Data Set 4
A study was conducted to determine if the drug dobutamine could be used effectively in a
test for measuring a patient's risk of having a heart attack, or "cardiac event." For
younger patients, a typical test of this risk is called "stress echocardiography." It involves
raising the patient's heart rate by exercise--often by having the patient run on a treadmill-and then taking various measurements, such as heart rate and blood pressure, as well as
more complicated measurements of the heart. The problem with this test is that it often
cannot be used on older patients whose bodies can't take the stress of hard
exercise. The key to assessing risk, however, is putting stress on the heart before taking
the relevant measurements. While exercise can't be used to create this stress for older
patients, the drug dobutamine can. This study, then, was an attempt to see if the variables
observed during the stress echocardiography test were still effective in predicting cardiac
events when the stress on the heart was produced by dobutamine instead of exercise.
In particular, 558 consecutive, eligible patients who underwent dobutamine stress
echocardiography at a certain clinic were recruited over a 5 year period. Each patient was
observed over the 12 months following recruitment, and their outcome (presence/absence
of cardiac event during the year) was recorded.
Description of data: The response variable is called event (0=cardiac event, 1=no
cardiac event). In addition, the following 23 predictor variables were observed:
bhr
basebp
pkhr
sbp
dose
maxhr
PERmphr
mbp
age
gender
baseEF
dobEF
chestpain
posECG
equivecg
restwma
posSE
hxofHT
hxofdm
hxofcig
hxofMI
BASAL HEART RATE
BASAL BLOOD PRESSURE
PEAK HEART RATE
SYSTOLIC BLOOD PRESSURE
DOSE OF DOBUTAMINE GIVEN
MAXIMUM HEART RATE
% OF MAX. PREDICTED HEART RATE ACHIEVED BY PATIENT
MAXIMUM BLOOD PRESSURE
PATIENT'S AGE
PATIENT'S GENDER (male = 0, female=1)
BASELINE CARDIAC EJECTION FRACTION
EJECTION FRACTION ON DOBUTAMINE
CHEST PAIN (0=yes, 1=no)
SIGNS OF HEART ATTACK ON ECG (0 = yes, 1=no)
ECG IS EQUIVOCAL (0 = yes, 1=no)
WALL MOTION ANAMOLY (0 = yes, 1=no)
STRESS ECHOCARDIOGRAM WAS POSITIVE (0 = yes, 1=no)
PATIENT HAS HISTORY OF HYPERTENSION (0 = yes, 1=no)
PATIENT HAS HISTORY OF DIABETES (0 = yes, 1=no)
PATIENT HAS HISTORY OF SMOKING (0 = yes, 1=no)
PATIENT HAS HISTORY OF HEART ATTACK (0 = yes, 1=no)
hxofPTCA
hxofCABG
PATIENT HAS HISTORY OF ANGIOPLASTY (0 = yes, 1=no)
PATIENT HAS HISTORY OF BYPASS SURGERY (0 = yes, 1=no)
Preliminary analysis: When the purpose of the study is predictive – particularly when
there are many predictor variables, it is common to use non-parametric methods such as
classification and regression trees (CART). However, if you are unfamiliar with such
methods, you are welcome to use a parametric method such as a generalized linear model
(GLM). If you choose the GLM route, you are required to investigate only a reasonable
preliminary model for the data (i.e., you don’t need to consider the possibility of
including interaction terms or non-linear functions of the continuous predictor variables).
Step 1: Regardless of your approach, you should divide the data into a “test” sample and
a (smaller) “validation” sample. For example, you could randomly choose 448
observations to make up your test sample. The remaining 100 observations would make
up your validation sample.
Step 2: Fit your model using only the data in the test sample. The fitted model will allow
you to predict the outcome (event or no event) for new values of the predictor variables.
Step 3: Predict outcomes for each observation in the validation sample. Specifically, use
the fitted model from Step 2 and the predictor variable values in the validation sample to
predict event/no event for each of the 100 cases.
Step 4: To assess the usefulness of your model for predictions, compute the percentage of
predicted outcomes that match the observed outcomes in the validation sample. Does
your model seem to predict outcomes better than the null model, i.e. the model with none
of the observed predictor variables?