, 48, 74, 67, 7, 145, 62, 68, 128, 137, 65, 37, 43, 4, 43, 136, 78, 111, 38, 21, 136, 92, 131, 41, 117, 9, 89, 59, 17, 97, 135, 122, 46, 15, 110, 9, 2, 18, 90, 58, 77, 64, 78, 25, 30, 55, 81, 29, 108, 42, 59, 97, 78, 150, 142, 136, 64, 96, 14, 147, 65, 37, 47, 15, 20, 120, 138, 6, 43, 64, 80, 18, 143, 65, 26, 8, 13, 76, 96, 17, 65, 105, 41, 105, 28, 86, 135, 75, 100, 40, 92, 102, 60, 85, 112, 16, 48, 69, 37, 27, 69, 84, 70, 128, 150, 146, 62, 107, 128, 66, 35, 94, 38, 125, 23, 12, 72, 19, 83, 97, 22, 56, 123, 113, 53, 53, 128, 126, 124, 82, 12, 16, 96, 11, 38, 90, 47, 62, 43, 38, 88, 5, 149, 32, 17, 145, 62, 19, 96, 59, 8, 110, 90, 53, 86, 92, 49, 24, 74, 47, 36, 58, 82, 52, 77, 105, 1, 118, 142, 28, 146, 120, 56, 104, 48, 46, 132, 91, 144, 18, 96, 74, 25, 143, 112, 60, 62, 147, 130, 44, 35, 7, 137, 129, 97, 38, 129, 128, 49, 119, 66, 98, 42, 121, 43, 35, 97, 121), 
M       = structure(.Data= c(17, 0, 2, 0, 2, 3, 1, 0, 0, 0, 6, 1, 0, 0, 0, 1, 18, 0, 0, 0, 2, 4, 0, 0, 0, 1, 7, 0, 0, 0, 1, 2, 19, 1, 1, 0, 1, 0, 1, 0, 0, 0, 5, 0, 0, 0, 0, 0, 10, 0, 0, 0, 2, 4, 0, 0, 0, 2, 4, 1, 0, 0, 0, 1, 15, 0, 1, 0, 2, 2, 0, 0, 0, 1, 8, 2, 0, 0, 0, 2, 16, 0, 0, 0, 2, 6, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 8, 0, 0, 0, 1, 2, 0, 0, 0, 0, 6, 0, 0, 0, 0, 3, 17, 1, 0, 0, 1, 5, 1, 0, 0, 0, 6, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 2, 0, 0, 0, 0, 3, 21, 0, 0, 0, 0, 5, 0, 0, 0, 0, 7, 0, 0, 0, 0, 2, 10, 0, 0, 0, 1, 1, 1, 0, 0, 0, 3, 0, 0, 0, 0, 3, 15, 1, 0, 0, 1, 2, 2, 0, 0, 0, 6, 0, 0, 0, 0, 3, 16, 0, 1, 0, 2, 3, 1, 0, 0, 0, 5, 3, 0, 0, 0, 1, 15, 1, 1, 0, 2, 1, 1, 0, 0, 0, 5, 0, 0, 0, 0, 3, 20, 1, 1, 0, 0, 1, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 17, 0, 0, 0, 0, 2, 0, 0, 0, 0, 8, 0, 0, 0, 0, 3), .Dim=c(16, 4, 4))
)

(C) INITIAL VALUES

 A list of initial values to the WinBUGS program 
 
 list(lambda=c(-0.64,0.00,2.00), beta=c(0.02,-0.06, 0.03,0.23), tau=4.0,
 delta = structure(.Data = c(3.02821186716995,0.08332666428735359,0.07419299262029873,0.008059025597196226,0.7220556849562841,
 0.535181555851886,0.4604990696278605,0.02300617205313604,0.1444148934672606,0.505300612432072,
 4.08670909051092,0.04405808326675045,0.3454558299063502,0.2997270407843201,0.4014285598400601,
 3.049869944592438),.Dim = c(4,4)),
 w = c(0.1938879064367082,0.3082251959080907,0.3976174116771475,0.08803732369193379,0.04404709753187268,
 0.7224843158451535,0.7511736191436543,0.8425815826480191,0.5713319062379999,0.9232168427893085,
 0.2207114915961449,0.2477630078349058,0.254143242785686,0.6155134597936252,0.4490437400861457,
 0.8766236239575043))
 
