This chapter investigates whether Salmon's account of causality in terms of physical processes and interactions makes justice of the type of causal claims made in social contexts. Based on some paradigmatic case studies from the social sciences (e.g. demography, epidemiology, or econometrics), it is argued that social scientists (i) use statistical causality to detect causal relations, (ii) state causal claims in causal contexts, (iii) look for specific variations to test, and (iv) model causal mechanisms by means of statistical tools.
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Bibliography
Abbott, A. (1998). The causal devolution. Sociological Methods and Research, 27(2), 148–181.
Adams, P., Hurd, M., McFadden, D., Merrill, A., Ribeiro, T. (2003). Healthy, wealthy, and wise? Tests for direct causal paths between health and socioeconomic status. Journal of Econometrics, 112, 3–56. With discussion.
Agresti, A. (1996). An introduction to categorical data analysis. New York: Wiley.
Aish-Van Vaerenbergh, A. -M. (1994). Modèles statistiques et inférences causales: analyse des structures de covariances avec LISREL. In R. Franck (Ed.), Faut-il chercher aux causes uneraison? (pp. 106–130). Paris: Vrin.
Aish-Van Vaerenbergh, A. -M. (2002). Explanatory models in suicide research: explaining relationships. In R. Franck (Ed.), The explanatory power of models (pp. 51–66). Dordrecht: Kluwer.
Aristotle (1928). Metaphysics. Translated by W. D. Ross, The works of Aristotle translated into English, vol. 8, Second edition. Oxford: Clarendon.
Atmanspacher, H., Bishop, R. (2002) (Ed.). Between chance and choice: interdisciplinary perspectives on determinism. Thoverton: Imprint Academic.
Bayarri, S., Berger, J. O. (2000). P-values for composite null models. Journal of the American Statistical Association, 95(452), 1127–1142. With discussion.
Beck, W., van der Maeson, L., Walker, A. (2001). Introduction: who and what is the European Union for? In W. Beck, L. van der Maeson, G. Thomése, A. Walker (Ed.), Social quality: a vision for Europe (pp. 1–18). The Hague: Kluwer Law International.
Berger, J. O., Boukai, B., Wang, Y. (1997). Unified frequentist and Bayesian testing of a precise hypothesis. Statistical Science, 12(3), 133–160.
Berger, J. O., Delampady, M. (1987). Testing precise hypotheses. Statistical Science, 3(2), 317–335.
Berger, J. O.,Guglielmi, A. (2001). Bayesian and conditional frequentist testing of a parametric model versus nonparametric alternatives. Journal of the American Statistical Association, 96(453), 174–184.
Berger, J. O., Guglielmi, A. (2001). Bayesian and conditional frequentist testing of a parametric model versus nonparametric alternatives. Journal of the American Statistical Association, 96(453), 174–184.
Berkovitz, J. (2002). On causal inference in determinism and indeterminism. In H. Atmanspacher, R. Bishop (Ed.), Between chance and choice: interdisciplinary perspectives on determinism (pp. 237–278). Thoverton: Imprint Academic.
Bernardo, J. M. (1980). A Bayesian analysis of classical hypothesis testing. In J. Bernardo, M. H. DeGroot, D. V. Lindley, A. F. M. Smith (Ed.), Bayesian statistics (pp. 605–647). Valencia: Valencia University Press. With discussion.
Bessie, J. D. (1993). On the strength of a causal chain. Pacific Philosophical Quarterly, 74(1), 11–36.
Blalock, H. M. (1964). Causal inferences in nonexperimental research. Chapel Hill: University of North Carolina Press.
Blalock, H. M. (1968a). The measurement problem: a gap between the languages of theory and research. In H. M. Jr. Blalock, A. Blalock (Ed.), Methodology in social research (pp. 5–27). New York: McGraw Hill.
Blalock, H. M. (1968b). Theory building and causal inferences. In H. M. Jr. Blalock, A. Blalock (Ed.), Methodology in social research (pp. 155–198). New York: McGraw Hill.
Boudon, R. (1967). L'analyse mathe‘matique des faits sociaux. Paris: Plon.
Boudon, R., Lazarfeld, P. (1966) (Ed.). L'analyse empirique de la causalite’;. Paris: Mouton & Co.
Bovens, L., Hartmann, S. (2003). Bayesian epistemology. Oxford: Clarendon Press.
Bunge, M. A. (1979a). Causality and modern science. New York: Dover. Third revised edtion.
Bunge, M. A. (1979b). A world of systems. Dordrecht: Reidel Publishing Company.
Bunge, M. A. (1996). Finding philosophy in social science. New Haven, CT: Yale University Press.
Bunge, M. A. (1998). Social science under debate: a philosophical perspective. Toronto: University of Toronto Press.
Bunge, M. A. (2004). How does it work? The search for explanatory mechanisms. Philosophy of the Social Sciences, 34(2), 182–210.
Caldwell, J. C. (1979). Education as a factor in mortality decline: an examination of Nigerian data. Population Studies, 33(3), 395–413.
Campbell, D. T., Stanley, J. C. (1963). Experimental and quasi-experimental designs for research. Chicago: Rand McNally.
Carnap, R. (1951). The logical foundations of probability. Chicago: University of Chicago Press. Second edition.
Carroll, J. W. (2003). Laws of nature. In E. N. Zalta (Ed.), The Stanford encyclopaedia of philosophy. (Fall 2003 edition). http://plato.stanford.edu/archives/fall2003/entries/laws-of-nature/. Accessed 12 March 2008.
Cartwright, N. (1979). Causal laws and effective strategies. Noûs, 13(4), 419–437.
Cartwright, N. (1989). Nature's capacities and their measurements. Oxford: Clarendon Press.
Cartwright, N. (1995). Précis of ‘Nature's capacities and their measurement’. Philosophy and Phenomenological Research, 55(1), 153–156.
Cartwright, N. (1997). What is a causal structure? In V. McKim, S. P. Turner (Ed.), Causality in crisis? Statistical methods and the search for causal knowledge in the social sciences (pp. 343–357). Indiana: University of Notre Dame Press.
Cartwright, N. (1999). Causal diversity and Markov condition. Synthese, 121, 3–27.
