000			01638nam a2200193 4500
005			20250915191903.0
008			250915b |||||||| |||| 00| 0 eng d
020			_a9781526424730
082			_a519 _bMCB
100			_aMcbee, Matthew _925223
245			_aStatistical approaches to causal analysis
260			_aNew Delhi _bSage Publications India Pvt Ltd _c2021
300			_axi, 234 p.
365			_aGBP _b33.00
500			_aTable of contents: Introduction Conditioning Directed Acyclic Graphs Rubin's Causal Model and the Propensity Score Propensity Score Analysis Instrumental Variable Analysis Regression Discontinuity Design Conclusion [https://us.sagepub.com/en-us/nam/statistical-approaches-to-causal-analysis/book257496#contents]
520			_aA practical, up-to-date, step-by-step guidance on causal analysis for advancing students, this volume of the SAGE Quantitative Research kit features worked example datasets throughout to clearly demonstrate the appication of these powerful techniques, giving students the know-how and the confidence to succeed in their quantitative research journey. Matthew McBee evaluates the issue of causal inference in quantitative research, while providing guidance on how to apply these analyses to your data, discussing key concepts such as: · Directed acyclic graphs (DAGs) · Rubin’s Causal Model (RCM) · Propensity Score Analysis · Regression Discontinuity Design (https://us.sagepub.com/en-us/nam/statistical-approaches-to-causal-analysis/book257496)
650			_aStatistical analysis _916797
942			_cBK _2ddc
999			_c10250 _d10250