ctmaAllInvFit: ctmaAllInvFit

View source: R/ctmaAllInvFit.R

ctmaAllInvFitR Documentation

ctmaAllInvFit

Description

Fit a CoTiMA model with all params (drift, T0var, diffusion) invariant across primary studies

Usage

ctmaAllInvFit(
  ctmaInitFit = NULL,
  activeDirectory = NULL,
  activateRPB = FALSE,
  digits = 4,
  drift = drift,
  coresToUse = c(1),
  n.manifest = 0,
  indVarying = FALSE,
  scaleTime = NULL,
  optimize = TRUE,
  priors = FALSE,
  finishsamples = NULL,
  iter = NULL,
  chains = NULL,
  verbose = NULL,
  loadAllInvFit = c(),
  saveAllInvFit = c(),
  silentOverwrite = FALSE,
  customPar = FALSE,
  T0means = 0,
  manifestMeans = 0,
  CoTiMAStanctArgs = NULL,
  lambda = NULL,
  manifestVars = NULL,
  indVaryingT0 = NULL
)

Arguments

ctmaInitFit

ctmaInitFit

activeDirectory

activeDirectory

activateRPB

activateRPB

digits

digits

drift

Labels for drift effects. Have to be either of the type V1toV2 or 0 for effects to be excluded, which is usually not recommended)

coresToUse

coresToUse

n.manifest

Number of manifest variables of the model (if left empty it will assumed to be identical with n.latent).

indVarying

Allows ct intercepts to vary at the individual level (random effects model, accounts for unobserved heterogeneity)

scaleTime

scaleTime

optimize

optimize

priors

priors (FALSE)

finishsamples

finishsamples

iter

iter

chains

chains

verbose

verbose

loadAllInvFit

loadAllInvFit

saveAllInvFit

saveAllInvFit

silentOverwrite

silentOverwrite

customPar

logical. If set TRUE (default) leverages the first pass using priors and ensure that the drift diagonal cannot easily go too negative (helps since ctsem > 3.4)

T0means

Default 0 (assuming standardized variables). Can be assigned labels to estimate them freely.

manifestMeans

Default 0 (assuming standardized variables). Can be assigned labels to estimate them freely.

CoTiMAStanctArgs

parameters that can be set to improve model fitting of the ctStanFit Function

lambda

R-type matrix with pattern of fixed (=1) or free (any string) loadings.

manifestVars

define the error variances of the manifests with a single time point using R-type lower triangular matrix with nrow=n.manifest & ncol=n.manifest.

indVaryingT0

Forces T0MEANS (T0 scores) to vary interindividually, which undos the nesting of T0(co-)variances in primary studies (default = TRUE). Was standard until Aug. 2022. Could provide better/worse estimates if set to FALSE.

Value

returns a fitted CoTiMA object, in which all drift parameters, Time 0 variances and covariances, and diffusion parameters were set invariant across primary studies


CoTiMA documentation built on May 29, 2024, 11:39 a.m.

Related to ctmaAllInvFit in CoTiMA...