Cartwright, N. (2000). Measuring causes: invariance, modularity and the causal Markov condition. Measurement in physics and economics discussion paper series. Centre for Philosophy of Natural and Social Science, 10/00.
Cartwright, N. (2002). Against modularity, the causal Markov condition, and any link between the two: comments on Hausman and Woodward. British Journal for the Philosophy of Science, 53(3), 411–453.
Cartwright, N. (2007a). Hunting causes and using them: approaches in philosophy and economics. Cambridge: Cambridge University Press.
Cartwright, N. (2007b). Are RCTs the gold standard? Bio Societies, 2, 11–20.
Chakravartty, A. (2005). Causal realism: events and processes. Erkenntnis, 63, 7–31.
Cohen, J. L. (1989). An introduction to the philosophy of induction and probability. Oxford: Clarendon Press.
Collingwood, R. (1940/1998). An essay on metaphysics. Oxford: Clarendon Press.
Cook, T. D., Campbell D. T. (1979). Quasi-experimentation. Design and analysis issues for field settings. Chicago: Rand MacNally.
Cook, T. D., Campbell D. T. (1986). The causal assumptions of quasi-experimental practice. Synthese, 68, 141–180.
Corfield, D., Williamson J. (2001) (Ed.). Foundations of Bayesianism. Dordrecht: Kluwer.
Courgeau, D. (1994). Du groupe à l'individu: l'exemple des comportements migratoires. Population, 1, 7–26.
Courgeau, D. (2002). Vers une analyse biographique multiniveaux. In M. Christine (Ed.), Actes des journeés de méthodologie statistique (pp. 375–394), INSEE méthodes 101.
Courgeau, D. (2003) (Ed.). Methodology and epistemology of multilevel analysis. Approaches from different social sciences. Dordrecht: Kluwer.
Courgeau, D. (2004a). Du groupe àl'individu: synthése multiniveau. Paris: Editions de l'INED.
Courgeau, D. (2004b). Probabilité, démographie et sciences sociales. Mathématiques et sciences humaines/Mathematics and Social Sciences, 167(3), 27–50.
Courgeau, D. (2007a). Multilevel synthesis: from the group to the individual. Dordrecht: Springer.
Courgeau, D. (2007b). Inférence statistique, échangeabilité et approche multiniveau. Mathématique et sciences humaines/Mathematics and Social Sciences, 179(3), 5é19.
Cox, D. R. (1992). Causality: some statistical aspects. Journal of the Royal Statistical Society, 155(2), 291é301.
Cox, R. T. (1946). Probability, frequency, and reasonable expectation. American Journal of Physics, 14(1), 1–13.
Cox, D. T. (2000). Causal inference without counterfactuals: commentary. Journal of the American Statistical Association, 95, 424–425.
Dawid, A. P. (1982). The well-calibrated Bayesian. Journal of the American Statistical Association, 77(379), 605–610.
Dawid, A. P. (2000). Causal inference without counterfactuals. Journal of the American Statistical Association, 95, 407–427.
Dawid, A. P. (2002a). Influence diagrams for causal modelling and inference. International Statistical Review, 70, 161–189. Corrigenda, ibidem, 437.
Dawid, A. P. (2002b). Commentary: counterfactuals: help or hindrance? International Journal of Epidemiology, 31, 429–430.
Dawid, A. P. (2007). Counterfactuals, hypotheticals and potential responses: a philosophical examination of statistical causality. In F. Russo, J. Williamson (Ed.), Causality and probability in the sciences (pp. 503–532). London: College Publications.
de Finetti, B. (1937). Foresight. Its logical laws, its subjective sources. In H. E. Kyburg, H. E. Smokler (Ed.), Studies in subjective probability (pp. 194–207). Huntington, New York: Wiley.
de Finetti, B. (1993). Probabilitàe induzione. Induction and probability. Edited by D. Montanari, D. Cocchi. Bologna: CLUEB.
Dowe, P. (1992). Wesley Salmon's process theory of causality and the conserved quantity theory. Philosophy of Science, 59, 195–216.
Drèze, J. H., Mouchart, M. (1990). Tales of testing Bayesians. In R. A. L. Carter, J. Dutta, A. Ullah (Ed.), Contributions to econometric theory and applications - Essays in honour of A. L. Nagar (pp. 345–366). New York: Springer.
Droesbeke, J.-J., Fine, J., Saporta, G. (2002). M èthodes bayèsiennes en statistique. Paris: Technip.
Ducasse, J. C. (1926). On the nature and observability of the causal relation. Journal of Philosophy, 23, 57–68.
Duchêne, J., Wunsch, G. (1985). From theory to statistical model. In IUSSP, International Population Conference (pp. 209–224), Volume 2. Liège: Ordina.
Duchêne, J., Wunsch, G. (1989). Conceptual frameworks and causal modelling. In L. Ruzicka, G. Wunsch, P. Kane (Ed.), Differential mortality. Methodological issues and biosocial factors (pp. 21–35). Oxford: Clarendon.
Duchêne, J., Wunsch, G. (1989) (Ed.). L'explication en sciences sociales: la recherche des causesen dèmographie. Chaire Quetelet 1987. Louvain-la-Neuve: CIACO.
Duchêne, J., Wunsch, G. (2006). Causalitè et modèles causaux. In G. Caselli, J. Vallin, G. Wunsch (Ed.), D èmographie: analyse et synthèse (pp. 315–334), Volume VIII, Observation, mèthodes auxiliaires, enseignement et recherche. Paris: Editions de l'Institut National d'Etudes Dèmographiques.
Duncan, O. D. (1975). Introduction to structural equation models. New York: Academic Press.
Dupré, J., Cartwright, N. (1988). Probability and causality: why Hume and indeterminism don't mix. Noûs, 22(4), 521–536.
Durkheim, E. (1895/1912). Les règles de la méthode sociologique. Paris: Libraire Félix Arcan. Sixth edition.
Durkheim, E. (1897/1960). Le suicide. Paris: Presses Universitaires de France.
Edwards, A. W. F. (1972). Likelihood. An account of the statistical concept of likelihood and its application to scientific inference. Cambridge: Cambridge University Press.
