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
)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