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SAS Exam A00-240 Topic 2 Question 114 Discussion

Actual exam question for SAS's A00-240 exam
Question #: 114
Topic #: 2
[All A00-240 Questions]

An analyst fits a logistic regression model to predict whether or not a client will default on a loan. One of the predictors in the model is agent, and each agent serves 15-20 clients each. The model fails to converge. The analyst prints the summarized data, showing the number of defaulted loans per agent. See the partial output below:

What is the most likely reason that the model fails to converge?

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Suggested Answer: A

by Brittni at Jul 11, 2025, 02:39 AM

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Olive
6 days ago
Missing values, really? Isn't that just lazy data-collecting? Come on, analysts, get it together!
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Almeta
6 days ago
I think missing values in the data might be causing the convergence problem.
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Audrie
16 days ago
I believe collinearity among predictors could also be a reason for the model failing to converge.
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Johnetta
19 days ago
Collinearity, huh? That could be it. If the agents are all doing pretty much the same thing, the model might not be able to figure out which one is really making the difference.
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Beatriz
24 days ago
Hmm, the data seems to have some strange patterns. Maybe there's some kind of separation going on here that's causing the model to freak out.
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Craig
10 days ago
B) There is collinearity among the predictors.
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Iesha
11 days ago
A) There is quasi-complete separation in the data.
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Bettina
1 months ago
I agree with Shelton, quasi-complete separation can cause convergence issues.
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Shelton
1 months ago
I think the model fails to converge because of quasi-complete separation.
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