Edwards, A. W. F. (1997). What did Fisher mean by ‘inverse probability’ in 1912–1922? Statistical Science, 12(3), 177–184.
Eells, E. (1991). Probabilistic causality. Cambridge: Cambridge University Press.
Eells, E., Sober, E. (1983). Probabilistic causality and the question of transitivity. Philosophy of Science, 50, 35–57.
Ehring, D. (1984). Probabilistic causality and pre-emption. British Journal for the Philosophy of Science, 35, 55–57.
Ellett, F. S., Ericson, D. P. (1983). The logic of causal methods in social science. Synthese, 57, 67–82.
Ellett, F. S., Ericson, D. P. (1984). Probabilistic causal systems and the conditional probability approach to causal analysis. Quality and Quantity, 18, 247–259.
Ellett, F. S., Ericson, D. P. (1986a). Correlation, partial correlation, and causation. Synthese, 67, 157–173.
Ellett, F. S., Ericson, D. P. (1986b). An analysis of probabilistic causation in dichotomous structures. Synthese, 67, 175–193.
Ellett, F. S., Ericson, D. P. (1989). Causal modelling and theories of causation. In J. Duchêne, G. Wunsch (Ed.), L'explication en sciences sociales: la recherche des causes en dèmographie (pp. 397–424). Chaire Quetelet 1987. Louvain-la-Neuve: CIACO.
Engle, R. F., Hendry, D. F., Richard, J. -F. (1983). Exogeneity. Econometrica, 51(2), 277–304.
Fetzer, J. (1988) (Ed.), Probability and causality. Dordrecht: Reidel.
Fisher, R. A. (1922). On the mathematical foundations of theoretical statistics. Philosophical Transactions of the Royal Society of London, 222, 309–368.
Fisher, R. A. (1925). Statistical methods for research workers. London: Oliver and Boyd. http://psychclassics.yorku.ca/Fisher/Methods/. Accessed 14 March 2008.
Fisher, R. A. (1930). Inverse probability. Proceeding of the Cambridge Philosophical Society, 26, 528–535.
Fisher, R. A. (1935). The logic of inductive inference. Journal of the Royal Statistical Society, 98(1), 39–82.
Florens, J. -P., Mouchart, M. (1989). Bayesian specification tests. In B. Cornet, H. Tulkens (Ed.), Contributions in operations research and economics (pp. 467–490). Cambridge: MIT Press.
Florens, J. -P., Mouchart, M. (1993). Bayesian testing and testing Bayesians. In G. S. Maddala, C. R. Rao (Ed.), Hand-book of statistics (pp. 303–334). Amsterdam: North Holland.
Franck, R. (1994) (Ed.). Faut-il chercher aux causes une raison? Paris: Vrin.
Franck, R. (1995). MosaÏques, machines, organismes et sociètès. Revue Philosophique de Louvain, 93(1–2), 67–81.
Franck, R. (2002) (Ed.). The explanatory power of models. Dordrecht: Kluwer.
Franck, R. (2003). Causal analysis, systems analysis, and multilevel analysis: philosophy and epistemology. In D. Courgeau (Ed.), Methodology and epistemology of multilevel analysis. Approaches from different social sciences (pp. 175–198). Dordrecht: Kluwer.
Freedman, D. A. (1999). From association to causation: some remarks on the history of statistics. Statistical Science, 14(3), 243–258.
Freedman, D. A. (2004a). Statistical models for causation. Technical Report 651. http://www.stat.berkeley.edu/census/651.pdf. Accessed 14 March 2008.
Freedman, D. A. (2004b). On specifying graphical models for causation, and the identification problem. Evaluation Review, 26, 267–93.
Freedman, D. A. (2005). Statistical models. Theory and practice. Cambridge: Cambridge University Press.
Freedman, D., Pisani, R., Purves, R. (1998). Statistics. New York: W.W. Norton. First edition.
Fried, H. O, Schmidt, S. S., Lovell, K. (1993) (Ed.). The measurement of productive efficiency. New York: Oxford University Press.
Galavotti, M. C., Suppes, P., Costantini, D. (2001) (Ed.), Stochastic causality. Stanford: CSLI.
Gasking, D. (1955). Causation and recipes. Mind, 64, 479–487.
Gérard, H. (1989). Théories et théorisation. In J. Duchêne, G. Wunsch (Ed.), L'explication en sciences sociales. La recherche des causes en démographie (pp. 267–281). Chaire Quetelet 1987. Louvain-la-Neuve: CIACO.
Gérard, H. (2006). De la théorisation en démographie. In G. Caselli, J. Vallin, G. Wun-sch (Ed.), D émographie: analyse et synthèse (pp. 291–314). Volume VIII, Observation, méthodes auxiliaires, enseignement et recherche, Paris: Editions de l'Institut National d'Etudes Démographiques.
Giere, R. (1984). Causal models with frequency dependence. Journal of Philosophy, 81, 384–391.
Giere, R. (1999), Science without laws. Chicago: University of Chicago Press.
Gillies, D. (2000). Philosophical theories of probability. London: Routledge.
Glymour, C., Scheines, R. (1986). Causal modeling with the TETRAD program. Synthese, 68, 37–64.
Glymour, C., Scheines, R., Spirtes, P., Kelly K. (1987). Discovering causal structure: artificial intelligence, philosophy of science, and statistical modelling. San Diego: Academic.
Goldberger, A. S. (1972). Structural equation methods in the social sciences. Econometrica, 40, 979–1001.
Goldstein, H. (1987). Multilevel models in educational and social research. London: Griffin.
Goldstein, H. (2003). Multilevel statistical models. Kendall's Library of Statistics, 3. London: Arnold.
Good, I. J. (1959). A theory of causality. British Journal for the Philosophy of Science, 9, 307– 310.
Good, I. J. (1961). A causal calculus I. British Journal for the Philosophy of Science, 11, 305– 18. Reprinted in I. J. Good, Good thinking. The foundations of probability and its applications (pp. 197–217). Minneapolis: University of Minnesota Press.
Good, I. J. (1962), “A causal calculus II”, British Journal for the Philosophy of Science, 12, pp. 43– 51. Reprinted in I. J. Good, Good thinking. The foundations of probability and its applications (pp. 197–217). Minneapolis: University of Minnesota Press.
