Detailed Course Information |
Fall 2016
Oct 22, 2025 |
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| PHP 2610 - Causal Inference and Missing Data |
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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 or PHP 2580.
1.000 Credit hours 1.000 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Primary Meeting Public Health Department Prerequisites: Undergraduate level MATH 1610 Minimum Grade of S or Graduate level PHP 2511 Minimum Grade of S |
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