000			01845 a2200253 4500
003			OSt
005			20220921163012.0
008			220921b xxu||||| |||| 00| 0 eng d
020			_a9780521885881
040			_cIIT Kanpur
041			_aeng
082			_a519.54 _bIm1c
100			_aImbens, Guido W.
245			_aCausal inference _bfor statistics, social, and biomedical sciences: an introduction _cGuido W. Imbens and Donald B. Rubin
260			_bCambridge University Press _c2015 _aCambridge
300			_axix, 625p
440			_aAdvances praise for causal inference for statistics, social, and biomedical sciences
520			_aMost 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.
650			_aCausation
650			_aInference
650			_aSocial sciences -- Research
700			_aRubin, Donald B.
942			_cBK
999			_c566066 _d566066