Description Arguments Details Value Author(s) See Also Examples
Extract information from a simulation result
object |
The target |
what |
The target component to be extracted. Please see details below. |
improper |
Specify whether to include the information from the replications with improper solutions |
nonconverged |
Specify whether to include the information from the nonconvergent replications |
Here are the list of information that can be specified in the what
argument. The items starting with * are the information that the improper
and nonconverged
arguments are not applicable.
*"modeltype"
: The type of the simulation result
*"nrep"
: The number of overall replications, including converged and nonconverged replications
"param"
: Parameter values (equivalent to the getPopulation
function)
"stdparam"
: Standardized parameter values (equivalent to the getPopulation
function with std = TRUE
)
"coef"
: Parameter estimates (equivalent to the coef
method)
"se"
: Standard errors
"fit"
: Fit indices
"misspec"
: Misspecified parameter values
"popfit"
: Population misfit
"fmi1"
: Fraction missings type 1
"fmi2"
: Fraction missings type 2
"std"
: Standardized Parameter Estimates
"stdse"
: Standard Errors of Standardized Values
"cilower"
: Lower bounds of confidence intervals
"ciupper"
: Upper bounds of confidence intervals
"ciwidth"
: Widths of confidence intervals
*"seed"
: Seed number (equivalent to the summarySeed
function)
"ngroup"
: Sample size of each group
"ntotal"
: Total sample size
"mcar"
: Percent missing completely at random
"mar"
: Percent missing at random
"extra"
: Extra output from the outfun
argument from the sim
function)
*"time"
: Time elapsed in running the simulation (equivalent to the summaryTime
function)
*"converged"
: Convergence of each replication
The target information depending on the what
argument
Sunthud Pornprasertmanit (psunthud@gmail.com)
SimResult
for the object input
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ## Not run:
loading <- matrix(0, 6, 2)
loading[1:3, 1] <- NA
loading[4:6, 2] <- NA
LY <- bind(loading, 0.7)
latent.cor <- matrix(NA, 2, 2)
diag(latent.cor) <- 1
RPS <- binds(latent.cor, 0.5)
RTE <- binds(diag(6))
VY <- bind(rep(NA,6),2)
CFA.Model <- model(LY = LY, RPS = RPS, RTE = RTE, modelType = "CFA")
# In reality, more than 5 replications are needed.
Output <- sim(5, CFA.Model, n=200)
inspect(Output, "coef")
inspect(Output, "param")
inspect(Output, "se", improper = TRUE, nonconverged = TRUE)
## End(Not run)
|
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