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New York University 3 credits Global Public Health
Causal inference seeks to study the causal effect of certain treatment/exposure/intervention on some outcome of interest. It has been widely used in public health, biomedical research, social sciences, educational research, economics, etc. The course will introduce some fundamental and advanced causal inference methods and will emphasize their applications in public health, biomedical research, and social sciences. Topics include the potential outcomes framework, treatment effect models, design and analysis of randomized experiments, methods for adjusting for overt bias in observational studies, sensitivity analysis for hidden bias in observational studies, detection of hidden bias, and methods for controlling for hidden bias. Each topic will be illustrated with extensive real-data public health examples. Corequisites: GPH-GU 2182 AND GPH-GU 2450 AND GPH-GU 2332 OR GPH-GU 2353 OR Restriction: Public Health-PhD OR DPH AND Corequisite: GPH-GU 2182 ,GPH-GU 2450, GPH-GU 3332,GPH-GU 3353.
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Learn how to write a good research question for a paper. Narrow your topic, identify a research problem, and create a focused question with practical examples.
Learn how to choose a research topic you can actually research. Discover how to narrow broad ideas, find reliable sources, and develop a focused research question.
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