Causality in the Sciences

Can progress in understanding the tools of causal inference in some sciences lead to progress in others? This book tackles these questions and others concerning the use of causality in the sciences.

[1]  R Fisher,et al.  Design of Experiments , 1936 .

[2]  T. Haavelmo The Statistical Implications of a System of Simultaneous Equations , 1943 .

[3]  I. Good A CAUSAL CALCULUS (I)* , 1961, The British Journal for the Philosophy of Science.

[4]  H. Simon,et al.  Cause and Counterfactual , 1966 .

[5]  Michail Prodan,et al.  CHAPTER 17 – THE PLANNING OF EXPERIMENTS , 1968 .

[6]  P. Suppes A Probabilistic Theory Of Causality , 1970 .

[7]  Wesley C. Salmon,et al.  Statistical explanation & statistical relevance , 1971 .

[8]  D. Rubin Estimating causal effects of treatments in randomized and nonrandomized studies. , 1974 .

[9]  A. Dawid Conditional Independence in Statistical Theory , 1979 .

[10]  D. A. Kenny,et al.  Correlation and Causation , 1937, Wilmott.

[11]  D. A. Kenny,et al.  Correlation and Causation. , 1982 .

[12]  M. Redhead,et al.  How the Laws of Physics Lie. , 1984 .

[13]  D. Rubin,et al.  The central role of the propensity score in observational studies for causal effects , 1983 .

[14]  J. Robins A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect , 1986 .

[15]  D. Lewis Philosophical Papers: Volume II , 1987 .

[16]  P. Holland CAUSAL INFERENCE, PATH ANALYSIS AND RECURSIVE STRUCTURAL EQUATIONS MODELS , 1988 .

[17]  D. Francis An introduction to structural equation models. , 1988, Journal of clinical and experimental neuropsychology.

[18]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems , 1988 .

[19]  N. Cartwright Nature's Capacities and Their Measurement , 1995 .

[20]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[21]  D. Rubin [On the Application of Probability Theory to Agricultural Experiments. Essay on Principles. Section 9.] Comment: Neyman (1923) and Causal Inference in Experiments and Observational Studies , 1990 .

[22]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[23]  S Greenland,et al.  Estimability and estimation of expected years of life lost due to a hazardous exposure. , 1991, Statistics in medicine.

[24]  Edward H. Herskovits,et al.  Computer-based probabilistic-network construction , 1992 .

[25]  Joshua D. Angrist,et al.  Identification of Causal Effects Using Instrumental Variables , 1993 .

[26]  Ming Li,et al.  An Introduction to Kolmogorov Complexity and Its Applications , 2019, Texts in Computer Science.

[27]  Judea Pearl,et al.  Counterfactual Probabilities: Computational Methods, Bounds and Applications , 1994, UAI.

[28]  Judea Pearl,et al.  Probabilistic Evaluation of Counterfactual Queries , 1994, AAAI.

[29]  C. Glymour,et al.  Conditioning and Intervening , 1994, The British Journal for the Philosophy of Science.

[30]  David Maxwell Chickering,et al.  Learning Bayesian networks: The combination of knowledge and statistical data , 1995, Mach. Learn..

[31]  J. Pearl Causal diagrams for empirical research , 1995 .

[32]  Thomas S. Richardson,et al.  Causal Inference in the Presence of Latent Variables and Selection Bias , 1995, UAI.

[33]  James M. Robins,et al.  Probabilistic evaluation of sequential plans from causal models with hidden variables , 1995, UAI.

[34]  Judea Pearl,et al.  Counterfactuals and Policy Analysis in Structural Models , 1995, UAI.

[35]  Nir Friedman,et al.  Learning Bayesian Networks with Local Structure , 1996, UAI.

[36]  Yang Xiang,et al.  Critical Remarks on Single Link Search in Learning Belief Networks , 1996, UAI.

[37]  James J. Heckman,et al.  Identification of Causal Effects Using Instrumental Variables: Comment , 1996 .

[38]  Avi Pfeffer,et al.  Object-Oriented Bayesian Networks , 1997, UAI.

[39]  J. Pearl Graphs, Causality, and Structural Equation Models , 1998 .

[40]  M. Sobel Causal Inference in Statistical Models of the Process of Socioeconomic Achievement , 1998 .

[41]  Michael I. Jordan Graphical Models , 2003 .

[42]  J. Woodward,et al.  Independence, Invariance and the Causal Markov Condition , 1999, The British Journal for the Philosophy of Science.

[43]  P. Todd,et al.  Simple Heuristics That Make Us Smart , 1999 .

[44]  J. Pearl,et al.  Causal diagrams for epidemiologic research. , 1999, Epidemiology.

[45]  Joe Suzuki,et al.  Learning Bayesian Belief Networks Based on the MDL Principle : An Efficient Algorithm Using the Branch and Bound Technique , 1999 .

[46]  J. Pearl Causality: Models, Reasoning and Inference , 2000 .

[47]  Michal Linial,et al.  Using Bayesian Networks to Analyze Expression Data , 2000, J. Comput. Biol..

[48]  D. Rubin Comment on "Causal inference without counterfactuals," by Dawid AP , 2000 .

[49]  Daphne Koller,et al.  Active Learning for Structure in Bayesian Networks , 2001, IJCAI.

[50]  W. Shadish,et al.  Experimental and Quasi-Experimental Designs for Generalized Causal Inference , 2001 .

[51]  Steffen L. Lauritzen,et al.  Causal Inference from Graphical Models , 2001 .

[52]  Judea Pearl,et al.  Direct and Indirect Effects , 2001, UAI.

[53]  Wolfgang Spohn,et al.  Bayesian Nets Are All There Is To Causal Dependence , 2001 .

