Lecture 8 - Logistic Regression Flashcards
What is logistic regression?
The prediction of group membership from a continuous independent variable
What is binary logistic regression?
The prediction of two groups from a continuous variable.
What is binary logistic regression also called?
Binomial logistic regression
What is multinomial logistic regression?
Predicting more than two groups from a continuous variable.
The odds of an event can be calculated by…?
Dividing the probability of the event occurring by the probability of the event not occurring.
Why are log odds used rather than normal odds?
Log odds are symmetrical around 0, which is better for statisticians.
Why is logistic regression so-called?
It is based on natural logarithms.
Logistic regressions aren’t actually used for predictions, they are used for…?
Modelling data.
What level of data is needed for logistic regression to work well/best?
High quantity of data.
What does Block 0: Beginning Block predict about your data?
All cases are predicted to result in the most common outcome - the accuracy of this prediction is then reported in a later table.
The first classification table tells us what?
How good the (first) model predicted in Block 0 is.
What does Block 1 method: Enter tell us?
- Iteration history: summary of how the model has been approximated and improved.
- Reports the results of logistic regression analysis.
- Whether it is a functional model, being better than block 0 or not.
-2 log likelihood has to be as ____ as possible to reflect a more accurate/effective model?
Small
What does the Omnibus Test of Model Coefficients tell us?
Whether the model is significant - tests general fit of the model.
What does the model summary tell us in a logistic regression?
- The final -2log likelihood of the model
- An approximation of R^2 for the model
Cox and Snell R Square and Nagelkerke R Square represents what?
An approximation/estimation of R Square for the model.
Can an equation be used to predict data points in logistic regressions, like for linear regressions?
No.
In Logistic Regression outputs under ‘Variables in the Equation’, what does the WALD statistic and Sig. represent?
Usefulness of each predictor - whether or not each predictor is significant in the model.
In Logistic Regression outputs under ‘Variables in the Equation’, what does the B represent?
Coefficients for each predictor variable in the model.
In Logistic Regression outputs under ‘Variables in the Equation’, what does the Exp (B) represent?
The change in predicted odds for each unit change in the predictor variable.
E.g. an increase of 1.898 in the odds of re-offending for every extra year/day/month that someone is convicted for.
The constant is the same as what?
The intercept.
What are 4 limitations of logistic regressions?
- Calculation only works if the relationship between the predictors/probabilities and the dependent variable is sigmoidal
- Very sensitive to outliers
- The ratio of sample size to variables needs to be quite high (needs large numbers of participants)
- SPSS assumes that relationships are being described, rather than being predicted.
The classification tables in the output of logistic regressions relate to what?
The sample only.
Why can logistic regressions not provide an equivalent of R Square Adjusted?
Logistic regression provides a model of the data from the sample, not a formula or prediction and not for the wider population.
In logistic regressions, the significance of the model generated is calculated using what?
An x squared-like measure.
Why is significance measured using an x squared-like measure in logistic regressions?
Because the DV is categorical.
In logistic regressions, what type of variable is the DV?
Categorical
The second classification table tell us what?
How good the (second) prediction in Block 1 was.
