ctmaAllInvFit {CoTiMA} | R Documentation |

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

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

`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 |

`nopriors` |
nopriors |

`finishsamples` |
finishsamples |

`iter` |
iter |

`chains` |
chains |

`verbose` |
verbose |

`loadAllInvFit` |
loadAllInvFit |

`saveAllInvFit` |
saveAllInvFit |

`silentOverwrite` |
silentOverwrite |

`customPar` |
logical. Leverages the first pass using priors and ensure that the drift diagonal cannott easily go too negative (could help with ctsem > 3.4) |

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

[Package *CoTiMA* version 0.4.0 Index]