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Question ID 20225

Suppose training data are oversampled in the event group to make the number of events and non-events
roughly equal. A logistic regression is run and the probabilities are output to a data set NEW and given the
variable name PE. A decision rule considered is, "Classify data as an event if probability is greater than
0.5." Also the data set NEW contains a variable TG that indicates whether there is an event (1=Event, 0=
No event).
The following SAS program was used.

What does this program calculate?

Option A

Depth 

Option B

Sensitivity

Option C

Specificity

Option D

Positive predictive value

Correct Answer B
Explanation


Question ID 20226

Refer to the exhibit:
The plots represent two models, A and B, being fit to the same two data sets, training and validation.
Model A is 90.5% accurate at distinguishing blue from red on the training data and 75.5% accurate at doing
the same on validation data. Model B is 83% accurate at distinguishing blue from red on the training data
and 78.3% accurate at doing the same on the validation data.
Which of the two models should be selected and why?

Option A

Model A. It is more complex with a higher accuracy than model B on training data.

Option B

Model A. It performs better on the boundary for the training data. 

Option C

Model B. It is more complex with a higher accuracy than model A on validation data.

Option D

Model B. It is simpler with a higher accuracy than model A on validation data.

Correct Answer D
Explanation

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