Description Usage Arguments Value Author(s) Examples
View source: R/summarySimResult.R
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).
1 | summaryConverge(object, std = FALSE, improper = TRUE)
|
object |
|
std |
If |
improper |
If TRUE, include the replications that provided improper solutions |
A list with the following elements:
Converged
The number of convergent and nonconvergent replications
n
Sample size
pmMCAR
Percent missing completely at random
pmMAR
Percent missing at random
paramValue
Parameter values
misspecValue
Misspecified-parameter values
popFit
Population misfit. See details of each element at summaryMisspec
.
Each element will provide the head-to-head comparison between convergent and nonconvergent replications properties.
Sunthud Pornprasertmanit (psunthud@gmail.com)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | ## Not run:
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)
## End(Not run)
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