forward.opt: Search for the optimal item-level PM design via forward...

Description Usage Arguments Value See Also

View source: R/forward-opt.R

Description

forward.opt runs simulations using Mplus. It returns the search results for optimal item-level PM designs via forward assembly.

Usage

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forward.opt(VNAMES, distal.var, n, nreps, seed, Time, k, Time.complete,
  costmx, pc, pd, design0.out, focal.param, max.mk, eval.budget = F,
  rm.budget = NULL, complete.var = NULL)

Arguments

VNAMES

A character vector containing the names of the observed variables. The variable names must be ordered chronologically, by the time (wave) they are measured.

distal.var

Char vector. Specify the names of the variables, if there are any time-independent distal variables included in the model that are not subject to planned missingness.

n

The total sample size as initially planned.

nreps

Number of replications for Monte Carlo simulations.

seed

The seed for random number generation.

Time

The total number of time points (i.e., the total number of data collection waves).

k

The number of observed variables collected at each wave.

Time.complete

Number of data collection waves that have been completed before the funding cut occurs.

costmx

A numeric vector containing the unit cost of each observed variable that is yet to be measured (post the funding cut). The cost is assumed to be constant across subjects, but it is allowed to vary across variables and across waves.

pc

Numeric. Proportion of completers: the proportion of subjects that will participate in all of the following waves of data collection and provide complete data. This must be greater than 0.

pd

Numeric. The proportion of subjects that will not participate in any of the following waves of data collection (i.e., drop from the longitudinal study). This value can be 0.

design0.out

An object returned by readModels. To obtain this object, the user need to have a Mplus output file which contains the a priori power analysis results for this specific model assuming a complete data design (i.e., simulation-based power analysis for sample size planning). In principle, a priori power analysis is supposed to be conducted before the study began.

focal.param

Char vector. The parameters of focal interest. The focal parameters should be specified in the specific format based on the Mplus output object design0.out.

max.mk

Specify the maximum number of unique missing data patterns in the selected design. Only applicable if forward assembly is used.

eval.budget

Logical scalar (TRUE or FALSE), indicating whether there is any budget constraint. If the user wishes to search for PM designs under the budget limit, they need to specify the amount of the remaining available budget that can be used for future data collection.

rm.budget

Numeric. The amount of remaining budget avaialbe for future data collection.

complete.var

Char Vector. Specify the name(s) of the variable (s) if there are any variable(s) that need to have complete data collected from all the participating subjects.

Value

An object containing the information of the optimal item-level missing design. The optimal design is the one that yields highest power for testing the focal parameters, compared to other plausible candidate PM designs.

See Also

simPM which is a warpper function for this function.


YiFengEDMS/simPM documentation built on July 25, 2020, 4:08 a.m.