Description Usage Arguments Value Constraints See Also Examples
coxph
Fits a Cox proportional hazards regression model.
1 |
formula |
A symbolic description of model to fit |
data |
FLTable object. Can be wide or deep |
catToDummy |
Transform categorical variables to numerical values either using dummy variables or by using Empirical Logit. If the value is 1, transformation is done using dummy variables, else if the value is 0, transformation is done using Empirical Logit. |
performNorm |
0/1 indicating whether to perform standardization of data. |
performVarReduc |
0/1. If the value is 1, the stored procedure eliminates variables based on standard deviation and correlation. |
makeDataSparse |
If 0,Retains zeroes and NULL values from the input table. If 1, Removes zeroes and NULL. If 2,Removes zeroes but retains NULL values. |
minStdDev |
Minimum acceptable standard deviation for elimination of variables. Any variable that has a standard deviation below this threshold is eliminated. This parameter is only consequential if the parameter PerformVarReduc = 1. Must be >0. |
maxCorrel |
Maximum acceptable absolute correlation between a pair of columns for eliminating variables. If the absolute value of the correlation exceeds this threshold, one of the columns is not transformed. Again, this parameter is only consequential if the parameter PerformVarReduc = 1. Must be >0 and <=1. |
classSpec |
list describing the categorical dummy variables. |
whereconditions |
takes the where_clause as a string. |
coxph
returns a FLCoxPH
object
The formula object should have a Surv
object.
The arguments to Surv
object must strictly be in the order
(time
,time2
,event
) or (time
,event
).
Arguments to Surv
should be plain. For instance, as.numeric(SurvColumn)
inside Surv
is not supported.
Only coefficients
,linear.predictors
,FLSurvivalData
,
FLCoxPHStats
,loglik
,wald.test
,n
,nevent
,
rscore
,call
,formula
,call
,model
,x
,
means
,terms
can be called on fitted object using $.
coefficients,plot,print,summary methods are available for fitted object.
coxph
for corresponding R function reference
1 2 3 4 5 6 7 8 9 10 | dropTable("tblcoxph_wide")
createTable("tblcoxph_wide",pSelect=paste0("SELECT ID AS obsid,time_AIDS_d AS time_val,censor AS status,sex,ivdrug,tx FROM ",getTestTableName("tblCoxPH")),pTemporary=FALSE)
widetable <- FLTable(getTestTableName("tblcoxph_wide"),
"obsid")
fitT <- coxph(Surv(time_val,status) ~ sex + ivdrug + tx,widetable)
resultList <- predict(fitT,newdata=widetable)
resultList[[1]]
resultList[[2]]
summary(fitT)
plot(fitT)
|
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