MASTER.R

In htx-r/RiskModelNMApredictions:

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#         Master analysis for MS NMA Prediction MODEL 
############################################################

###### Give your path of data
library(devtools)
#install_github("htx-r/CleaningData",force=TRUE)
install_github("htx-r/RiskModelNMApredictions", force = TRUE)
library(RiskModelNMApredictions)
#library(CleaningData)
mydatapath="C:/Users/kc19o338/Desktop/HTx/data/IPD data from 6 Biogen trials"


### load data
cleanBIOGENtrials<-cleanBIOGENtrials.fun(mydatapath)
adsl01<-cleanBIOGENtrials$adsl01
### Select variables that I need and recode them in numerical values (e.g. Male=1, Female=0)
MSrelapse<-numericalDataRisk.fun(adsl01)
###results of Internal risk score
model<-internalRisk.fun(MSrelapse)
model
##############################################################################
#selection of variables based on n half RCTs (script named CrossSelection.Lasso)        #######################
##### because of the "for" loop it takes a lot of time and is only needed for 
##### the selection of variables in cross Internal Risk score
##### its results are integrated into Cross internal risk score
##results of Cross Internal Risk score
CrossInternalRisk.fun(MSrelapse)

#####################################################################################
###########################ANALYSIS FOR 2 YEARS RELAPSES#############################
####################################################################################
###results of Internal risk score
internalRisk2year.fun(MSrelapse)
####selection of variables based on n half RCTs(script named CrossSelection2years.Lasso)
####because of the "for" loop it takes a lot of time and is only needed for 
####the selection of variables in cross Internal Risk score
####its results are integrated into Cross internal risk score
####results of Cross Internal Risk score
CrossInternalRisk2year.fun(MSrelapse)