Good, I. J. (1972). Review of Patrick Suppes ‘A Probabilistic Theory of Causality’. Journal of American Statistical Association, 67(337), 245–246.
Good, I. J. (1977). Explicativity: a mathematical theory of explanation with statistical applications. Proceedings of Royal Society, A 354, 303–330. Reprinted in I. J. Good, Good thinking. The foundations of probability and its applications (pp. 219–236). Minneapolis: University of Minnesota Press.
Good, I. J. (1980). Some comments on probabilistic causality. Pacific Philosophical Quarterly, 61, 301–304.
Good, I. J. (1983a). Good thinking. The foundations of probability and its applications. Minneapolis: University of Minnesota Press.
Good, I. J. (1983b). The philosophy of exploratory data analysis. Philosophy of Science, 50, 283– 295.
Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424–438.
Grawitz, M. (1996). M éthodes des sciences sociales. Paris: Dalloz. Tenth edition.
Greenland, S. (2000). An introduction to instrumental variables for epidemiologists. International Journal of Epidemiology, 29, 722–729.
Grünbaum, A. (1963). Philosophical problems of space and time. New York: Alfred A. Knopf.
Gutiérrez-Fisac, J. L., Regidor, E., Banegas Banegas, J. R., Rodriguez Artalejo, F. (2002). The size of obesity differences associated with educational level in Spain, 1987, and 1995/97. Journal of Epidemiology and Community Health, 56, 457–460.
Haavelmo, T. (1944). The probability approach in econometrics. Econometrica, 12, iii–vi + 1–115.
Hacking, I. (1965). Logic of statistical inference. London: Cambridge University Press.
Hacking, I. (1978). The emergence of probability: a philosophical study of early ideas about probability, induction and statistical inference. Cambridge: Cambridge University Press.
Hage, J., Meeker, B. F. (1988). Social causality. Boston: Unwin Hyman.
Hájek, A. (2003). Interpretations of probability. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Summer 2003 edition). http://plato.stanford.edu/archives/sum2003/entries/probability-interpret/. Accessed 14 March 2008.
Halpern, J., Pearl, J. (2005a). Causes and explanations: a structural-model approach. Part I: Causes. British Journal for the Philosophy of Science, 56, 843–887.
Halpern, J., Pearl, J. (2005b). Causes and explanations: a structural-model approach. Part II: Explanations. British Journal for the Philosophy of Science, 56, 889–911.
Hanson, N. R. (1958). Patterns of discovery: an inquiry into the conceptual foundations of science. Cambridge: Cambridge University Press.
Hausman, D. (1983). Are there causal relations among dependent variables? Philosophy of Science, 50, 58–81.
Hausman, D. (1993). Linking causal and explanatory asymmetry. Philosophy of Science, 60, 435– 451.
Hausman, D. (1998). Causal asymmetries. Cambridge: Cambridge University Press.
Hausman, D., Woodward, J. (1999). Independence, invariance, and the causal Markov condition. British Journal for the Philosophy of Science, 50, 521–583.
Hausman, D., Woodward, J. (2004). Modularity and the causal Markov condition: a restatement. British Journal for the Philosophy of Science, 55, 147–161.
Heckman, J. (2005). The scientific model of causality. Sociological Methodology, 35(1), 1–97.
Hedström, P., Swedberg, R. (1999a) (Ed.). Social mechanisms: an analytical approach to social theory. Cambridge: Cambridge University Press.
Hedström, P., Swedberg, R. (1999b). Social mechanisms: an introductory essay. In P. Hedström, R. Swedberg (Ed.), Social mechanisms: an analytical approach to social theory (pp. 1–31). Cambridge: Cambridge University Press.
Hellevik, O. (1984). Introduction to causal analysis. London: Allen & Unwin.
Hempel, C. G. (1965). Aspects of scientific explanation and other essays. New York: Free Press.
Hempel, C. G., Oppenheim, P. (1948). Studies in the logic of explanation. Philosophy of Science, 15(2), 135–175. Reprinted in C. G. Hempel, Aspects of scientific explanation and other essays (pp. 245–282). New York: Free Press.
Hesslow, G. (1976). Discussion: two notes on the probabilistic approach to causality. Philosophy of Science, 43, 290–292.
Hitchcock, C. (2001). The intransitivity of causation revealed in equations and graphs. Journal of Philosophy, 98(6), 273–299.
Hitchcock, C. (2004) (Ed.). Contemporary debates in philosophy of science. Oxford: Blackwell.
Holland, P. W. (1986). Statistics and causal inference. Journal of the American Statistical Association, 81, 945–970.
Holland, P. W. (1988). Comment: causal mechanism or causal effect? Which is best for statistical science? Statistical Science, 3(2), 186–188.
Holland, P. W., Rubin, D. B. (1988). Causal inference in retrospective studies. Evaluation Review, 12(3), 203–231.
Hoover, K. D. (2001). Causality in macroeconomics. Cambridge: Cambridge University Press.
Howson, C. (1983). Statistical explanation and statistical support. Erkenntnis, 20, 61–78.
Howson, C. (1988). On a recent argument for the impossibility of a statistical explanation of single events. Erkenntnis, 29, 113–124.
Howson, C. (2001). The logic of Bayesian probability. In D. Corfield, J. Williamson (Ed.), Foundations of Bayesianism (pp. 137–159). Dordrecht: Kluwer.
Howson, C., Urbach, P. (1993). Scientific reasoning: the Bayesian approach. Chicago: Open Court. Second edition.
Hume, D. (1739–1740). A treatise of human nature. Edited by D. F. Norton, M. J. Norton. Oxford/New York: Oxford University Press, 2000.
Hume, D. (1748). An enquiry concerning human understanding. Edited by T. L. Beauchamp. Oxford/New York: Oxford University Press, 1999.
Humphreys, P. (1984). Aleatory explanation expanded. PSA: Proceedings of the Biannual Meeting of the Philosophy of Science Association, 1982, vol. 2, 208–223.
Humphreys, P. (1986a). Causality in the social sciences: an overview. Synthese, 68, 1–12.