[54]  Jin Tian,et al.  A general identification condition for causal effects , 2002, AAAI/IAAI.

[55]  D. Lindley Seeing and Doing: the Concept of Causation , 2002 .

[56]  S. Cole,et al.  Fallibility in estimating direct effects. , 2002, International journal of epidemiology.

[57]  G. Quinn,et al.  Experimental Design and Data Analysis for Biologists , 2002 .

[58]  J. Kadane,et al.  Placebos that harm: sham surgery controls in clinical trials , 2002, Statistical methods in medical research.

[59]  A. Dawid Influence Diagrams for Causal Modelling and Inference , 2002 .

[60]  Sander Greenland,et al.  An overview of relations among causal modelling methods. , 2002, International journal of epidemiology.

[61]  J. Pearl REPLY TO WOODWARD , 2003, Economics and Philosophy.

[62]  Tom Burr,et al.  Causation, Prediction, and Search , 2003, Technometrics.

[63]  J. Pearl Statistics and causal inference: A review , 2003 .

[64]  Jin Tian,et al.  Probabilities of causation: Bounds and identification , 2000, Annals of Mathematics and Artificial Intelligence.

[65]  N. Wermuth,et al.  Causality: a Statistical View , 2004 .

[66]  Paul Humphreys,et al.  Are There Algorithms That Discover Causal Structure? , 1999, Synthese.

[67]  D. Rubin Direct and Indirect Causal Effects via Potential Outcomes * , 2004 .

[68]  Gregory F. Cooper,et al.  A Bayesian method for the induction of probabilistic networks from data , 1992, Machine Learning.

[69]  G. Guyatt,et al.  Grading quality of evidence and strength of recommendations , 2004, BMJ : British Medical Journal.

[70]  Ned Hall,et al.  Causation and counterfactuals , 2004 .

[71]  J. Woodward Making Things Happen: A Theory of Causal Explanation , 2003 .

[72]  Roger Brent,et al.  A Fishing Buddy for Hypothesis Generators , 2005, Science.

[73]  Jon Williamson,et al.  Bayesian Nets and Causality: Philosophical and Computational Foundations , 2005 .

[74]  Chen Avin,et al.  Identifiability of Path-Specific Effects , 2005, IJCAI.

[75]  Kevin Murphy,et al.  Active Learning of Causal Bayes Net Structure , 2006 .

[76]  Judea Pearl,et al.  Identification of Conditional Interventional Distributions , 2006, UAI.

[77]  Bernard Manderick,et al.  Learning Causal Bayesian Networks from Observations and Experiments: A Decision Theoretic Approach , 2006, MDAI.

[78]  Judea Pearl,et al.  Identification of Joint Interventional Distributions in Recursive Semi-Markovian Causal Models , 2006, AAAI.

[79]  D. Rubin Matched Sampling for Causal Effects , 2006 .

[80]  Kevin B. Korb,et al.  The power of intervention , 2006, Minds and Machines.

[81]  Paul M. B. Vitányi,et al.  Meaningful Information , 2001, IEEE Transactions on Information Theory.

[82]  Mark J van der Laan,et al.  Estimation of Direct Causal Effects , 2006, Epidemiology.

[83]  Kiyoko F. Aoki-Kinoshita,et al.  From genomics to chemical genomics: new developments in KEGG , 2005, Nucleic Acids Res..

[84]  Judea Pearl,et al.  What Counterfactuals Can Be Tested , 2007, UAI.

[85]  John Worrall,et al.  Why There's No Cause to Randomize , 2007, The British Journal for the Philosophy of Science.

[86]  Steven G. Epstein,et al.  Inclusion: The Politics of Difference in Medical Research , 2007 .

[87]  Richard E. Neapolitan,et al.  Learning Bayesian networks , 2007, KDD '07.

[88]  H. White,et al.  An Extended Class of Instrumental Variables for the Estimation of Causal Effects , 2011 .

[89]  Nancy Cartwright,et al.  Hunting Causes and Using Them: Against modularity, the causal Markov condition and any link between the two: comments on Hausman and Woodward , 2007 .

[90]  Lawrence F. Katz,et al.  What Can We Learn about Neighborhood Effects from the Moving to Opportunity Experiment?1 , 2008, American Journal of Sociology.

[91]  Onyebuchi A Arah,et al.  The role of causal reasoning in understanding Simpson's paradox, Lord's paradox, and the suppression effect: covariate selection in the analysis of observational studies , 2008, Emerging themes in epidemiology.

[92]  Isabelle Guyon,et al.  Design and Analysis of the Causation and Prediction Challenge , 2008, WCCI Causation and Prediction Challenge.

[93]  Erik Weber,et al.  Counterfactuals and causal inference: methods and principles for social research , 2008 .

[94]  D. Rubin Should observational studies be designed to allow lack of balance in covariate distributions across treatment groups? , 2009 .

[95]  Judea Pearl,et al.  Letter to the Editor: Remarks on the Method of Propensity Score , 2009 .

[96]  J. Pearl Myth, Confusion, and Science in Causal Analysis , 2009 .

[97]  Jon Williamson Probabilistic Theories of Causality , 2009 .

[98]  Nancy Cartwright,et al.  How to do things with causes. , 2009 .

[99]  Isabelle Guyon,et al.  Causality : Objectives and Assessment , 2010 .

[100]  J. Reiss Error in economics: the methodology of evidence-based economics , 2010 .

[101]  Judea Pearl,et al.  Mediating Instrumental Variables , 2011 .

[102]  Sander Greenland,et al.  Causal Diagrams , 2011, International Encyclopedia of Statistical Science.