Los efectos de terceras variables en la investigación psicológica

Erreferentzia bibliografikoak

• Aguinis, H. (2003). Regression Analysis for Categorical Moderators. New York: Guilford Press.
• Aiken, L.S. y West, S.G. (1991). Multiple regression: testing and interpreting interactions. Newbury Park, CA: Sage.
• Ato, M. y Vallejo, G. (2007). Diseños Experimentales en Psicología. Madrid: Pirámide.
• Baron, R.M. y Kenny, D. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182.
• Bauer, D.J. y Curran, P.J. (2005). Probing interactions in fixed and multilevel regression: inferential and graphical techniques. Multivariate Behavioral Research, 40, 373-400.
• Bollen, K.A. (1989). Structural equations with latent variables. New York: Wiley.
• Chaplin, W.F. (2007). Moderator and mediator models in personality research: a basic introduction. En R.W. Robins, R.C. Fraley y R.F. Krueger (Eds): Handbook of Research Methods in Personality Psychology, pp. 602-630. New York: Guilford Press.
• Cheung, M.W. (2009). Comparison of methods for constructing confidence intervals of standardized indirect effects. Behavior Research Methods, 41, 425-438.
• Cheung, G.W. y Lau, R.S. (2008). Testing mediation and suppression effects of latent variables: bootstrapping with structural equation models. Organizational Research Methods, 11, 296-325.
• Cohen, J. y Cohen, P. (1983). Applied multiple regression/correlation for the behavioral sciences. 2nd Ed. Hillsdale, NJ: Lawrence Erlbaum.
• Cohen, J., Cohen, P., West, S.G. y Aiken, L.S. (2003). Applied multiple regression correlation analysis for the behavioral sciences. 3rd Ed. Mahwah: Lawrence Erlbaum.
• Collins, L.M., Graham, J.W. y Flaherty, B.P. (1998). An alternative frame-work for defining mediation. Multivariate Behavioral Research, 33, 295-312.
• Conger, A.J. (1974). A revised definition for suppressor variables: a guide to their identification and interpretation. Educational and Psychological Measurement, 34, 35-46.
• Echambadi, R. y Hess, J.D. (2007). Mean-centering does not alleviate collinearity problems in moderate multiple regression models. Marketing Science, 26, 438-445.
• Edwards, J.R. y Lambert, L.S. (2007). Methods for integrating moderation and mediation: a general analytical framework using moderated path analysis. Psychological Methods, 12, 1-22.
• Estévez, A. y Calvete, E. (2009). Mediación a través de pensamientos automáticos de la relación entre esquemas y síntomas de depresión. Anales de Psicología, 25, 27-35.
• Fairchild, A.J. y MacKinnon, D.P. (2009). A general model for testing mediation and moderation effects. Prevention Science, 10, 87-99.
• Fritz, M.S. y MacKinnon, D.P. (2007). Required sample size to detect the mediated effect. Psychological Science, 18, 233-239.
• Frazier, P.A.; Tix, A.P. y Barron, K.E. (2004). Testing moderator and mediator effects in counseling psychology research. Journal of Counseling Psychology, 51, 115-134.
• Greenland, S. (2000). Causal analysis in the health sciences. Journal of the American Statistical Association, 95, 286-289.
• Greenland, S. y Morgenstern, H. (2001). Confounding in health research. Annual Review of Public Health, 22, 189-212.
• Holmbeck, G.N. (1997). Toward terminological, conceptual and statistical clarity in the study of mediadors and moderators: examples from the child-clinical and pediatric psychology literatures. Journal of Consulting and Clinical Psychology, 65, 599-610.
• Horst, P. (1941). A role of predictor variables which are independent of the criterion. Social Science Research Bulletin, 48, 431-436.
• Iacobucci, D. (2008). Mediation analysis. Thousand Oaks, CA: Sage.
• Iacobucci, D.; Saldanha, N. Y Deng, X. (2007). A meditation on mediation: evidence that structural equations models perform better than regressions. Journal of Consumer Psychology, 17, 140-154.
• Jaccard, J. y Turrisi, R. (2003). Interaction effects in multiple regression (2nd ed.) Thousand Oaks, CA: Sage.
