Causality

Number Of Volumes: 4
Stephen P. Turner
SAGE Benchmarks in Social Research Methods
Causality
January 2010 | 1704 pages | Sage UK
Create Flyer

Purchase

Hardcover
ISBN: 9781847879332
Available from January 0001

Description

Causality is a core problem in social science methodology, as the laws of causality found in physics – which state generalizations without exceptions - are not found in the social sciences. As a consequence, classical definitions of the causal relation, such as John Stuart Mill's definition in terms of invariant succession, need either to be modified and qualified, or replaced by a different concept of causality entirely. This has lead to a long and complex literature on the problems of causality.

This four volume major reference work covers the main issues, methods of analysis, and alternatives, of causality, including the classic texts applying these alternative concepts and methods to empirical cases. The volumes give a substantial historical and philosophical introduction relevant to the concerns of practitioners. As a whole, the volumes represent a complete guide to the literature on social science causality from the beginning to the present.

Contents

VOLUME 1

  • On the Study of Causes
  • Quetelet on Probabilities
  • Causation
  • Mariage
  • The Scientific Law
  • Cause and Effect-Probability
  • Contingency and Correlation-the Insufficiency of Causation
  • On the Correlation of Total Pauperism with Proportion of Out-Relief
  • An Investigation into the Causes in Pauperism in England, Chiefly During the Last Two Intercensal Decades
  • Partial Association

VOLUME 2

  • The Generalizing Theories: Adequate cause
  • Concerning Cause and the Law of Torts
  • Causation in Tort Law
  • Causal Ordering and Identifiability
  • Spurious Correlation: A causal interpretation
  • Correlation and Causality: The multivariate case
  • The Introduction of Additional Variables and the Problem of Spuriousness
  • The Introduction of Additional Variables and the Elaboration of Analysis
  • The Environment and Disease: Association or causation?
  • Investigating Causal Relations by Econometric Models and Cross-spectral Models
  • Spurious Regressions in Econometrics
  • Testing for Causality: A personal viewpoint
  • Statistics and Causal Inference
  • Statistics and Causal Inference: Comment: Which ifs have causal answers?
  • Statistics and Causal Inference: Comment
  • Statistics and Causal Inference: Comment: Statistics and metaphysics
  • Statistics and Causal Inference: Comment
  • Statistics and Causal Inference: Rejoinder
  • Causal Inference, Path Analysis, and Recursive Structural Equations Models
  • Dangers of Cigarette Smoking
  • Cigarettes, Cancer, and Statistics
  • The Nature of Probability
  • Lung Cancer and Cigarettes
  • Cancer and Smoking
  • Inhaling
  • Review
  • Sample Selection Bias as a Specification Error
  • Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: The case of manpower training
  • Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: The case of manpower training: Comment
  • Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: The case of manpower training: Comment
  • Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: The case of manpower training: Rejoinder

VOLUME 3

  • Graphs, Causality, and Structural Equation Models
  • Confounding and Collapsibility in Causal Inference
  • Causal Diagrams for Empirical Research
  • Graphical Models for Causation, and the Identification Problem
  • Measures of Association for Cross Classifications
  • Simple Models for the Analysis of Association in Cross-classifications Having Ordered Categories
  • The Multivariate Analysis of Qualitative Data: Interactions among multiple classifications
  • The Analysis of Cross-classified Data: Independence, quasi-independence, and interactions in contingency tables with or without missing entries
  • The Central Role of the Propensity Score in Observational Studies for Causal Effects
  • Estimating Causal Effects of Treatments in Randomized and Nonrandomized Studies
  • Constructing a Control Group Using Multivariate Matched Sampling Methods that Incorporate the Propensity Score
  • Reducing Bias in Observational Studies Using Subclassification on the Propensity Score
  • Identification of Causal Effects Using Instrumental Variables
  • Bayesian Inference for Causal Effects: The role of randomization
  • Estimating Causal Effects from Large Data Sets Using Propensity Scores
  • Assignment of Treatment Group on the Basis of a Covariate
  • From Association to Causation in Observational Studies: The role of tests of strongly ignorable treatment assignment
  • Notes on the Theory of Association of Attributes in Statistics
  • The Interpretation of Interaction in Contingency Tables
  • On Simpson's Paradox and the Sure-thing Principle
  • Confounding and Simpson's Paradox
  • Comment on: 'Confounding and Simpson's Paradox'
  • Ecological Correlations and the Behavior of Individuals
  • Social experiments: Some developments over the past fifteen years
  • The Moderator-mediator Variable Distinction in Social Psychological Research: Conceptual, strategic and statistical considerations

VOLUME 4

  • Causal Laws and Effective Strategies
  • Causes and Conditions
  • Causation
  • Causation
  • Causation as Influence
  • Small n's and Big Conclusions: An examination of the reasoning in comparative studies based on a small number of cases
  • Utilizing Causal Models to Discover Flaws in Experiments
  • Statistical Models and Shoe Leather
  • From Association to Causation Via Regression
  • Nuisance Variables and the Ex Post Facto Design
  • The Path Analysis Controversy: A new statistical approach to strong appraisal of verisimilitude

Description

Causality is a core problem in social science methodology, as the laws of causality found in physics – which state generalizations without exceptions - are not found in the social sciences. As a consequence, classical definitions of the causal relation, such as John Stuart Mill's definition in terms of invariant succession, need either to be modified and qualified, or replaced by a different concept of causality entirely. This has lead to a long and complex literature on the problems of causality.

