model selection - MODEL SELECTION FOR LOGISTIC REGRESSION...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon
MODEL SELECTION FOR LOGISTIC REGRESSION Estimation : Interest centers on examining the association between outcome and one or more variables, possibly adjusted for other variables. We are most interested in drawing inferences about regression coefficients from the logistic model Prediction : Interest conters on being able to predict which category an individual observation will fall into based on the values of one or more explanatory variables. We are most interested in the properties of predictions made based on our logistic model. First, we will consider how to go about performing logistic regression analysis when we interested in estimation Second, we will consider how to go about performing logistic regression analysis when we are interested in prediction. Simple random experiments If we start adjusting for variables, we remove ability to talk about randomization Blocked Randomized Experiments OBSERVATIONAL STUDIES Confirmatory vs Exploratory Exploratory Studies
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
EXAMPLE MODEL SELECTION PART II
Background image of page 2
Image of page 3
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 02/09/2012 for the course STAT 513 taught by Professor Barbaramc.knight during the Spring '11 term at University of Washington.

Page1 / 7

model selection - MODEL SELECTION FOR LOGISTIC REGRESSION...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online