DynTxRegime (version 3.01)

.newTypedSimpleFit: Complete Outcome Regression Step When Single Model.

Description

Complete an outcome regression step when iterative method is not required and subsets are not used for modeling. Method is not exported.

Usage

.newTypedSimpleFit(moMain, moCont, txInfo, ...)
# S4 method for modelObj,modelObj,TxInfoNoSubsets
.newTypedSimpleFit(moMain, moCont, txInfo, data, response, suppress)
# S4 method for modelObj,NULL,TxInfoNoSubsets
.newTypedSimpleFit(moMain, moCont, txInfo, data, response, suppress)
# S4 method for NULL,modelObj,TxInfoNoSubsets
.newTypedSimpleFit(moMain, moCont, txInfo, data, response, suppress)
# S4 method for modelObj,modelObj,TxInfoWithSubsets
.newTypedSimpleFit(moMain, moCont, txInfo, data, response, suppress)
# S4 method for modelObj,NULL,TxInfoWithSubsets
.newTypedSimpleFit(moMain, moCont, txInfo, data, response, suppress)
# S4 method for NULL,modelObj,TxInfoWithSubsets
.newTypedSimpleFit(moMain, moCont, txInfo, data, response, suppress)

Arguments

moMain

"modelObj" for main effects component of outcome.

moCont

"modelObj" for contrast component of outcome.

txInfo

Treatment information.

...

Used to pass arguments that are required but the class of which does not determine the method that is selected.

data

"data.frame" of covariates and treatment history.

response

Vector of outcome of interest.

suppress

T/F indicating if screen prints are generated.

Examples

data(bmiData)

y <- -(bmiData$month12BMI - bmiData$month4BMI) / bmiData$month4BMI * 100

moMain <- buildModelObj(model = ~ parentBMI + baselineBMI + month4BMI, 
                        solver.method = 'lm')
moCont <- buildModelObj(model = ~ parentBMI + baselineBMI + month4BMI, 
                        solver.method = 'lm')

# Treatment Object
txInfo <- DynTxRegime:::.newTxInfo(fSet = NULL, 
                                   txName = "A2", 
                                   data = bmiData, 
                                   suppress = TRUE, 
                                   verify = TRUE)

obj <- DynTxRegime:::.newTypedSimpleFit(moMain = moMain, 
                                        moCont = moCont,  
                                        txInfo = txInfo, 
                                        data = bmiData,  
                                        response = y,  
                                        suppress = TRUE)

is(obj)
coef(obj)
fitObject(obj)
plot(obj)
predict(obj)
predict(obj, bmiData)
DynTxRegime:::.predictAllTreatments(object = obj, data = bmiData)
print(obj)
show(obj)
summary(obj)

obj <- DynTxRegime:::.newTypedSimpleFit(moMain = moMain, 
                                        moCont = NULL,  
                                        txInfo = txInfo, 
                                        data = bmiData,  
                                        response = y,  
                                        suppress = TRUE)

is(obj)
print(obj)

obj <- DynTxRegime:::.newTypedSimpleFit(moMain = NULL, 
                                        moCont = moCont,  
                                        txInfo = txInfo, 
                                        data = bmiData,  
                                        response = y,  
                                        suppress = TRUE)


is(obj)
print(obj)

fSet <- function(data){
          subsets <- list(list("subset1", c("CD","MR")),
                          list("subset2", c("CD","MR")))
         txOpts <- character(nrow(data))
         txOpts[data$A1 == "CD"] <- "subset1"
         txOpts[data$A1 == "MR"] <- "subset2"
         return(list("subsets" = subsets, "txOpts" = txOpts))
        }

# Integer treatment with subsetting
txInfo <- DynTxRegime:::.newTxInfo(fSet = fSet, 
                                   txName = "A2", 
                                   data = bmiData, 
                                   suppress = TRUE, 
                                   verify = TRUE)

obj <- DynTxRegime:::.newTypedSimpleFit(moMain = moMain, 
                                        moCont = moCont, 
                                        txInfo = txInfo, 
                                        data = bmiData, 
                                        response = y, 
                                        suppress = TRUE)

is(obj)
coef(obj)
fitObject(obj)
plot(obj)
predict(obj)
predict(obj, bmiData)
DynTxRegime:::.predictAllTreatments(object = obj, data = bmiData)
print(obj)
show(obj)
summary(obj)


obj <- DynTxRegime:::.newTypedSimpleFit(moMain = moMain, 
                                        moCont = NULL, 
                                        txInfo = txInfo, 
                                        data = bmiData, 
                                        response = y, 
                                        suppress = TRUE)

is(obj)
print(obj)

obj <- DynTxRegime:::.newTypedSimpleFit(moMain = NULL, 
                                        moCont = moCont, 
                                        txInfo = txInfo, 
                                        data = bmiData, 
                                        response = y, 
                                        suppress = TRUE)
is(obj)
print(obj)