• James, L.R. y Brett, J.M. (1984). Mediators, moderators and test for mediation. Journal of Applied Psychology, 69, 307-321.
• James, L.R., Mulaik, S.A. y Brett, J.M. (2006). A tale of two methods. Organizational Research Methods, 9, 233-244.
• Jandasek, B., Holmbeck, G.N. y Rose, B.M. (2008). Statistical considerations: moderators and mediators. En M. Hersen y A.W. Grow (Eds.): Handbook of Clinical Psychology. Vol 2: Children and Adolescents (pp. 391-320). New York: Wiley.
• Jiménez, T.I., Musitu, G. y Murgui, S. (2008). Funcionamiento familiar y consumo de sustancias en adolescentes: el rol mediador de la autoestima. International Journal of Clinical and Health Psychology, 8, 139-151.
• Judd, C.M. y Kenny, D. (1981). Process analysis: estimating mediation in treatment evaluations. Evaluation Review, 5, 602-619.
• Judd, C.M. y Kenny, D. (2010). Data analysis in social psychology: recent and recurrent issues. En S.T. Fiske, D.T. Gilbert & G. Lindzey (Eds.): Handbook of Social Psychology, 5th Edition (pp. 115-139). New York, NY: Wiley.
• Kam, C.D. y Franzese F.J. (2007). Modeling and interpreting interactive hypotheses in regression analysis. Ann Arbor: The University of Michigan Press.
• Kenny, D. (1979). Correlation and causality. New York: Wiley.
• Kenny, D. (2008). Reflections on mediation. Organizational Research Methods, 11, 353-358.
• Kenny, D. (2009). Estimating and testing mediation. Documento recuperado el 7/6/2009 de la dirección: http://davidakenny.net/p5130/mediationsem.ppt
• Kenny, D. Kashy, D.A. y Bolger, N. (2006). Data analysis in social psychology. En D.T. Gilbert, S.T. Fiske y G. Linzey (Eds.), The Handbook of Social Psychology, 4th Ed. Vol.1, pp. 233-265. New York: Oxford University Press.
• Kraemer, H.C.; Kiernan, M.; Essex, M. y Kupfer, D.J. (2008). How and why criteria defining moderators and mediators differ between Baron & Kenny and MacArthur approaches. Health Psychology, 27, S101-108.
• Maasen, G.H. y Baker, A.B. (2001). Suppressor variables in path models: definitions and interpretations. Sociological Methods and Research, 30, 241-270.
• MacKinnon, D.P. (2008). Introduction to Statistical Mediation Analysis. New York: Lawrence Erlbaum Associates.
• MacKinnon, D.P. y Dwyer, J.H. (1993). Estimating mediated effects in prevention studies. Evaluation Review, 17, 144-158.
• MacKinnon, D.P. y Luecken, L.J. (2008). How and for whom? Mediation and moderation in health psychology. Health Psychology, 27(2, supp), S99-S100.
• MacKinnon, D.P.; Fairchild, A.J. y Fritz, M.S. (2007). Mediation analysis. Annual Review of Psychology, 58, 593-614.
• MacKinnon, D.P.; Krull, J. L y Lockwood, C.M. (2000). Equivalence of the mediation, confounding and suppression effect. Prevention Science, 1, 173-181.
• MacKinnon, D.P.; Krull, J. L y Lockwood, C.M. (2002). A comparison of methods to test mediation and other intervening variable effects. Psychological Methods, 7, 83-104.
• MacKinnon, D.P., Lockwood, C.M. y Williams, J. (2004). Confidence limits for the indirect effect: distribution of the product and resampling methods. Multivariate Behavioral Research, 39, 99.128.
• MacKinnon, D.P., Warsi, G. y Dwyer, J.H. (1995). A simulation study of mediated effect measures. Multivariate Behavioral Research, 30, 41-62.
• MacKinnon, D.P., Lockwood, C.M., Hoffman, J.M., West, S.G. y Sheets, V. (2002). A comparison of methods to test mediation and other intervening variable effects, Psychological Methods, 7, 83-104.
