print.LCT: Print tree results to the terminal
In MattisvdBergh/LCT: Estimate a Latent Class Tree model with Latent GOLD 5.1

These function display the results of a Latent Class Tree analysis

1 2	## S3 method for class 'LCT' print(x, ...)

`dataDir`	directory of the data or a dataframe with the data
`LG`	directory of the Latent GOLD executable
`LGS`	directory of Latent GOLD syntax for a model with 1- and 2-class splits
`decreasing`	Whether the ordering of classes should be decreasing or not. Defaults to TRUE.
`maxClassSplit1`	Maximum size of the first split of the tree. Will be assessed with the criterion given in stopCriterium. Defaults to two.
`maxClassSplit2`	Maximum size of each split after the first split of the tree. Defaults to two.
`stopCriterium`	Criterium to decide on a split. Can be "LL" (logLikelihood), "AIC" or "BIC".
`resultsName`	Name of a folder which will be created in the working directory and contains all results by Latent GOLD.
`minSampleSize`	Minimum sample size of a class. If this is below 1, a probability of the total sample size is used.
`itemNames`	The names of the indicators. If this is not given, the rownames of the datafile will be used.
`nKeepVariables`	Number of variables to be kept if one wants to explore the results with external variables.
`weight`	Name of the variable with the weights. When all records are unique observations, this should be one for every observation.
`measurementLevels`	A character vector being either ordinal or continuous to indicate the measurement level of each variable. It is required when LGS is specified.