Humphreys, P. (1986b). Quantitative probabilistic causality and structural scientific realism. PSA:Proceedings of the Biannual Meeting of the Philosophy of Science Association, 1984, vol. 2, 329–342.
Humphreys, P. (1989). The chances of explanation. Princeton: Princeton University Press.
Irzik, G. (1986). Causal modelling and the statistical analysis of causation. PSA: Proceedings of the Biannual Meeting of the Philosophy of Science Association, 1984, vol. 1: Contributed Papers, 12–23.
Irzik, G. (1996). Can causes be reduced to correlations? British Journal for the Philosophy of Science, 47, 249–270.
Irzik, G., Meyer, E. (1987). Causal modeling: new directions for statistical explanation. Philosophy of Science, 54, 495–514.
Jaynes, E. T. (1957). Information theory and statistical mechanics. The Physical Review, 106(4), 620–630. Reprinted in E. T. Jaynes, E. T. Jaynes: papers on probability, statistics and statistical physics (pp. 4–16). Edited by R. G. Rosenkrantz. Dordrecht: Kluwer.
Jaynes, E. T. (1989). E. T. Jaynes: papers on probability, statistics and statistical physics. Edited by R. G. Rosenkrantz. Dordrecht: Kluwer.
Jaynes, E. T. (2003). Probability theory: the logic of science. Cambridge: Cambridge University Press.
Jeffrey, R. (1966). The logic of decision. Chicago: University of Chicago Press. Second edition 1983.
Jeffreys, H. (1939). Theory of probability. Reprinted, Oxford: Oxford University Press. Oxford Classics in the Physical Sciences Series. 1998.
Kalleberg, A. L. (1977). Work values and job rewards: a theory of job satisfaction. American Sociological Review, 42, 124–143.
Kant, I. (1781). Critique of pure reason. Second edition 1787. Translated by N. K. Smith. London: McMillan. 1929.
Kant, I. (1783). Prolegomena to any future metaphysics. Translated by P. Gray Lucas. Manchester: Manchester University Press. 1953.
Keynes, J. M. (1921). A treatise on probability. London: Macmillan.
Kincaid, H. (1990). Defending laws in the social sciences. Philosophy of the Social Sciences, 20, 56–83.
Kincaid, H. (2004). There are laws in the social sciences. In C. Hitchcock (Ed.), Contemporary debates in philosophy of science (pp. 168–186). Oxford: Blackwell.
Klein, L. R. (1974). A textbook of econometrics. Englewood Cliffs (N.J): Prentice-Hall. Second edition.
Kolmogorov, A. N. (1933). Foundations of the theory of probability. New York: Chelsea Publishing. 1950.
Koopman, B. O. (1940). The axioms and algebra of intuitive probability. Annals of Mathematics, 41, 269–292.
Korb, K., Wallace, C. (1997). In search of the philosopher's stone: remarks on Humphreys and Freedman's critique of causal discovery. British Journal for the Philosophy of Science, 48(4), 543–553.
Kundi, M. (2006). Causality and the interpretation of epidemiological evidence. Environmental Health Perspectives, 114, 969–974.
Kyburg, H. E., Smokler, H. E., (1964) (Ed.). Studies in subjective probability. New York: Wiley.
Lagiou, P., Adami, H. -O., Trichopoulos, D. (2005). Causality in cancer epidemiology. European Journal of Epidemiology, 20, 565–574.
Land, K. C. (1983). Social indicators. Annual Review of Sociology, 9, 1–26.
Laplace, P. (1814). Essai philosophique sur les probabilité s. Paris: Bourgois. 1986.
Larson, J. (1991). The measurement of health: concepts and indicators. New York: Greenwood Press.
Laudisa, F. (1999). Causalità. Storia di un modello di conoscenza. Roma: Carocci Editore.
Lehnmann, E.L. (1966). Some concepts of dependence. Annals of Mathematical Statistics, 37, 1137–1153.
Lewis, D. (1971). A subjectivist guide to objective chance. Reprinted in D. Lewis, Philosophical papers Vol. II (pp. 159–213). Oxford: Oxford University Press. 1986.
Lewis, D. (1973). Causation. Reprinted with postscripts in D. Lewis, Philosophical Papers Vol. II (pp. 159–213). Oxford: Oxford University Press.
Lilienfeld, D. E., Stolley, P. D. (1994). Foundations of epidemiology. New York: Oxford University Press. Third edition.
Little, D. (1990). Varieties of social explanations: an introduction to the philosophy of social science. Boulder: Westview Press.
Little, D. (1993). On the scope and limits of generalizations in the social sciences. Synthese, 97, 183–208.
Little, D. (1995a). Causal explanation in the social sciences. Southern Journal of Philosophy, 34 (Supplement), 31–56.
Little, D. (1995b) (Ed.). On the reliability of economic models: essays in the philosophy of economics. Boston: Kluwer.
Little, D. (1998). Microfoundations, method and causation. On the philosophy of the social sciences. New Brunswick, NJ: Transaction Publishers.
Little, D. (2004). Causal mechanisms. In M. S. Lewis-Beck, A. Bryman, T. F. Liao (Ed.), The Sage Encyclopedia of social science research methods, Vol. 1. Thousand Oaks, CA: Sage.
Long, J. S. (1983a). Confirmatory factor analysis. Beverly Hills: Sage.
Long, J. S. (1983b). Covariance structure models. Beverly Hills: Sage.
López-Ríos, O., Mompart, A., Wunsch, G. (1992). Système de soins et mortalité régionale: une analyse causale. European Journal of Population, 8(4), 363–379.
Mach, E. (1905). Knowledge and error. Dordrecht: Reidel. 1976.
Mackie, J. L. (1974). The cement of the universe: a study on causation. Oxford: Clarendon.
Masuy-Stroobant, G. (2002). The determinants of infant mortality: how far are conceptual frameworks really modelled? In R. Franck (Ed.), The explanatory power of models (pp. 15–30). Dordrecht: Kluwer.
Masuy-Stroobant, G., Gourbin, C. (1995). Infant health and mortality indicators: their accuracy for monitoring the socio-economic development in the Europe of 1994. European Journal of Population, 11(1), 63–84.
Maudlin, T. (2007). The metaphysics within physics. Oxford: Clarendon.
