MSDecision: Multiple Sclerosis Decision Delay

In ADVICE: Automatic Direct Variable Selection via Interrupted Coefficient Estimation

Description

This data frame contains the time (in weeks) between the initial symptoms (onset symptoms) and the decision time to visit a doctor in the case of 54 patients who eventually were diagnosed with multiple sclerosis. Interest centers on whether there are any factors which tend to be related to the delay time.

Usage

data(MSDecision)

Format

A data frame with 54 observations on the following 16 variables.

Delay

numeric, time in weeks

ClinicalDiseaseCourse

factor, 2 levels

CodedGender

factor, 2 levels, 1 = Male, 2 = Female

AgeAtOnset

numeric, age in years

OnsetSymptom1

factor, 4 levels

OnsetSymptom2

factor, 5 levels

OnsetSymptomSeverity

factor, 2 levels, 0 = Low, 1 = High

TriggerSymptom1

factor, 4 levels

TriggerSymptom2

factor, 4 levels

TriggerSymptomSeverity

factor, 2 levels, 0 = Low, 1 = High

FamilyHistory

factor, 2 levels, yes = there is MS in the family history

FearOfWorseningSymptoms

factor, 2 levels

MoreThanOneSymptom

factor, 2 levels

EffectonResponsibilities

factor, 2 levels, yes = the symptoms are having an effect on the individual

UncertainResponse

logical, TRUE = recorded delay time is not accurate

Details

The levels of the Clinical Disease Course variable are: Clinically Isolated Syndrome and Relapse-Remitting.

Examples

   xy <- MSDecision
   xy$sensoryOnset1 <- factor(xy$OnsetSymptom1=="SENSORY")
   xy$brainstemOnset2 <- factor(xy$OnsetSymptom2=="BRAINSTEM")
   xy$sensoryTrigger1 <- factor(xy$TriggerSymptom1=="SENSORY")
   xy$brainstemTrigger2 <- factor(xy$TriggerSymptom2=="BRAINSTEM")
   xy <- xy[, -c(5, 6, 8, 9, 15)]
   xy[,1]<-log(xy[,1])
   names(xy)[1] <- "y"
   out <- ices(y ~ ., data = xy)
   summary(out)
   plot(out) 
   plot(out, normqq=TRUE)
   plot(out, scaleloc=TRUE)

ADVICE documentation built on April 16, 2021, 9:07 a.m.