mlts_standardized: Get Standardized Estimates for an mlts Model

In mlts: Multilevel Latent Time Series Models with 'R' and 'Stan'

Get Standardized Estimates for an mlts Model

Description

Get Standardized Estimates for an mlts Model

Usage

mlts_standardized(
  object,
  what = c("between", "within", "both"),
  digits = 3,
  prob = 0.95,
  add_cluster_std = FALSE
)

Arguments

object	mltsfit. Output of mlts_model and related functions.
what	character. Get between-level standardized estimates (what = "between", the default), within-level standardized estimates averaged over clusters (what = "within"), or both (what = "both").
digits	Number of digits. Default is 3.
prob	A value between 0 and 1 to indicate the width of the credible interval. Default is .95.
add_cluster_std	logical. If what = "within", within-level standardized effects for each cluster are included in the output (defaults to FALSE).

Value

A list containing between- and within-level standardized parameters.

Examples

# build simple vector-autoregressive mlts model for two time-series variables
var_model <- mlts_model(q = 2)

# fit model with (artificial) dataset ts_data
fit <- mlts_fit(
  model = var_model,
  data = ts_data,
  ts = c("Y1", "Y2"), # time-series variables
  id = "ID", # identifier variable
  time = "time", # time variable
  tinterval = 1, # interval for approximation of continuous-time dynamic model,
  monitor_person_pars = TRUE # person parameters need to be sampled for standardization
)

# inspect standardized parameter estimates
mlts_standardized(fit)

mlts documentation built on June 27, 2024, 5:13 p.m.