This four volume major reference work covers the main issues, methods of analysis, and alternatives, of causality, including the classic texts applying these alternative concepts and methods to empirical cases. The volumes give a substantial historical and philosophical introduction relevant to the concerns of practitioners. As a whole, the volumes represent a complete guide to the literature on social science causality from the beginning to the present.

Contents

VOLUME 1

  • On the Study of Causes
  • Quetelet on Probabilities
  • Causation
  • Mariage
  • The Scientific Law
  • Cause and Effect-Probability
  • Contingency and Correlation-the Insufficiency of Causation
  • On the Correlation of Total Pauperism with Proportion of Out-Relief
  • An Investigation into the Causes in Pauperism in England, Chiefly During the Last Two Intercensal Decades
  • Partial Association

VOLUME 2

  • The Generalizing Theories: Adequate cause
  • Concerning Cause and the Law of Torts
  • Causation in Tort Law
  • Causal Ordering and Identifiability
  • Spurious Correlation: A causal interpretation
  • Correlation and Causality: The multivariate case
  • The Introduction of Additional Variables and the Problem of Spuriousness
  • The Introduction of Additional Variables and the Elaboration of Analysis
  • The Environment and Disease: Association or causation?
  • Investigating Causal Relations by Econometric Models and Cross-spectral Models
  • Spurious Regressions in Econometrics
  • Testing for Causality: A personal viewpoint
  • Statistics and Causal Inference
  • Statistics and Causal Inference: Comment: Which ifs have causal answers?
  • Statistics and Causal Inference: Comment
  • Statistics and Causal Inference: Comment: Statistics and metaphysics
  • Statistics and Causal Inference: Comment
  • Statistics and Causal Inference: Rejoinder
  • Causal Inference, Path Analysis, and Recursive Structural Equations Models
  • Dangers of Cigarette Smoking
  • Cigarettes, Cancer, and Statistics
  • The Nature of Probability
  • Lung Cancer and Cigarettes
  • Cancer and Smoking
  • Inhaling
  • Review
  • Sample Selection Bias as a Specification Error
  • Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: The case of manpower training
  • Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: The case of manpower training: Comment
  • Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: The case of manpower training: Comment
  • Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: The case of manpower training: Rejoinder

VOLUME 3

  • Graphs, Causality, and Structural Equation Models
  • Confounding and Collapsibility in Causal Inference
  • Causal Diagrams for Empirical Research
  • Graphical Models for Causation, and the Identification Problem
  • Measures of Association for Cross Classifications
  • Simple Models for the Analysis of Association in Cross-classifications Having Ordered Categories
  • The Multivariate Analysis of Qualitative Data: Interactions among multiple classifications
  • The Analysis of Cross-classified Data: Independence, quasi-independence, and interactions in contingency tables with or without missing entries
  • The Central Role of the Propensity Score in Observational Studies for Causal Effects
  • Estimating Causal Effects of Treatments in Randomized and Nonrandomized Studies
  • Constructing a Control Group Using Multivariate Matched Sampling Methods that Incorporate the Propensity Score
  • Reducing Bias in Observational Studies Using Subclassification on the Propensity Score
  • Identification of Causal Effects Using Instrumental Variables
  • Bayesian Inference for Causal Effects: The role of randomization
  • Estimating Causal Effects from Large Data Sets Using Propensity Scores
  • Assignment of Treatment Group on the Basis of a Covariate
  • From Association to Causation in Observational Studies: The role of tests of strongly ignorable treatment assignment
  • Notes on the Theory of Association of Attributes in Statistics
  • The Interpretation of Interaction in Contingency Tables
  • On Simpson's Paradox and the Sure-thing Principle
  • Confounding and Simpson's Paradox
  • Comment on: 'Confounding and Simpson's Paradox'
  • Ecological Correlations and the Behavior of Individuals
  • Social experiments: Some developments over the past fifteen years
  • The Moderator-mediator Variable Distinction in Social Psychological Research: Conceptual, strategic and statistical considerations

VOLUME 4

  • Causal Laws and Effective Strategies
  • Causes and Conditions
  • Causation
  • Causation
  • Causation as Influence
  • Small n's and Big Conclusions: An examination of the reasoning in comparative studies based on a small number of cases
  • Utilizing Causal Models to Discover Flaws in Experiments
  • Statistical Models and Shoe Leather
  • From Association to Causation Via Regression
  • Nuisance Variables and the Ex Post Facto Design
  • The Path Analysis Controversy: A new statistical approach to strong appraisal of verisimilitude

January 2010 | 1704 pages | Sage UK

Format Published Date ISBN Price
Hardcover 31/03/2026 9781847879332 $1307.00

Causality is a core problem in social science methodology, as the laws of causality found in physics – which state generalizations without exceptions - are not found in the social sciences. As a consequence, classical definitions of the causal relation, such as John Stuart Mill's definition in terms of invariant succession, need either to be modified and qualified, or replaced by a different concept of causality entirely. This has lead to a long and complex literature on the problems of causality.

