This function computes the initial values for the parameters for a multivariate latent growth curve model or a latent change score model.
getMULTI.initial(dat, t_var, y_var, curveFun, records, res_scale, res_cor)A list containing the initial values for the parameters in the multivariate latent growth curve model or a latent change score model growth curve model.
A wide-format data frame, with each row corresponding to a unique ID. It contains the observed variables
with repeated measurements and occasions for multiple longitudinal outcomes. It takes the value passed from getMGM().
A vector of strings, with each element representing the prefix for column names related to the time
variable for the corresponding outcome variable at each study wave. It takes the value passed from getMGM().
A vector of strings, with each element representing the prefix for column names corresponding to a
particular outcome variable at each study wave. It takes the value passed from getMGM().
A string specifying the functional form of the growth curve. Supported options for y_model =
"LGCM" include: "linear" (or "LIN"), "quadratic" (or "QUAD"), "negative exponential"
(or "EXP"), "Jenss-Bayley" (or "JB"), and "bilinear spline" (or "BLS"). Supported
options for y_model = "LCSM" include: "quadratic" (or "QUAD"), "negative exponential"
(or "EXP"), "Jenss-Bayley" (or "JB"), and "nonparametric" (or "NonP"). It takes the
value passed from getMGM().
A list of numeric vectors, with each vector specifying the indices of the observed study waves for
the corresponding outcome variable. It takes the value passed from getMGM().
A numeric vector with each element representing the scaling factor for the initial calculation of the residual
variance. These values should be between 0 and 1, exclusive. It takes the value passed from getMGM().
A numeric value or vector for user-specified residual correlation between any two longitudinal outcomes to calculate
the corresponding initial value. It takes the value passed from getMGM().