Description Usage Arguments Details Value Note Author(s) References See Also Examples
One of the main and most important functions. Ties together Indirect Statements and summary output of direct effects
1 | AllSummary(AllNames, Directry = getwd(), GreaterThanNum = 0, PasteIND = 1)
|
AllNames |
|
Directry |
this the path where the folder specified by |
GreaterThanNum |
number of output files containing path over which to average which must be less than the number of imputations and is only used if multiple imputations are performed. Default 0 which is to use all data sets in mean calculations. |
PasteIND |
a value of 1 indicates to use all possible indirect effects in modelling and a value of 0 is input to only use direct effects in modelling |
Must initialize and run backwards selection before using this function
Average |
list with the following objects: |
DirectEffectCounts |
count matrix for number of times path appears which will be 1's and 0's if no imputed data sets are used |
MeanDirectEffects |
mean values of direct effects for paths which are just the direct effects if no imputations are performed |
MeanStandardError |
the mean square error of the effect parameters averaged over imputed data sets if they exist |
MeanPValue |
mean p values of these direct effects |
MinPVals |
minimum p values of these direct effects |
MaxPVals |
maximum p value of these direct effects |
MedianPVals |
median p value of these direct effects |
INDStatements |
lists of indirect effect relations |
This function must be run before AddOnAllInd
can be run (see examples), but otherwise is not a very useful summary function. The user is
instead referred to AllSummary2
. The means in the matrices above are only calculated for those paths and parameters which appear in the count matrix with a value greater than the GreaterThanNum.
William Terry
M Plus
1 2 3 4 5 6 7 8 | ## Not run:
InitD=Simulate(MissingYN=1)
xxx=Initialize(InitD,NumImpute=3,WhichCat=c(1,1,1,1,0))
ggg=AllBackwardSelect(xxx[[1]])
zzz=AllSummary(xxx[[1]])[[2]]
## End(Not run)
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