Lecture 6 - Logistic Regression Flashcards
What is the primary purpose of logistic regression?
To model categorical outcomes based on predictor variables.
What type of outcome does logistic regression model?
Categorical outcomes.
What are the two main types of logistic regression?
Binomial Logistic Regression and Multinomial Logistic Regression.
How does logistic regression differ from linear regression in terms of outcome?
Logistic regression is used for categorical outcomes, while linear regression is used for continuous outcomes.
What is the equation for logistic regression?
y = 1 / (1 + e^(-v)), where v = bx + c.
What does the odds ratio represent in logistic regression?
The measure of association between predictor variables and the outcome, indicating how the odds change with a unit increase in the predictor.
What test is used to evaluate the significance of individual predictors in logistic regression?
Wald Test.
What does a significant Wald Test indicate?
That the predictor variable significantly contributes to the model.
Name a test used to assess the goodness-of-fit in logistic regression.
Hosmer and Lemeshow Test.
What does the Hosmer and Lemeshow Test evaluate?
How well the model’s predicted outcomes match the actual outcomes.
What is multicollinearity and why is it important in logistic regression?
Multicollinearity refers to high correlations between predictor variables, which can affect the stability and interpretation of the regression coefficients.
What assumption in logistic regression involves checking the linearity of the logit?
The assumption that there is a linear relationship between the logit of the dependent variable and the predictor.
What procedure is used to test the linearity of the logit?
Box-Tidwell procedure.
What is the difference between the ‘Enter’ method and the ‘Stepwise’ method in logistic regression?
The ‘Enter’ method includes all predictors simultaneously, while the ‘Stepwise’ method adds or removes predictors based on statistical criteria.
How can you interpret the coefficient in logistic regression?
By exponentiating the coefficient, which shows how the odds change with a unit increase in the predictor.
What is a common way to report the overall significance of a logistic regression model?
Using the chi-squared (Χ²) test.
What does a significant chi-squared (Χ²) test result indicate in logistic regression?
That the model with the predictors explains a significant proportion of the variance in the outcome.
How is predictive accuracy assessed in logistic regression?
By evaluating the proportion of correctly classified cases and comparing observed and predicted outcomes.
What are the pseudo R-squared values used for in logistic regression?
To provide an approximation of the variance explained by the model, similar to R² in linear regression.
In the context of logistic regression, what does an odds ratio greater than 1 signify?
That the odds of the outcome increase with an increase in the predictor.
In the context of logistic regression, what does an odds ratio less than 1 signify?
That the odds of the outcome decrease with an increase in the predictor.
What is the Box-Tidwell procedure used for in logistic regression?
To test the linearity of the logit for continuous predictors.
What steps are involved in performing logistic regression analysis in SPSS?
Select predictors and dependent variable, configure options, interpret output.
