View source: R/ctmaAllInvFit.R

ctmaAllInvFit | R Documentation |

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,
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
)
```

`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 |

`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. |

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

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.