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Brown University

 

HELP | EXIT

Detailed Course Information

 

Spring 2015
Mar 29, 2024
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  Select the desired Level or Schedule Type to find available classes for the course.

PHP 2610 - Causal Inference and Missing Data
Systematic overview of modern statistical methods for handling incomplete data and for drawing causal inferences from "broken experiments" and observational studies. Topics include modeling approaches, propensity score adjustment, instrumental variables, inverse weighting methods and sensitivity analysis. Case studies used throughout to illustrate ideas and concepts. Prerequisite: MATH 1610 or PHP 2511. Open to advanced undergraduates with permission from the instructor.
1.000 Credit hours
1.000 Lecture hours

Levels: Graduate, Undergraduate
Schedule Types: Primary Meeting

Public Health Department

Restrictions:
Must be enrolled in one of the following Levels:     
      Graduate

Prerequisites:
Undergraduate level MATH 1610 Minimum Grade of S or Graduate level PHP 2511 Minimum Grade of S

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