mxtrmodLRT | R Documentation |
This function runs likelihood ratio tests on full vs. reduced mixture models. Input arguments are data frame outputs from the mxtrmod function.
mxtrmodLRT(fullmod, redmod, adj = NULL)
fullmod |
The output data frame from the mxtrmod function on the full mixture model. |
redmod |
The output data frame from the mxtrmod function on the reduced mixture model. |
adj |
The adjustment method for multiple comparisons. The default is set to NULL. Options for adjustment methods are described in the documentation for the function mt.rawp2adjp in the multtest package. |
A data frame containing the response variables (i.e. metabolites), negative log likelihoods of full and reduced models, chi square statistics, degrees of freedom, p-values, and, if requested, adjusted p-values.
Michael Nodzenski, Anna Reisetter, Denise Scholtens
Moulton LH, Halsey NA. A mixture model with detection limits for regression analyses of antibody response to vaccine. Biometrics. 1995 Dec;51(4):1570-8.
#Create sample data set.seed(123) yvar<-rlnorm(200) these<-sample(1:100,20) yvar[these]<-NA logyvar<-log(yvar) y2var<-rlnorm(200) those<-sample(1:200,25) y2var[those]<-NA logy2var<-log(y2var) pred1<-sample(0:1,200,replace=TRUE) pred2<-sample(1:10,200,replace=TRUE) pred3<-sample(0:1,200,replace=TRUE) pred3miss<-sample(1:200,50) pred3[pred3miss]<-NA testdata<-data.frame(cbind(yvar,y2var,logyvar,logy2var,pred1,pred2,pred3)) #Get the names of the response variables ynames<-names(testdata)[3:4] #Run a full mixture model on each response variable fullMod<-~pred1+pred2+pred3|pred1+pred2+pred3 fullModRes<-mxtrmod(ynames=ynames,mxtrModel=fullMod,data=testdata) fullModRes #Run a reduced mixture model on each response variable redMod<-~pred2|pred2 redModRes<-mxtrmod(ynames=ynames,mxtrModel=redMod,data=testdata,fullModel=fullMod) redModRes #Compare models using likelihood ratio test mxtrmodLRT(fullModRes,redModRes)
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