R/hr.threg.R

Defines functions hr

Documented in hr

### The following is the definition of the hr.threg function
hr <- function(object, var, timevalue, scenario)
    UseMethod("hr")

"hr.threg" <-
function (object,var,timevalue,scenario) 
{
	para <- match.call(expand.dots = FALSE)
        indx <- match(c("object", "var", "timevalue", "scenario"),
		  names(para), nomatch=0) 

	if (indx[1] ==0) stop("An object argument is required")
	if (indx[2] ==0) stop("A var argument is required")
        if (!inherits(object, 'threg'))
           stop("Primary argument must be a threg object")

	m_timevalue<-match(c("timevalue"), names(para), 0)

        #if "timevalue" option is not specified, use the study time
	if (!m_timevalue) timevalue<- model.extract(object$mf, "response")[,1]
	if(!is.numeric(timevalue)) {
		stop(paste("'timevalue' option must specify a numerical value!"))	     		
	}	
	m_scenario<-match(c("scenario"), names(para), 0)
	m_hr<-match(c("var"), names(para), 0)

        scenario_value<-NULL
        scenario_covariate<-NULL
        if(m_scenario!=0) {
		cur_scenario_string<-para[[m_scenario]]
		while(length(cur_scenario_string)>=2) {

			if(length(cur_scenario_string)==3) {
				current_scenario_covariate_string<-cur_scenario_string[[3]]
				if(length(current_scenario_covariate_string)==2) { 
				  current_scenario_covariate<-current_scenario_covariate_string[[1]]
				  current_covariate_value<-current_scenario_covariate_string[[2]]
				  scenario_covariate<-c(current_scenario_covariate,scenario_covariate)
				  scenario_value<-c(current_covariate_value,scenario_value)
				}  				
				else {
				  stop("wrong scenario specification")  
				}
				cur_scenario_string<-cur_scenario_string[[2]]
			}
			else if(length(cur_scenario_string)==2) {
				current_scenario_covariate_string<-cur_scenario_string
				current_scenario_covariate<-current_scenario_covariate_string[[1]]
				current_covariate_value<-current_scenario_covariate_string[[2]]

				scenario_covariate<-c(current_scenario_covariate,scenario_covariate)
				scenario_value<-c(current_covariate_value,scenario_value)

				current_scenario_covariate_string<-NULL
				cur_scenario_string<-NULL
				current_scenario_covariate<-NULL
				current_covariate_value<-NULL
			}
		}

        }
        #add intercept term
	scenario_covariate<-c("(Intercept)",scenario_covariate)
	scenario_value<-c(1,scenario_value)        

	names(scenario_value)<-scenario_covariate
        



        m_hr<-match(c("var"), names(para), 0)
	hr_var<-as.character(para[[m_hr]])
        if (!is.factor(object$mf[[hr_var]])) stop("The variable for the hazard ratio calculation should be a factor variable")

        if (length(levels(object$mf[[hr_var]]))<2) stop("The variable for the hazard ratio calculation should have more than one level")
 

        if (!any(names(object$mf)==hr_var)) stop("The variable ",as.character(para[[m_hr]]) , " for the hazard ratio calculation should be included in the model")

        
        

        scenario_value_hr<-rbind(rep(0,length(levels(object$mf[[hr_var]]))-1),diag(rep(1,length(levels(object$mf[[hr_var]]))-1)))
	#names(scenario_value_hr)<-paste(hr_var,levels(object$mf[[hr_var]])[-1],sep="")
        colnames(scenario_value_hr) <- paste(hr_var,levels(object$mf[[hr_var]])[-1],sep="")
        if (any(matrix(rep(names(scenario_value),times=length(dimnames(scenario_value_hr)[[2]])),nrow=length(dimnames(scenario_value_hr)[[2]]),byrow=TRUE)==dimnames(scenario_value_hr)[[2]])) stop("Don't specify the scenario value of the dummy variable for the hazard ratio calculation!")


        scenario_value<-matrix(rep(scenario_value,times=length(levels(object$mf[[hr_var]]))),nrow=length(levels(object$mf[[hr_var]])),byrow=TRUE)

        dimnames(scenario_value)[[2]] <- as.list(scenario_covariate)


        

	scenario_value<-cbind(scenario_value,scenario_value_hr)



        #judge if any covariate for lny0 lacks of scenario value
	judgematrix_lny0<-matrix(rep(object$lny0,times=dim(scenario_value)[2]),ncol=dim(scenario_value)[2])==matrix(rep(dimnames(scenario_value)[[2]],times=length(object$lny0)),nrow=length(object$lny0),byrow=TRUE)


	if (any(!apply(judgematrix_lny0,1,any)))
               stop(paste("scenario value for",  object$lny0[!apply(judgematrix_lny0,1,any)][1], "is required!"))
	       
	#choose the right position of scenario values to combine
	positionpick_lny0=judgematrix_lny0%*%c(1:dim(scenario_value)[2])

        lny0<-scenario_value[,positionpick_lny0]%*%object$coef[1:length(object$lny0)]
	y0<-exp(lny0)


        #judge if any covariate for mu lacks of scenario value
	judgematrix_mu<-matrix(rep(object$mu,times=dim(scenario_value)[2]),ncol=dim(scenario_value)[2])==matrix(rep(dimnames(scenario_value)[[2]],times=length(object$mu)),nrow=length(object$mu),byrow=TRUE)


	if (any(!apply(judgematrix_mu,1,any)))
               stop(paste("scenario value for",  object$mu[!apply(judgematrix_mu,1,any)][1], "is required!"))
	       
	#choose the right position of scenario values to combine
	positionpick_mu=judgematrix_mu%*%c(1:dim(scenario_value)[2])

        mu<-scenario_value[,positionpick_mu]%*%object$coef[(length(object$lny0)+1):(length(object$lny0)+length(object$mu))]
        
	dim(y0)<-NULL
	dim(lny0)<-NULL
	dim(mu)<-NULL

        y0<-c(rep(y0,length(timevalue)))
	lny0<-c(rep(lny0,length(timevalue)))
	mu<-c(rep(mu,length(timevalue)))
	lenth_timevalue<-length(timevalue)
	
	#replicate values for matrix calculation
	timevalue_rep<-rep(timevalue,each=length(dimnames(scenario_value_hr)[[2]])+1)


	f<-exp((lny0-.5*(log(2*pi*(timevalue_rep^3))+(y0+mu*timevalue_rep)^2/timevalue_rep)))
        S<-exp(log(pnorm((mu*timevalue_rep+y0)/sqrt(timevalue_rep))-exp(-2*y0*mu)*pnorm((mu*timevalue_rep-y0)/sqrt(timevalue_rep))))
	h<-f/S
	dim(h)<-c(length(dimnames(scenario_value_hr)[[2]])+1,lenth_timevalue)
	#list the hazard ratios
        if (dim(h)[[1]]>2) {
		hr<-t(h[-1,]/h[1,])
        }
        else if (dim(h)[[1]]==2) {
                hr<-cbind(h[-1,]/h[1,])
        }

	colnames(hr)<-dimnames(scenario_value_hr)[[2]]
	hr<-cbind(timevalue,hr)

	#rownames(hr)<-c(timevalue)
	#table_hr<-cbind(hr)
	#dimnames(table_hr)<-list(names(hr),"Haz. Ratio")
	#prmatrix(table_hr)
	hr
	
}

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threg documentation built on May 29, 2017, 9:37 p.m.