140.623.01
Statistical Methods in Public Health III
 Location:
 East Baltimore
 Term:
 3rd term
 Department:
 Biostatistics
 Credits:
 4 credits
 Academic Year:
 2013  2014
 Instruction Method:
 TBD
 Class Times:

 Tu Th, 10:30  11:50am
 Auditors Allowed:
 Yes, with instructor consent
 Grading Restriction:
 Letter Grade or Pass/Fail
 Course Instructors:
 Contact:
 Marie DienerWest
 Resources:
 Prerequisite:
 Description:

Presents use of generalized linear models for quantitative analysis of data encountered in public health and medicine. Specific models include analysis of variance, analysis of covariance, multiple linear regression, logistic regression, and Cox regression.
 Learning Objectives:

Upon successfully completing this course, students will be able to:
 Use statistical reasoning to formulate public health questions in quantitative terms 1.1 Critique a proposed public health hypothesis to determine its suitability for testing using regression methods and the available data; 1.2 Formulate and correctly interpret a multivariable linear, logistic or survival regression model to estimate a health effect while minimizing confounding and identifying possible effect modification; 1.3 Evaluate the limitations of observational data as evidence for a health effect; 1.4 Appreciate the importance of relying upon many regression models to capture the relationships among a response and predictor in observational studies
 Conduct statistical computations and construct graphical and tabular displays for regression analysis 2.1 Use the statistical analysis package Stata to perform multivariable regression models; 2.2 Document and archive the steps of your statistical analysis by creating a Stata dofile; 2.3 Create and interpret scatterplots and adjusted variable plots that display the relationships among an outcome and multiple risk factors; 2.4 Create and interpret tables of regression results including unadjusted and adjusted estimates of coefficients with confidence intervals from many models
 Use probability models to describe trends and random variation in public health data 3.1 Distinguish between the underlying probability distributions for modeling continuous, categorical, binary and timetoevent data; 3.2 Recognize the key assumptions underlying a multivariable regression model and judge whether departures in a particular application warrant consultation with a statistical expert
 Use statistical methods for inference in multiple regression to draw valid public health inferences from data [4.1 Conduct a simple linear, logistic or survival regression and correctly interpret the regression coefficients and their confidence interval.
 Methods of Assessment:
Student evaluation based on problem sets and exams.
 Enrollment Restriction:
For MPH, DrPH, "special students" and MHS degree candidates in departments to be determined
 Instructor Consent:
Consent required for some students
 Consent Note:
Consent required for nonPH students
 For consent, contact:
 Special Comments:
One 90minute lab per week, lab is 140.923. As soon as you register for the course, please also register for one section of 140.923. Course Materials Fee is $40.00.