McCullag, P. (1989) (Ed.). Generalized linear models. London: Chapaman & Hall.
McKim, V., Turner, S. P. (1997) (Ed.). Causality in crisis? Statistical methods and the search for causal knowledge in the social sciences. Indiana: University of Notre Dame Press.
Meek, C. (1995). Causal inference and causal explanation with background knowledge. In P. Besnard, S. Hanks (Ed.), Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence (pp. 403–410). San Mateo, CA: Morgan Kaufmann.
Mellor, D. H. (1971). The matter of chance. London: Cambridge University Press.
Menzies, P., Price, H. (1993). Causation as a secondary quality. British Journal for the Philosophy of Science, 44, 187–203.
Mill, J. S. (1843). A system of logic, ratiocinative and inductive: being a connected view of the principles of evidence and the methods of scientific investigation. New York: Harper & Brothers. Eighth edition.
Montuschi, E. (2003). The objects of social science. London: Continuum.
Montuschi, E. (2006). Oggettività e scienze umane. Introduzione alla filosofia della ricerca sociale. Roma: Carocci editore.
Mooney Marini, M., Singer, B. (1988). Causality in the social sciences. Sociological Methodology, 18, 347–409.
Morgan, M. (1997). Searching for causal relations in economic statistics. In V. McKim, S. P. Turner (Ed.), Causality in crisis? Statistical methods and the search for causal knowledge in the social sciences (pp. 47–80). Indiana: University of Notre Dame Press.
Mosley, W. H., Chen, L. C. (1984). An analytical framework for the study of child survival in developing countries. Population and Development Review, 10 (Supplement), 25–45.
Mouchart, M., Russo, F., Wunsch, G. (2008). Structural modelling, exogeneity and causality. In H. Engelhardt, H. -P. Kohler, A. Prskwetz (Ed.), Causal analysis in population studies: concepts, methods, applications (Chapter 4). Dordrecht: Springer.
Mulaik, S. A. (1972). The foundations of factor analysis. New York: McGraw Hill.
Mulaik, S. A. (1985). Exploratory statistics and empiricism. Philosophy of Science, 52, 410–430.
Neter, J., Kutner, M. H., Nachtsheim C. J., Wasserman, W. (1996). Applied linear statistical models. Chicago: Richard D. Irwin. Fourth edition.
Niiniluoto, I. (1981). Statistical explanation reconsidered. Synthese, 48, 437–472.
Norris, P., Inglehart, R. (2003). Islam and the West: testing the ‘clash of civilization‘ thesis. Comparative Sociology, 1(3–4), 235–265. http://ksghome.harvard.edu/˜pnorris/Acrobat/ Clash%20of%20Civilization.pdf. Accessed 14 March 2008.
Otte, R. (1981). A critique of Suppes‘ theory of probabilistic causality. Synthese, 48, 167–189.
Papineau, D. (1985). Causal asymmetry. British Journal for Philosophy of Science, 36(3), 273– 289.
Papineau, D. (1991). Correlation and causes. British Journal for Philosophy of Science, 42(3), 397–412.
Parascandola, M., Weed, D. (2001). Causation in epidemiology. Journal of Epidemiology and Community Health, 55, 905–912.
Pearl, J. (1988a). Probabilistic reasoning in intelligent systems. San Mateo, CA: Morgan Kaufman.
Pearl, J. (1988b). Graphs, causality, and structural equation models. Sociological Methods and Research, 27(2), 226–284.
Pearl, J. (1990). Jeffrey‘s rule, passage of experience, and neo-Bayesianism. In H. E. Kyburg et al. (Ed.), Knowledge representation and defeasible reasoning (pp. 245–265). Amsterdam: Kluwer.
Pearl, J. (1995). Causal diagrams for empirical research. Biometrika, 82(4), 669–688.
Pearl, J. (2000). Causality. Models, reasoning, and inference. Cambridge: Cambridge University Press.
Pearl, J. (2001). Causal inference in statistics: a gentle introduction. Technical Report R-289, Computer Science Department, University of California, Los Angeles.
Pearl, J., Verna, T. S. (1991). A statistical semantics for causation. In Proceeding, 3rd International Workshop on AI & Statistics, Fort Lauderdale, FL, 2–5 January 1991. http://bayes.cs.ucla.edu/cslpapers.html. Accessed 14 March 2008.
Pearson, K. (1911). The grammar of science. London: A. and C. Black.
Peto, R., Darby, S., Deo, H., Silcocks, P., Whitley, E., Doll, R. (2000). Smoking, smoking cessation, and lung cancer in UK since 1950. British Medical Journal, 321, 323–329.
Philips, D., Berman, Y. (2003). Social quality and ethnos communities: concepts and indicators. Community Development Journal, 38, 344–357.
Pickett, K., Pearl, M. (2001). Multilevel analysis of neighbourhood socioeconomic context and health outcomes: a critical review. Journal of Epidemiology and Community Health, 55, 111– 122.
Popper, K. R. (1957). The propensity interpretation of the calculus of probability and the quantum theory. In S. Körner (Ed.), The Colston Papers (pp. 65–70), vol. 9.
Popper, K. R. (1959). The propensity interpretation of probability. British Journal for the Philosophy of Science, 10, 25–42.
Pratt, J. W., Schlaifer, R. (1984). On the nature and discovery of structure. Journal of the American Statistical Association, 79(385), 9–21.
Price, H. (1991). Agency and probabilistic causality. British Journal for the Philosophy of Science, 42, 157–176.
Price, H. (1992). Agency and causal asymmetry. Mind, 101, 501–520.
Price, H. (2004). Models and modals. In D. Gillies (Ed.), Laws and models in science (pp. 49–69). London: King‘s College Publications.
Psillos, S. (2002). Causation and explanation. Chesham: Acumen Publishing.
Psillos, S. (2004). A glimpse of the secret connexion: harmonizing mechanisms with counterfac-tuals. Perspectives on Science, 12(3), 288–319.
Psillos, S. (2005). Undetermination. Encyclopedia of Philosophy. Gale MacMillan Reference. Second edition. http://www.phs.uoa.gr/˜psillos/Publicationsfiles/Underdetermination.doc. Accessed 14 March 2008.
