simsem (version 0.4-6)

summaryConverge: Provide a comparison between the characteristics of convergent replications and nonconvergent replications

Description

This function provides a comparison between the characteristics of convergent replications and nonconvergent replications. The comparison includes sample size (if varying), percent missing completely at random (if varying), percent missing at random (if varying), parameter values, misspecified-parameter values (if applicable), and population misfit (if applicable).

Usage

summaryConverge(object, improper = FALSE)

Arguments

object

SimResult object being described

improper

If TRUE, include the replications that provided improper solutions

Value

• A list with the following elements:
  • ConvergedThe number of convergent and nonconvergent replications
  • nSample size
  • pmMCARPercent missing completely at random
  • pmMARPercent missing at random
  • paramValueParameter values
  • misspecValueMisspecified-parameter values
  • popFitPopulation misfit. See details of each element atsummaryMisspec.
  Each element will provide the head-to-head comparison between convergent and nonconvergent replications properties.

Examples

path.BE <- matrix(0, 4, 4)
path.BE[3, 1:2] <- NA
path.BE[4, 3] <- NA
starting.BE <- matrix("", 4, 4)
starting.BE[3, 1:2] <- "runif(1, 0.3, 0.5)"
starting.BE[4, 3] <- "runif(1, 0.5, 0.7)"
mis.path.BE <- matrix(0, 4, 4)
mis.path.BE[4, 1:2] <- "runif(1, -0.1, 0.1)"
BE <- bind(path.BE, starting.BE, misspec=mis.path.BE)

residual.error <- diag(4)
residual.error[1,2] <- residual.error[2,1] <- NA
RPS <- binds(residual.error, "rnorm(1, 0.3, 0.1)")

loading <- matrix(0, 12, 4)
loading[1:3, 1] <- NA
loading[4:6, 2] <- NA
loading[7:9, 3] <- NA
loading[10:12, 4] <- NA
mis.loading <- matrix("runif(1, -0.3, 0.3)", 12, 4)
mis.loading[is.na(loading)] <- 0
LY <- bind(loading, "runif(1, 0.7, 0.9)", misspec=mis.loading)

mis.error.cor <- matrix("rnorm(1, 0, 0.1)", 12, 12)
diag(mis.error.cor) <- 0
RTE <- binds(diag(12), misspec=mis.error.cor)

SEM.Model <- model(RPS = RPS, BE = BE, LY=LY, RTE=RTE, modelType="SEM")

n1 <- list(mean = 0, sd = 0.1)
chi5 <- list(df = 5)

facDist <- bindDist(c("chisq", "chisq", "norm", "norm"), chi5, chi5, n1, n1)

# In reality, more than 50 replications are needed.
simOut <- sim(50, n=500, SEM.Model, sequential=TRUE, facDist=facDist, estimator="mlr")

# Summary the convergent and nonconvergent replications
summaryConverge(simOut)