SAS A00-240 Exam - Topic 6 Question 41 Discussion

Actual exam question for SAS's A00-240 exam

Question #: 41
Topic #: 6

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?

AThere is quasi-complete separation in the data.

BThere is collinearity among the predictors.

CThere are missing values in the data.

DThere are too many observations in the data.

Show Suggested Answer

Suggested Answer: A

by Gracia at May 04, 2022, 10:59 PM

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Deeanna

6 months ago

Missing values could also mess things up, but not as likely.

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Kimberely

6 months ago

Wait, how can there be too many observations? That seems odd.

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Jarvis

6 months ago

I thought collinearity could be a problem too, though.

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Teresita

6 months ago

Totally agree, that’s a classic reason for non-convergence.

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Sabra

6 months ago

Looks like quasi-complete separation is the issue here.

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Carmelina

7 months ago

I doubt having too many observations is the issue; more data usually helps, right? It seems like A is the most likely answer.

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Hollis

7 months ago

Missing values could be a factor, but I feel like they usually just lead to warnings rather than convergence failures.

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Bettina

7 months ago

I think collinearity could also be a problem, but I’m not sure if it would prevent convergence like separation would.

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Loreen

7 months ago

I remember something about quasi-complete separation causing convergence issues in logistic regression. That might be it.

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Denna

7 months ago

This looks like a classic cross-site scripting (XSS) attack. The attacker is injecting malicious JavaScript code into the URL, which could be executed by the victim's browser.

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Karma

7 months ago

Okay, I've got a strategy for this. I'll start by eliminating the options that I know are false, then focus on the remaining ones to determine which three are true. Single-row functions can be tricky, but I think I can work through this.

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