Binary Logistic Regression Flashcards
Continuous Variable for Outcome use what test?
Linear Regression
Discrete or Binary Variable for Outcome use what test?
Logistic Regression
What is the Purpose of Binary Logistic Regression?
- Predict the outcome of a BINART dependent outcome variable based on one or more independent predictor variables, which may be discrete or continuous
- Interpret significant odds ratios
Researchers can transform continuous outcome variables into what?
BINARY variable if assumptions of linear regression are not met
Residual Homoscedasticity
What you WANT for linear regression
Heteroscedastic
VARIANCE is NOT equal at all points = MUST do LOGISTIC regression
Logit is what?
LOG-ODDS
Natural log of the odds of success
Maximum Likelihood Estimation MLE
Used to maximize the predictive capabilities of the regression
Overall M
Model of Significance
Overall Model Significance (step 1)
No R^2 or Adjusted R^2 to interpret the proportion of total variation
USE a Chi-Squaree goodness of fit statistic for the overall model
Significance of Predictor Variables (step 2)
Hypothesis tests are conducted using a WALD-CHI-SQUARE TEST
Since logistic regression is a non-linear model, the coefficient estimate B is transformed into ODDS RATIO
OR or expB or adjusted OR
Adjusted OR = allows you to look at one predictor value by controlling for the others
Definition of Odds Ratio OR
The odds that an outcome Y=1 will occur given a particular exposure X, compared to the odds of the outcome occurring in the absence of that exposure
OR Meanings
OR = 1 = X does not affect odds of Y
OR >1 = X is associated with higher odds of Y
OR <1 = X is associated with lower odds of Y
For OR the 95% CI is significant when it what?
Does NOT include 1