simsem (version 0.2-8)

SimFunction-class: Class "SimFunction"

Description

This class will save a function using for data transformation later in a simulation study within simResult.

Objects from the Class

Objects can be created by simFunction. It can also be called from the form new("SimFunction", ...).

Methods

• summaryTo summarize the object
• runTo use the object for data transformation.

See Also

• SimResultfor how to use thesimFunctionin a simulation study

Examples

showClass("SimFunction")

n65 <- simNorm(0.6, 0.05)
u35 <- simUnif(0.3, 0.5)
u68 <- simUnif(0.6, 0.8)
u2 <- simUnif(-0.2, 0.2)
n1 <- simNorm(0, 0.1)

loading <- matrix(0, 9, 3)
loading[1:3, 1] <- NA
loading[4:6, 2] <- NA
loading[7:9, 3] <- NA
loading.start <- matrix("", 9, 3)
loading.start[1:3, 1] <- 0.7
loading.start[4:6, 2] <- 0.7
loading.start[7:9, 3] <- "u68"
LY <- simMatrix(loading, loading.start)

RTE <- symMatrix(diag(9))

factor.cor <- diag(3)
factor.cor[1, 2] <- factor.cor[2, 1] <- NA
RPS <- symMatrix(factor.cor, 0.5)

path <- matrix(0, 3, 3)
path[3, 1:2] <- NA
path.start <- matrix(0, 3, 3)
path.start[3, 1] <- "n65"
path.start[3, 2] <- "u35"
BE <- simMatrix(path, path.start)

datGen <- simSetSEM(BE=BE, LY=LY, RPS=RPS, RTE=RTE)

loading.trivial <- matrix(NA, 9, 3)
loading.trivial[is.na(loading)] <- 0
LY.trivial <- simMatrix(loading.trivial, "u2")

error.cor.trivial <- matrix(NA, 9, 9)
diag(error.cor.trivial) <- 0
RTE.trivial <- symMatrix(error.cor.trivial, "n1")

misGen <- simMisspecSEM(LY = LY.trivial, RTE = RTE.trivial)

Data.Mis <- simData(datGen, 300, misspec=misGen)

loading <- matrix(0, 12, 4)
loading[1:3, 1] <- NA
loading[4:6, 2] <- NA
loading[7:9, 4] <- NA
loading[10:12, 3] <- NA

path <- matrix(0, 4, 4)
path[4, 1:3] <- NA

analysis <- simParamSEM(BE=path, LY=loading)

Model <- simModel(analysis)

# Find the products of indicators
newFUN <- function(data, var1, var2, namesProd) {
	prod <- data[,var1] * data[,var2]
	colnames(prod) <- namesProd
	return(data.frame(data, prod))
}

fun <- simFunction(newFUN, var1=paste("y", 1:3, sep=""), var2=paste("y", 4:6, sep=""), namesProd=paste("y", 10:12, sep=""))

# Real simulation will need more than just 10 replications
Output <- simResult(10, Data.Mis, Model, objFunction=fun)
summary(Output)

# Example of using the simfunction
mc <- simFunction(newFUN, var1=1:3, var2=4:6, namesProd=paste("y", 10:12, sep=""))
run(mc, attitude[,-1])
summary(mc)