Quetelet, A. (1869). Physique sociale. Ou essai sur le développement des facultés de l‘homme. Bruxelles: Muquardt.
Ramsey, F. P. (1931). Truth and probability. In F. P. Ramsey, The foundations of mathematics and other logical essays (Chapter VII, pp. 156–198). Edited by R. B. Braithwaite. London/London: Kegan Paul/Harcourt, Brace & Co. 1999 electronic edition. http://socserv.mcmaster.ca/econ/ugcm/3ll3/ramseyfp/ramsess.pdf. Accessed 14 March 2008.
Reichenbach, H. (1949). The theory of probability. Berkeley: University of California Press.
Reichenbach, H. (1956). The direction of time. Berkeley: University of California Press.
Reiss, J. (2001). Natural economic quantities and their measurement. Measurement in Physics and Economics — Discussion Papers. Technical Report 14/01, Centre for Philosophy of Natural and Social Science, London School of Economics.
Reiss, J. (2007). Do we need mechanisms in the social sciences? Philosophy of the Social Sciences, 37(2), 163–184.
Reiss, J. (2008). Error in economics: towards a more evidence-based methodology. London: Rout-ledge.
Roberts, J. T. (2004). There are no laws in the social sciences. In C. Hitchcock (Ed.), Contemporary debates in the social sciences (pp. 151–167). Oxford: Balckwell.
Robinson, W. (1950). Ecological correlations and the behaviour of individuals. American Sociological Review, 15, 351–357.
Rosen, D. (1978). In defence of a probabilistic theory of causality. Philosophy of Science, 45, 604–613.
Rosenbaum, P. R. (1984). From association to causation in observational studies. The role of tests of strongly ignorable treatment assignment. Journal of the American Statistical Association, 385, 41–48.
Rosenbaum, P. R., Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.
Rubin, D. (1974). Estimating causal effects of treatments in randomized and non randomized studies. Journal of Educational Psychology, 66(5), 688–701.
Rubin, D. (1978). Bayesian inference for causal effects: the role of randomization. The Annals of Statistics, 6, 34–58.
Russell, B. (1912–1913). On the notion of cause. Proceedings of the Aristotelian Society, 13, 1–26.
Russo, F. (2006a). Salmon and van Fraassen on the existence of unobservable entities: a matter of interpretation of probability. Foundations of Science, 11(3), 221–247.
Russo, F. (2006b). The rationale of variation in methodological and evidential pluralism. Philo-sophica, 77, 97–124.
Russo, F. (2007). Frequency-driven probabilities in quantitative causal analysis. Philosophical Writings, 32, 32–56.
Russo, F., Mouchart, M., Ghins, M., Wunsch, G. (2006). Causality, structural modelling and exogeneity. Discussion Paper 0601, Institut de Statistique, Université catholique de Louvain, Belgium.
Russo, F., Williamson J. (2007a) (Ed.). Causality and probability in the sciences. Texts in Philosophy Series. London: College Publications.
Russo, F., Williamson, J. (2007b). Interpreting probability in causal models for cancer. In F. Russo, J. Williamson (Ed.), Causality and probability in the sciences (pp. 217–242). Texts in Philosophy Series. London: College Publications.
Russo, F., Williamson, J. (2007c). Interpreting causality in the health sciences. International Studies in Philosophy of Science, 21(2), 157–170.
Salmon, W. C. (1967). Foundations of scientific inference. Pittsburgh: University of Pittsburgh Press.
Salmon, W. C. (1971). Statistical explanation. In W. C. Salmon et al. (Ed.), Statistical explanation and statistical relevance (pp. 29–87). Pittsburgh: University of Pittsburgh Press.
Salmon, W. C. (1977). Objectively homogeneous references classes. Synthese, 36, 399–414.
Salmon, W. C. (1980). Probabilistic causality. Pacific Philosophical Quarterly, 61, 50–74.
Salmon, W. C. (1984). Scientific explanation and the causal structure of the world. Princeton, NJ: Princeton University Press.
Salmon, W. C. (1988). Dynamic rationality. In J. Fetzer J. (Ed.), Probability and causality (pp. 3–42). Dordrecht: Reidel.
Salmon, W. C. (1990). Causal propensities: statistical causality vs. aleatory causality. Topoi, 9, 95–100.
Salmon, W. C. (1998). Causality and explanation. New York: Oxford University Press.
Salmon, W. C. et al. (1971). Statistical explanation and statistical relevance. Pittsburgh: University of Pittsburgh Press.
Savage, L. J. (1954). The foundations of statistics. New York: Wiley.
Simon, H. (1952). On the definition of the causal relation. Journal of Philosophy, 49(16), 517– 528.
Simon, H. (1953). Causal ordering and identifiability. In W. C. Hood, T. C. Koopmans (Ed.), Studies in econometric method (pp. 49–74). New York: Wiley.
Simon, H. (1954). Spurious correlation: a causal interpretation. Journal of the American Statistical Association, 49(267), 467–479.
Simon, H. (1979). The meaning of causal ordering. In K. R. Merto, J. J. Coleman, P. H. Rossi (Ed.), Qualitative and quantitative social research (pp. 65–81). New York: Free Press.
Skyrms, B. (1988). Probability and causation. Journal of Econometrics, 39, 53–68.
Snijders, T. A. B., Bosker, R. J. (2004). Multilevel analysis. An introduction to basic and advanced multilevel modeling. London: Sage. Fourth edition.
Sober, E. (1984). Two concepts of cause. PSA: Proceedings of the Biannual Meeting of the Philosophy of Science Association, 1982, vol. 2, 405–424.
Sober, E. (1986). Causal factors, causal influence, causal explanation. Proceedings of Aristotelian Society, 60, 97–136.
Spirtes, P., Glymour, C., Scheines, R. (1991). From probability to causality. Philosophical Studies, 91, 1–36.
Spirtes, P., Glymour, C., Scheines, R. (1993). Causation, prediction, and search. New York: Springer.
Spirtes, P., Richardson, T., Meek, C., Scheines, R., Glymour, C. (1998). Using path diagrams as a structural equation modeling tool. Sociological Method and Research, 27(2), 182–225.
