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# semPaths.sem <- function(object,...)
# {
# invisible(semPaths(semPlotModel(object),...))
# }
#
# semPaths.msem <- function(object,...)
# {
# invisible(semPaths(semPlotModel(object),...))
# }
#
# semPaths.msemObjectiveML <- function(object,...)
# {
# invisible(semPaths(semPlotModel(object),...))
# }
#
### SINGLE GROUP MODEL ###
semPlotModel.sem <- function(object, ...)
{
# Check if object is of class "sem":
if (!any(class(object)%in%c("sem","semmod"))) stop("Input must be a 'sem' object")
# Define Pars:
Pars <- data.frame(
label = rownames(object$ram),
lhs = object$ram[,3],
edge = "--",
rhs = object$ram[,2],
est = object$ram[,5],
std = standardizedCoefficients(object)[,2],
group = 1,
fixed = object$ram[,4]==0,
par = object$ram[,4],
stringsAsFactors=FALSE)
# Extract parameter estimates:
Pars$est[object$ram[,4]!=0] <- object$coef[object$ram[,4]]
# Fix labels:
for (i in unique(object$ram[,4][object$ram[,4]!=0]))
{
if (any(Pars$label[object$ram[,4]==i]=="") & any(Pars$label[object$ram[,4]==i]!=""))
{
Pars$label[object$ram[,4]==i & Pars$label==""] <- Pars$label[object$ram[,4]==i & Pars$label!=""]
}
}
# Name variables:
Pars$lhs <- object$var.names[Pars$lhs]
Pars$rhs <- object$var.names[Pars$rhs]
# Variable dataframe:
Vars <- data.frame(
name = object$var.names,
manifest = object$var.names %in% colnames(object$S),
exogenous = NA,
stringsAsFactors=FALSE)
# Define operators:
Pars$edge[object$ram[,1]==2] <- "<->"
Pars$edge[object$ram[,1]==1] <- "~>"
# Pars$op[object$ram[,1]==1 & !Vars$manifest[match(Pars$lhs,Vars$name)] & Vars$manifest[match(Pars$rhs,Vars$name)]] <- "->"
semModel <- new("semPlotModel")
semModel@Pars <- Pars
semModel@Vars <- Vars
semModel@Computed <- TRUE
semModel@Original <- list(object)
semModel@ObsCovs <- list(object$S)
semModel@ImpCovs <- list(object$C)
return(semModel)
}
### MUTLI GROUP MODEL ###
semPlotModel.msem <- semPlotModel.msemObjectiveML <- function(object, ...)
{
nGroup <- length(object$ram)
GroupNames <- object$groups
ParsS <- list()
stdobject <- standcoefmsem(object)
for (g in 1:nGroup)
{
# Define Pars:
Pars <- data.frame(
label = rownames(object$ram[[g]]),
lhs = object$ram[[g]][,3],
edge = "",
rhs = object$ram[[g]][,2],
est = object$ram[[g]][,5],
std = stdobject[[g]][,2],
group = GroupNames[g],
fixed = object$ram[[g]][,4]==0,
par = object$ram[[g]][,4],
stringsAsFactors=FALSE)
# Extract parameter estimates:
Pars$est[object$ram[[g]][,4]!=0] <- object$coef[object$ram[[g]][,4]]
# Fix labels:
for (i in unique(object$ram[[g]][,4][object$ram[[g]][,4]!=0]))
{
if (any(Pars$label[object$ram[[g]][,4]==i]=="") & any(Pars$label[object$ram[[g]][,4]==i]!=""))
{
Pars$label[object$ram[[g]][,4]==i & Pars$label==""] <- Pars$label[object$ram[[g]][,4]==i & Pars$label!=""]
}
}
# Name variables:
Pars$lhs <- object$var.names[[g]][Pars$lhs]
Pars$rhs <- object$var.names[[g]][Pars$rhs]
# Define operators:
Pars$edge[object$ram[[g]][,1]==2] <- "<->"
Pars$edge[object$ram[[g]][,1]==1] <- "->"
ParsS[[g]] <- Pars
}
Pars <- do.call("rbind",ParsS)
# Variable dataframe:
Vars <- data.frame(
name = unique(unlist(object$var.names)),
manifest = unique(unlist(object$var.names)) %in% unique(c(sapply(object$S,colnames))),
exogenous = NA,
stringsAsFactors=FALSE)
# Pars$op[object$ram[,1]==1 & !Vars$manifest[match(Pars$lhs,Vars$name)] & Vars$manifest[match(Pars$rhs,Vars$name)]] <- "->"
semModel <- new("semPlotModel")
semModel@Pars <- Pars
semModel@Vars <- Vars
semModel@Computed <- TRUE
semModel@Original <- list(object)
semModel@ObsCovs <- object$S
semModel@ImpCovs <- object$C
return(semModel)
}
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