Question 26 of my final exam for Design and Analysis of Sample Surveys

26. You have just graded an an exam with 28 questions and 15 students. You fit a logistic item- response model estimating ability, difficulty, and discrimination parameters. Which of the following statements are basically true? (Indicate all that apply.)

(a) If a question is answered correctly by students with very low and very high ability, but is missed by students in the middle, it will have a high value for its discrimination parameter.

(b) It is not possible to fit an item-response model when you have more questions than students. In order to fit the model, you either need to reduce the number of questions (for example, by discarding some questions or by putting together some questions into a combined score) or increase the number of students in the dataset.

(c) To keep the model identified, you can set one of the difficulty parameters or one of the ability parameters to zero and set one of the discrimination parameters to 1.

(d) If two students answer the same number of questions correctly, they will have the same estimated ability parameter.

(e) Under the model, if a student’s ability parameter has the same value as a particular question’s difficulty parameter, there is a 50% chance the student will get the question right.

Solution to question 25

From yesterday:

25. You are using multilevel regression and poststratification (MRP) to a survey of 1500 people to estimate support for the space program, by state. The model is fit using, as a state- level predictor, the Republican presidential vote in the state, which turns out to have a low correlation with support for the space program. Which of the following statements are basically true? (Indicate all that apply.)

(a) For small states, the MRP estimates will be determined almost entirely by the demo- graphic characteristics of the respondents in the sample from that state.

(b) For small states, the MRP estimates will be determined almost entirely by the demographic characteristics of the population in that state.

(c) Adding a predictor specifically for this model (for example, a measure of per-capita space-program spending in the state) could dramatically improve the estimates of state-level opinion.

(d) It would not be appropriate to add a predictor such as per-capita space-program spending in the state: by adding such a predictor to the model, you would essentially be assuming what you are trying to prove.

Solution: (b) and (c) are correct. (a) is wrong (actually, inference for small states will be driven by the state-level predictor), and (d) is wrong (because the new coefficient will be estimated from the data).

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