 list(lambda=c(-0.04,0.20,1.00), beta=c(0.42, 0.02,-0.02,0.03), tau=1.0,
 delta = structure(.Data = c(5.025892470151376,0.376189965677409,0.4314906083776112,0.00326785186492139,3.160783182533284,
 0.5063280453618199,1.36410224272391,0.1066890874495908,0.016694366165325,1.212781473025998,
 3.228517042341537,0.2261396219807522,0.6316849356275059,0.2196589664263533,0.1841762274831587,
 1.502734413651113),.Dim = c(4,4)),
 w = c(0.4985185265202123,0.6581138639600906,0.6240230599843403,0.4697872739311377,0.3428314759711447,
 0.815977876004412,0.858073598010187,0.6040675245139917,0.4149944014559592,0.9846918331418342,
 0.871645053323193,0.4790513618482073,0.2616102726971218,0.3574161309620325,0.8216315685705765,
 0.9753200882349632))
 
 list(lambda=c(-0.44,0.06,1.17), beta=c(0.22,-0.02,-0.07,0.33), tau=5.3,
 delta = structure(.Data = c(2.285148823675355,0.09358238777369159,0.1126720137121962,0.02843057175894592,1.205595754773291,
 0.4570333392383865,0.4370342509521121,0.02378615541406277,0.03362382019392043,0.7881903297515734,
 2.566635391723692,0.04360489385041454,0.5727426798702359,0.2208080290320477,0.2969754497226734,
 4.50249848710502),.Dim = c(4,4)),
 w = c(0.2194472284196692,0.4669587345272758,0.1674732044719388,0.4719642461236636,0.5094061981439,
 0.7826550957161017,0.950215327064607,0.8271033902778772,0.5516384156111833,0.7957318113967325,
 0.207499036196386,0.1683697445012838,0.08134174117836253,0.5456163601696568,0.6592878055103532,
 0.9010012474486458))
 
 list(lambda=c(-0.24,0.12,1.70), beta=c(0.32,-0.10,-0.17,0.53), tau=8.3,
 delta = structure(.Data = c(4.0935753812725,0.1509334779970691,0.1330368924059832,0.001031601470504925,3.075085918164132,
 3.102663945243298,0.7528712199315544,0.1236791778530205,0.05575985523939865,0.3101724069194222,
 3.046931251802173,0.08375677084698101,0.8602051445145789,0.1950645318840977,0.2504292840862828,
 1.827707768288177),.Dim = c(4,4)),
 w = c(0.1275987155392187,0.4763820197584091,0.2507908691459491,0.2796531754919482,0.4590527265030838,
 0.5751109018218692,0.8096215713606422,0.3230787149272294,0.2653744048515348,0.9414511150025765,
 0.5598714718508113,0.2319782474409413,0.196813457435786,0.4025155050195529,0.02986182100218052,
 0.9415792778862027))
 
 list(lambda=c(-0.84,0.30,0.80), beta=c(0.12,-0.00,-0.10,0.13), tau=2.0,
 delta = structure(.Data = c(3.644660263619611,0.2921465193140186,0.143121075010806,0.02672675190279807,3.047116998301678,
 1.005666957393303,1.765414241011373,0.01758744104180956,0.1906951467334762,1.169252232359629,
 4.019310981455396,0.3546820317386415,0.4117793955590412,0.05536981624253349,0.235458657741816,
 1.385260554300138),.Dim = c(4,4)),
 w = c(0.3906343965181638,0.5998877795018537,0.1957001887772123,0.6168053089730058,0.6955712922913762,
 0.803210346565939,0.519534466760316,0.7181739677229961,0.4220322456283374,0.897622765075753,
 0.3206344229730937,0.7195821381770769,0.2000724265924498,0.5950497149466768,0.3968543724142268,
0.8872930336629012))