PSYC40005: Lecture 7 - Logistic Regression and Loglinear Models
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Questions and Answers

In logistic regression, what is the main reason for not being able to compare the variance with linear regression R2?

  • The dependent variable is binary, not continuous
  • The proportion (mean) of the dependent variable affects the variance (correct)
  • The model is non-linear, not linear
  • The predictor variables are not correlated with the dependent variable

    • Why are extremes values easier to account for in logistic regression?

  • There is less variability around the mean (correct)
  • It is easier to model extreme probabilities
  • There is more variability around the mean
  • The model is more robust to outliers

    • What is the main difference between R2 in linear regression and logistic regression?

  • R2 is only calculated for linear regression, not logistic regression
  • R2 is calculated based on correlation in linear regression, and likelihood ratios in logistic regression (correct)
  • R2 is calculated based on correlation in logistic regression, and likelihood ratios in linear regression
  • R2 is only calculated for logistic regression, not linear regression

    • What is the purpose of Nagelkerke's adjustment to the Cox and Snell R2?

    <p>To scale the R2 value to a maximum possible value</p> Signup and view all the answers

    In logistic regression, what does it mean to correctly predict values?

    <p>To accurately forecast the probability of the dependent variable</p> Signup and view all the answers

    Why are means around 0.5 associated with high variance?

    <p>Because the probability is near the midpoint</p> Signup and view all the answers

    What is the role of likelihood ratios in logistic regression?

    <p>To calculate the R2 value</p> Signup and view all the answers

    How are parameters estimated in logistic regression?

    <p>Using numerical methods</p> Signup and view all the answers

    What is the purpose of the Cox and Snell R2 in logistic regression?

    <p>To compare the model with the null model</p> Signup and view all the answers

    Why is it difficult to interpret the R2 value in logistic regression?

    <p>Because it does not have a maximum value of 1.0</p> Signup and view all the answers

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