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Causal Inference for Statistics, Social, and Biomedical Sciences - An Introduction (Hardcover)
Loot Price: R1,586
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Causal Inference for Statistics, Social, and Biomedical Sciences - An Introduction (Hardcover)
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Most questions in social and biomedical sciences are causal in
nature: what would happen to individuals, or to groups, if part of
their environment were changed? In this groundbreaking text, two
world-renowned experts present statistical methods for studying
such questions. This book starts with the notion of potential
outcomes, each corresponding to the outcome that would be realized
if a subject were exposed to a particular treatment or regime. In
this approach, causal effects are comparisons of such potential
outcomes. The fundamental problem of causal inference is that we
can only observe one of the potential outcomes for a particular
subject. The authors discuss how randomized experiments allow us to
assess causal effects and then turn to observational studies. They
lay out the assumptions needed for causal inference and describe
the leading analysis methods, including, matching, propensity-score
methods, and instrumental variables. Many detailed applications are
included, with special focus on practical aspects for the empirical
researcher.
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