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### Path diagrams ###
#
# setMethod("semPaths.S4",signature("lavaan"),function(object,...){
# invisible(semPaths(semPlotModel(object),...))
# })
#
## EXTRACT MODEL ###
setMethod("semPlotModel_S4",signature("lavaan"),function(object){
if (is(object,"blavaan")) class(object) <- 'lavaan'
if (!is(object,"lavaan")) stop("Input must me a 'lavaan' object")
# Extract parameter estimates:
pars <- parameterEstimates(object,standardized=TRUE)
list <- inspect(object,"list")
# Remove mean structure (TEMP SOLUTION)
# meanstructure <- pars$op=="~1"
# pars <- pars[!meanstructure,]
# Extract variable and factor names:
# varNames <- fit@Model@dimNames$lambda[[1]]
# factNames <- fit@Model@dimNames$lambda[[2]]
# Lambda <- inspect(object,"coef")$lambda
varNames <- lavaanNames(object, type="ov")
factNames <- lavaanNames(object, type="lv")
# rm(Lambda)
factNames <- factNames[!factNames%in%varNames]
# Extract number of variables and factors
n <- length(varNames)
k <- length(factNames)
# Extract parameter names:
if (is.null(pars$label)) pars$label <- rep("",nrow(pars))
semModel <- new("semPlotModel")
if (is.null(pars$group)) pars$group <- ""
# Create edges dataframe
semModel@Pars <- data.frame(
label = pars$label,
lhs = ifelse(pars$op=="~"|pars$op=="~1",pars$rhs,pars$lhs),
edge = "--",
rhs = ifelse(pars$op=="~"|pars$op=="~1",pars$lhs,pars$rhs),
est = pars$est,
std = pars$std.all,
group = pars$group,
fixed = list$free[list$op!="=="]==0,
par = list$free[list$op!="=="],
stringsAsFactors=FALSE)
semModel@Pars$edge[pars$op=="~~"] <- "<->"
semModel@Pars$edge[pars$op=="~*~"] <- "<->"
semModel@Pars$edge[pars$op=="~"] <- "~>"
semModel@Pars$edge[pars$op=="=~"] <- "->"
semModel@Pars$edge[pars$op=="~1"] <- "int"
semModel@Pars$edge[grepl("\\|",pars$op)] <- "|"
# Move thresholds to Thresholds slot:
semModel@Thresholds <- semModel@Pars[grepl("\\|",semModel@Pars$edge),-(3:4)]
# Remove constraints and weird stuff:
semModel@Pars <- semModel@Pars[!pars$op %in% c('<', '>',':=','<','>','==','|'),]
# Remove thresholds from Pars:
# semModel@Pars <- semModel@Pars[!grepl("\\|",semModel@Pars$edge),]
semModel@Vars <- data.frame(
name = c(varNames,factNames),
manifest = c(varNames,factNames)%in%varNames,
exogenous = NA,
stringsAsFactors=FALSE)
# res.cov <- lavTech(object, "sampstat")$res.cov
# lavTech(object, "sampstat")$cov
# if (!is.null(res.cov) && !length(res.cov) == 0){
# if (!is.null(res.cov[[1]])){
# semModel@ObsCovs <- object@SampleStats@res.cov
# } else {
# semModel@ObsCovs <- object@SampleStats@cov
# }
# } else {
# semModel@ObsCovs <- list(matrix(NA,
# length(varNames),length(varNames)))
# }
# Use add.labels=TRUE so lavTech returns named matrices (handles multigroup with different vars)
if (lavInspect(object, "options")$conditional.x){
semModel@ObsCovs <- lapply(lavTech(object, "sampstat", add.labels = TRUE),"[[","res.cov")
} else {
semModel@ObsCovs <- lapply(lavTech(object, "sampstat", add.labels = TRUE),"[[","cov")
}
names(semModel@ObsCovs) <- lavInspect(object, "group.label")
if (lavInspect(object, "options")$conditional.x){
semModel@ImpCovs <- lapply(lavTech(object, "implied", add.labels = TRUE), "[[", "res.cov")
} else {
semModel@ImpCovs <- lapply(lavTech(object, "implied", add.labels = TRUE), "[[", "cov")
}
names(semModel@ImpCovs) <- lavInspect(object, "group.label") # object@Data@group.label
semModel@Computed <- TRUE
semModel@Original <- list(object)
return(semModel)
})
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