ml_tsdlvm1 {psychonetrics}

Multi-level Lag-1 dynamic latent variable model family of psychonetrics models for time-series data

Description

This function is a wrapper around dlvm1 that allows for specifying the model using a long format data and similar input as the mlVAR package. The ml_ts_lvgvar simply sets within_latent = "ggm" and between_latent = "ggm" by default. The ml_gvar and ml_var are simple wrappers with different named defaults for contemporaneous and between-person effects.

Usage

ml_tsdlvm1(data, beepvar, idvar, vars, groups, estimator = "FIML", 
  standardize = c("none", "z", "quantile"), ...)

ml_ts_lvgvar(...)

ml_gvar(..., contemporaneous = c("ggm", "cov", "chol", "prec"), 
        between = c("ggm", "cov", "chol", "prec"))
             
ml_var(..., contemporaneous = c("cov", "chol", "prec", "ggm"), 
        between = c("cov", "chol", "prec", "ggm"))

Arguments

data

The data to be used. Must be raw data in long format (each row indicates one person at one time point).

beepvar

Optional string indicating assessment beep per day. Adding this argument will cause non-consecutive beeps to be treated as missing!

idvar

String indicating the subject ID

vars

Vectors of variables to include in the analysis

groups

An optional string indicating the name of the group variable in data.

estimator

Estimator to be used. Must be "FIML".

standardize

Which standardization method should be used? "none" (default) for no standardization, "z" for z-scores, and "quantile" for a non-parametric transformation to the quantiles of the marginal standard normal distribution.

contemporaneous

The type of within-person latent contemporaneous model to be used.

between

The type of between-person latent model to be used.

...

Arguments sent to dlvm1

Author(s)

Sacha Epskamp <[e-mail]>