| 000 | 02376cam a22003498i 4500 | ||
|---|---|---|---|
| 999 |
_c2066 _d2066 |
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| 003 | OSt | ||
| 005 | 20230929091456.0 | ||
| 008 | 221028s2023 mau b 001 0 eng | ||
| 020 |
_a9780262545914 _q(paperback) |
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| 020 |
_z9780262374927 _q(epub) |
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| 020 |
_z9780262374910 _q(pdf) |
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| 040 |
_aDLC _beng _erda _cDLC |
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| 100 | 1 |
_aHuber, Martin, _97256 |
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| 245 | 1 | 0 | _aCausal analysis: impact evaluation and causal machine learning with applications in R |
| 263 | _a2306 | ||
| 264 | 1 |
_aCambridge, Massachusetts _bThe MIT Press, _c[2023] |
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| 300 | _apages cm | ||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_aunmediated _bn _2rdamedia |
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| 338 |
_avolume _bnc _2rdacarrier |
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| 504 | _aIncludes bibliographical references and index. | ||
| 520 |
_aA comprehensive and cutting-edge introduction to quantitative methods of causal analysis, including new trends in machine learning.
Reasoning about cause and effect—the consequence of doing one thing versus another—is an integral part of our lives as human beings. In an increasingly digital and data-driven economy, the importance of sophisticated causal analysis only deepens. Presenting the most important quantitative methods for evaluating causal effects, this textbook provides graduate students and researchers with a clear and comprehensive introduction to the causal analysis of empirical data. Martin Huber's accessible approach highlights the intuition and motivation behind various methods while also providing formal discussions of key concepts using statistical notation. Causal Analysis covers several methodological developments not covered in other texts, including new trends in machine learning, the evaluation of interaction or interference effects, and recent research designs such as bunching or kink designs. _cProvided by publisher. |
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| 650 | 0 |
_aSocial sciences _xResearch. _97257 |
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| 650 | 0 |
_aCausation. _96991 |
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| 650 | 0 |
_aInference. _96992 |
|
| 650 | 0 |
_aEconometrics. _97258 |
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| 776 | 0 | 8 |
_iOnline version: _aHuber, Martin, 1980- _tCausal analysis _dCambridge, Massachusetts : The MIT Press, [2023] _z9780262374927 _w(DLC) 2022033286 |
| 856 |
_3Details (publisher) _uhttps://mitpress.mit.edu/9780262545914/causal-analysis/ |
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| 906 |
_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg |
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| 942 |
_2JEL _cBO |
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