Deck 16: Logistic and Time Series Regression

Question 1

Logistic regression deals with situations in which the dependent variable is dichotomous.

Answer 1

True

Question 2

Logistic regression is often used in political science.

Answer 2

True

Question 3

The dichotomous nature of the dependent variable violates an assumption of multiple regression.

Answer 3

True

Question 4

Logistic regression fits a U-shaped curve to the data.

Question 5

Logistic regression is the same as multiple regression with dummy variables.

Question 6

The Nagelkerke R² is analogous to R² in multiple regression.

Question 7

Classification tables should have 50% or fewer correctly predicted values.

Question 8

The Hosmer and Lemeshow test compares the observed and predicted values and should be statistically significant.

Question 9

Wald χ² is the test statistic used in logistic regression for testing the statistical significance of logistic regression coefficients.

Question 10

Logistic regression can be used to predict the likelihood of an event occurring.

Question 11

The odds ratio compares the probability of something occurring, as compared to it not occurring.

Question 12

The same principles that apply to multiple regression, such as full model specification, also apply to time series regression.

Question 13

With time series data, the assumption of random distribution of error terms is usually violated.

Question 14

Autocorrelation is detected by examining the variance inflation factor.

Question 15

Values of the Durbin-Watson statistic around 2 indicate autocorrelation.

Question 16

The Durbin-Watson statistic has a range of values for which test statistics are inconclusive.

Question 17

Autocorrelation is a problem, but serial correlation is not.

Question 18

It is better to correct for autocorrelation by taking first differences than by examining relationships in levels form.

Question 19

Policies and program are sometimes evaluated by including dummy variables in the model.

Question 20

A step impact variable is similar to an increasing impact variable.

Question 21

Lagged variables are variables whose effect becomes manifest at some future time.