This four volume major reference work covers the main issues, methods of analysis, and alternatives, of causality, including the classic texts applying these alternative concepts and methods to empirical cases. The volumes give a substantial historical and philosophical introduction relevant to the concerns of practitioners. As a whole, the volumes represent a complete guide to the literature on social science causality from the beginning to the present.


Table Of Contents:

  • VOLUME 1
  • On the Study of Causes
  • Quetelet on Probabilities
  • Causation
  • Mariage
  • The Scientific Law
  • Cause and Effect-Probability
  • Contingency and Correlation-the Insufficiency of Causation
  • On the Correlation of Total Pauperism with Proportion of Out-Relief
  • An Investigation into the Causes in Pauperism in England, Chiefly During the Last Two Intercensal Decades
  • Partial Association
  • VOLUME 2
  • The Generalizing Theories: Adequate cause
  • Concerning Cause and the Law of Torts
  • Causation in Tort Law
  • Causal Ordering and Identifiability
  • Spurious Correlation: A causal interpretation
  • Correlation and Causality: The multivariate case
  • The Introduction of Additional Variables and the Problem of Spuriousness
  • The Introduction of Additional Variables and the Elaboration of Analysis
  • The Environment and Disease: Association or causation?
  • Investigating Causal Relations by Econometric Models and Cross-spectral Models
  • Spurious Regressions in Econometrics
  • Testing for Causality: A personal viewpoint
  • Statistics and Causal Inference
  • Statistics and Causal Inference: Comment: Which ifs have causal answers?
  • Statistics and Causal Inference: Comment
  • Statistics and Causal Inference: Comment: Statistics and metaphysics
  • Statistics and Causal Inference: Comment
  • Statistics and Causal Inference: Rejoinder
  • Causal Inference, Path Analysis, and Recursive Structural Equations Models
  • Dangers of Cigarette Smoking
  • Cigarettes, Cancer, and Statistics
  • The Nature of Probability
  • Lung Cancer and Cigarettes
  • Cancer and Smoking
  • Inhaling
  • Review
  • Sample Selection Bias as a Specification Error
  • Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: The case of manpower training
  • Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: The case of manpower training: Comment
  • Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: The case of manpower training: Comment
  • Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: The case of manpower training: Rejoinder
  • VOLUME 3
  • Graphs, Causality, and Structural Equation Models
  • Confounding and Collapsibility in Causal Inference
  • Causal Diagrams for Empirical Research
  • Graphical Models for Causation, and the Identification Problem
  • Measures of Association for Cross Classifications
  • Simple Models for the Analysis of Association in Cross-classifications Having Ordered Categories
  • The Multivariate Analysis of Qualitative Data: Interactions among multiple classifications
  • The Analysis of Cross-classified Data: Independence, quasi-independence, and interactions in contingency tables with or without missing entries
  • The Central Role of the Propensity Score in Observational Studies for Causal Effects
  • Estimating Causal Effects of Treatments in Randomized and Nonrandomized Studies
  • Constructing a Control Group Using Multivariate Matched Sampling Methods that Incorporate the Propensity Score
  • Reducing Bias in Observational Studies Using Subclassification on the Propensity Score
  • Identification of Causal Effects Using Instrumental Variables
  • Bayesian Inference for Causal Effects: The role of randomization
  • Estimating Causal Effects from Large Data Sets Using Propensity Scores
  • Assignment of Treatment Group on the Basis of a Covariate
  • From Association to Causation in Observational Studies: The role of tests of strongly ignorable treatment assignment
  • Notes on the Theory of Association of Attributes in Statistics
  • The Interpretation of Interaction in Contingency Tables
  • On Simpson's Paradox and the Sure-thing Principle
  • Confounding and Simpson's Paradox
  • Comment on: 'Confounding and Simpson's Paradox'
  • Ecological Correlations and the Behavior of Individuals
  • Social experiments: Some developments over the past fifteen years
  • The Moderator-mediator Variable Distinction in Social Psychological Research: Conceptual, strategic and statistical considerations
  • VOLUME 4
  • Causal Laws and Effective Strategies
  • Causes and Conditions
  • Causation
  • Causation
  • Causation as Influence
  • Small n's and Big Conclusions: An examination of the reasoning in comparative studies based on a small number of cases
  • Utilizing Causal Models to Discover Flaws in Experiments
  • Statistical Models and Shoe Leather
  • From Association to Causation Via Regression
  • Nuisance Variables and the Ex Post Facto Design
  • The Path Analysis Controversy: A new statistical approach to strong appraisal of verisimilitude

Recent Product Reviews:

Recommendations