Steuer, M. (2003). The scientific study of society. Boston: Kluwer.
Stone, R. (1993). The assumptions on which causal inferences rest. Journal of the American Statistical Association, 55(2), 455–466.
Suppes, P. (1970). A probabilistic theory of causality. Amsterdam: North Holland.
Suppes, P. (1982). Problems of causal analysis in the social sciences. Epistemologia, Special Issue 1982, 239–250.
Suppes, P. (2002). Representation and invariance of scientific structures. Stanford: CSLI Publications.
Susser, M. (2001). Glossary: causality in public health sciences. Journal of Epidemiology and Community Health, 55, 376–378.
Susser, M. W. (1973). Causal thinking in the health sciences. New York: Oxford University Press.
Susser, M., Susser, E. (1996). Choosing a future for epidemiology ii: from black box to Chinese box and ecoepidemiology. American Journal of Public Health, 86, 674–677.
Thompson, P. (2006). Bayes p-values. In S. Kotz, C. B. Read, N. Balakrishnan, B. Vidakovic (Ed.), Encyclopedia of Statistical Sciences. Hoboken, NJ: Wiley-Interscience. Second edition.
Toulemon, L. (2006). Les modèles de régression. In G. Caselli, J. Vallin, G. Wunsch (Ed.), D émographie: analyse et synthèse (pp. 359–374). Volume VIII Observation, méthodes auxiliaires, enseignement et recherche. Paris: Editions de l‘Institut National d‘Etudes Démographiques.
Urbach, P. (1989). Random sampling and the principles of estimation. Proceedings of the Aristotelian Society, 89, 143–164.
Vandresse, M. (2005). Characteristics of the newborn at birth and health status: a congested two-frontiers approach. Unpublished manuscript.
Vandresse, M. (2008). Late fertility: its causal effects on health of the newborn and its implications in fertility decision process. PhD Thesis. Université catholique de Louvain.
van Bouwel, J. (2004). Individualism and holism, reduction and pluralism: a comment on Keith Sawyer and Julie Zahle. Philosophy of the Social Sciences, 34(4), 527–535.
van Fraassen, B. C. (1980). The scientific image. Oxford: Clarendon Press.
van Fraassen, B. C. (1983). Calibration: a frequency justification for personal probabilities. In R. S. Cohen, L. Laudan (Ed.), Physics, philosophy and psychoanalysis: essays in honour of Adolph Grümbaum (pp. 295–319). Dordrecht: Reidel.
van Fraassen, B. C. (1989). Laws and symmetry. Oxford: Clarendon.
Venn, J. (1876). The logic of chance: an essay on the foundations and province of the theory of probability. London: Macmillan. Second edition.
Vineis, P. (2003). Causality in epidemiology. Sozial und Praventiv Medizin, 48, 80–87.
von Bertalanffy, L. (1969). General system theory: foundations, development, applications. New York: Braziller.
von Mises, R. (1957). Probability, statistics and truth. New York: Macmillan. Second edition.
von Wright, G. (1971). Explanation and understanding. Ithaca: Cornell University Press.
Wackerly, D. D., Mendenhall W., Scheaffer R. L. (2002). Mathematical statistics with applications. Pacific Grove: Duxbury. Sixth edition.
Williams, M., Williamson, J. (2006). Combining argumentation and Bayesian nets for breast cancer prognosis. Journal of Logic, Language and Information, 15, 155–178.
Williamson, J. (2005a). Bayesian nets and causality. Philosophical and computational foundations. Oxford: Oxford University Press.
Williamson, J. (2005b). Causality. In D. Gabbay, F. Guenthner (Ed.), Handbook of philosophical logic (pp. 131–162). volume 13. Springer.
Williamson, J. (2005c). Philosophies of probability: objective Bayesianism and its challenges. In A. Irvine (Ed.), Handbook of the philosophy of mathematics. Volume four of Handbook of Philosophy of Science. Elsevier. http://www.kent.ac.uk/secl/philosophy/jw/2004/philprob.pdf. Accessed 17 March 2008.
Williamson, J. (2007). Motivating objective Bayesianism: from empirical constraints to objective probabilities. In W. L. Harper, G. R. Wheeler (Ed.), Probability and inference: essays in honour of Henry E. Kyburg Jr (pp. 155–183). London: College Publications.
Woodward, J. (1993). Book review: Humphreys, P., ‘The chances of explanation: causal explanation in social, medical and physical sciences‘. Philosophy of Science, 60(4), 671–673.
Woodward, J. (1999). Causal interpretation in systems of equations. Synthese, 121, 199–247.
Woodward, J. (2003). Making things happen: a theory of causal explanation. Oxford: Oxford University Press.
Wonnacott, T. H., Wonnacott, R. J. (1990). Introductory Statistics. New York: Wiley. Fifth edition.
Worrall, J. (2002). What evidence in evidence-based medicine? Philosophy of Science, 69, 316– 330.
Wright, S. (1921). Correlation and causation. Journal of Agricultural Research, 20, 557–585.
Wright, S. (1934). The method of path coefficient. Annals of Mathematical Statistics, 5(3), 161– 215.
Wunsch, G. (1984). Theories, models and knowledge: the logic of demographic discovery. Genus, 40(1–2), 1–18.
Wunsch, G. (1986). Causal connections in causal modelling. Genus, 42(3–4), 1–12.
Wunsch, G. (1988). Causal theory and causal modelling. Leuven: Leuven University Press.
Wunsch, G. (1995). God has chosen to give the easy case to the physicists. In Evolution or revolution in European population. European Population Conference. 1 Plenary Session (pp. 201– 224). Milano: Franco Angeli.
Wunsch, G. (2007). Confounding and control. Demographic research, 6(4), 95–120.
Yule, G. U. (1897). On the theory of correlation. Journal of Royal Statistical Society, 60, 812–854.
Zellner, A. (1988). Causality and causal laws in economics. Journal of Econometrics, 39, 7–21.
Zeller, R. A., Carmines, E. G. (1980). Measurement in the social science. The link between theory and data. Cambridge: Cambridge University Press.
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(2009). What Do Social Scientists Do?. In: Causality and Causal Modelling in the Social Sciences. Methodos Series, vol 5. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-8817-9_1
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