loglik: Wrapper to the Fortran subroutines computing the log-likelihood

Description

Log-likelihood of hlme, lcmm, multlcmm, Jointlcmm and mpjlcmm models. The argument's specification is not straightforward, so these functions are usually not directly used.

Usage

loglikhlme(
  b,
  Y0,
  X0,
  prior0,
  pprior0,
  idprob0,
  idea0,
  idg0,
  idcor0,
  ns0,
  ng0,
  nv0,
  nobs0,
  nea0,
  nmes0,
  idiag0,
  nwg0,
  ncor0,
  npm0,
  fix0,
  nfix0,
  bfix0
)
logliklcmm(
  b,
  Y0,
  X0,
  prior0,
  pprior0,
  idprob0,
  idea0,
  idg0,
  idcor0,
  ns0,
  ng0,
  nv0,
  nobs0,
  nea0,
  nmes0,
  idiag0,
  nwg0,
  ncor0,
  npm0,
  epsY0,
  idlink0,
  nbzitr0,
  zitr0,
  minY0,
  maxY0,
  ide0,
  fix0,
  nfix0,
  bfix0
)
loglikmultlcmm(
  b,
  Y0,
  X0,
  prior0,
  pprior0,
  idprob0,
  idea0,
  idg0,
  idcor0,
  idcontr0,
  ny0,
  ns0,
  ng0,
  nv0,
  nobs0,
  nea0,
  nmes0,
  idiag0,
  nwg0,
  ncor0,
  nalea0,
  npm0,
  epsY0,
  idlink0,
  nbzitr0,
  zitr0,
  uniqueY0,
  indiceY0,
  nvalSPLORD0,
  fix0,
  nfix0,
  bfix0,
  methInteg0,
  nMC0,
  dimMC0,
  seqMC0,
  chol0
)
loglikJointlcmm(
  b,
  Y0,
  X0,
  prior0,
  pprior0,
  tentr0,
  tevt0,
  devt0,
  ind_survint0,
  idprob0,
  idea0,
  idg0,
  idcor0,
  idcom0,
  idspecif0,
  idtdv0,
  idlink0,
  epsY0,
  nbzitr0,
  zitr0,
  uniqueY0,
  nvalSPL0,
  indiceY0,
  typrisq0,
  risqcom0,
  nz0,
  zi0,
  ns0,
  ng0,
  nv0,
  nobs0,
  nmes0,
  nbevt0,
  nea0,
  nwg0,
  ncor0,
  idiag0,
  idtrunc0,
  logspecif0,
  npm0,
  fix0,
  nfix0,
  bfix0
)
loglikmpjlcmm(
  b,
  K0,
  ny0,
  nbevt0,
  ng0,
  ns0,
  Y0,
  nobs0,
  X0,
  nv0,
  Xns0,
  nv20,
  prior0,
  Tentr0,
  Tevt0,
  Devt0,
  ind_survint0,
  idnv0,
  idnv20,
  idspecif0,
  idlink0,
  epsY0,
  nbzitr0,
  zitr0,
  uniqueY0,
  nvalSPL0,
  indiceY0,
  typrisq0,
  risqcom0,
  nz0,
  zi0,
  nmes0,
  nea0,
  nw0,
  ncor0,
  nalea0,
  idiag0,
  idtrunc0,
  logspecif0,
  npm0,
  fix0,
  contrainte0,
  nfix0,
  bfix0
)

Value

the log-likelihood

Arguments

b: the vector of estimated parameters (length npm0)
Y0: the observed values of the outcome(s) (length nobs0)
X0: the observed values of all covariates included in the model (dim nob0 * nv0)
prior0: the prior latent class (length ns0)
pprior0: the prior probabilty of each latent class (dim ns0 * ng0)
idprob0: indicator of presence in the class membership submodel (length nv0)
idea0: indicator of presence in the random part of the longitudinal submodel (length nv0)
idg0: indicator of presence in the fixed part of the longitudinal submodel (length nv0)
idcor0: indicator of presence in the correlation part of the longitudinal submodel (length nv0)
ns0: number of subjects
ng0: number of latent classes
nv0: number of covariates
nobs0: number of observations
nea0: number of random effects
nmes0: number of mesures for each subject (length ns0 or dom ns0*ny0)
idiag0: indicator of diagonal variance matrix of the random effects
nwg0: number of parameters for proportional random effects over latent classes
ncor0: number of parameters for the correlation
npm0: total number of parameters
fix0: indicator of non estimated parameter (length npm0+nfix0)
nfix0: number of non estimated parameters
bfix0: vector of non estimated parameters
epsY0: epsY values for Beta transformations
idlink0: type of transformation
nbzitr0: number of nodes for the transformations
zitr0: nodes for the transformations
minY0: minimum value for the longitudinal outcome
maxY0: maximum value for the longitudinal outcome
ide0: indicator of observed values for ordinal outcomes
idcontr0: indicator of presence as contrast in the fixed part of the longitudinal submodel (length nv0)
ny0: number of longitudinal outcomes
nalea0: number of parameters f the outcome specific random effect
uniqueY0: unique values of the longitudinal outcomes
indiceY0: correspondance between Y0 and uniqueY0
nvalSPLORD0: number of unique values for outcomes modeled with splines transformations or as ordinal outcome
methInteg0: type of integration
nMC0: number of nodes for Monte Carlo integration
dimMC0: dimension of the integration
seqMC0: sequence of integration nodes
chol0: indicator of Cholesky parameterization
tentr0: entry time for the survival submodel
tevt0: event time for the survival submodel
devt0: indicator of event for the survival submodel
ind_survint0: indicator of risk change
idcom0: indicator of presence in the survival submodel with common effect
idspecif0: indicator of presence in the survival submodel with cause-specific or class specific effect
idtdv0: indicator of 'TimeDepVar' covariate
nvalSPL0: number of unique values for outcomes modeled with splines transformations
typrisq0: type of baseline risk
risqcom0: specification of baseline risk across latent classes
nz0: number of nodes for the baseline
zi0: nodes for the baseline
nbevt0: number of events
idtrunc0: indicator of left truncation
logspecif0: indicator of logarithm parameterization
K0: number of latent processes
Xns0: the observed values of the covariates included in the survival submodel (dim ns0*nv20)
nv20: number of covariates in Xns0
Tentr0: entry time for the survival submodel (length ns0)
Tevt0: event time for the survival submodel (length ns0)
Devt0: indicator of event for the survival submodel (length ns0)
idnv0: indicator of presence in each subpart of the longitudinal models (length 4*sum(nv0))
idnv20: indicator of presence in each subpart of the survival models (length 3*nv20)
nw0: number of parameters for proportional random effects over latent classes
contrainte0: type of identifiability constraints

Author

Cecile Proust-Lima, Viviane Philipps