• Mallinckrodt, B., Abraham, W.T., Wei, M. y Russell, D.W. (2006). Advances in testing the statistical significance of mediation effects. Journal of Counseling Psychology, 53, 372-378.
• Meinert, C.L. (1986). Clinical trials: design, conduct and analysis. New York, NY: Oxford University Press.
• Miller, G.A. y Chapman, J.P. (2001). Misunderstanding analysis of covariance. Journal of Abnormal Psychology, 110, 40-48.
• Milliken, G.A. y Johnson, D.E. (2002). Analysis of messy data. III: Analysis of covariance. Boca Ratón, CA: Chapman & Hall.
• Müller, D.; Yzerbyt, V.Y. y Judd, C.M. (2008). Adjusting for a mediator in models with two crossed treatment variables. Organizational Research Methods, 11, 224.240.
• Nguyen-Rodriguez, H.T., Chou, C.; Unger, J.B. y Spruijt-Metz, D. (2008). BMI as a moderator of perceived stress and emotional eating in adolescents. Eating Behavior, 9, 238-246.
• Pearl, J. (2009a). Causality: models, reasoning and inference. 2nd Edition. New York, NY: Cambridge University Press.
• Pearl, J. (2009b). Causal inference in statistics: an overview. Statistics Surveys, 3, 96-146.
• Pearl, J. (2010a). An introduction to causal inference. International Journal of Biostatistics, 6, issue 2, article 7.
• Pearl, J. (2010b). The Mediation Formula: a guide to the assessment of causal pathways in non-linear models. UCLA Cognitive Systems Experimental Laboratory. Technical Report R-363. Documento recuperado el 3/08/2010 de la dirección: ftp://ftp.cs.ucla.edu/pub/stat_ser/r363.pdf
• Potthoff, R.F. (1964). On the Johnson-Neyman technique and some extensions thereof. Psychometrika, 29, 241-256.
• Preacher, K.J. y Hayes, A.F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments & Computers, 36, 717-731.
• Preacher, K.J. y Hayes, A.F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40, 879-891.
• Preacher, K.J., Rucker, D.D. y Hayes, A.F. (2007). Addressing moderated mediation hypotheses: Theory, methods and prescriptions. Multivariate Behavioral Research, 42,185-227.
• Quiles, M.N., Rodríguez, A., Navas, M., Rodríguez, R., Betancor, V. y Coello E. (2006). Variables moderadoras y mediadoras de la relación percepción de diferencias-ansiedad intergrupal. Psicothema, 18, 105-111.
• Quiñones, E., López, J.J., Peñaranda, M. y Tortosa, F. (2004). The nature of social and personality psychology as reflected in JPSP, 1965-2000. Journal of Personality and Social Psychology, 86, 435-452.
• Rose, B. M., Holmbeck, G. N., Coakley, R. M. y Franks, E. A. (2004). Mediator and moderator effects in developmental and behavioral pediatric research. Developmental and Behavioral Pediatrics, 25, 58-67.
• Rosenbaum, P.R. (2002). Observational studies. 2nd Edition. New York, NY: Springer.
• Rubin, D. (2005). Causal inference using potential outcomes: design, modeling, decisions. Journal of the American Statistical Association, 100, 322-331.
• Shadish, W., Cook, T.D. y Campbell, D.T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Boston, MA: Houghton Mifflin Company.
• Shrout, P.E. y Bolger, N. (2002). Mediation in experimental and nonexperimental studies: new procedures and recommendations. Psychological Methods, 7, 422-445.
• Sobel, M.E. (1986). Some new results on indirect effects and their standard errors in covariance structure models. Sociological Methodology, 16, 149-186.
• Spencer, S.J., Zanna, M.P. and Fong, G.T. (2005). Establishing a causal chain: why experiments are often more effective than mediational analyses in examining psychological processes. Journal of Personality and Social Psychology, 89, 845-51.
• Stone, C.A. and Sobel, M.E. (1990). The robustness of estimates of total indirect effects in covariance structure models estimates by maximum likelihood. Psychometrika, 55, 337-352.
• Stone-Romero, E.F. y Rosopa, P.J. (2008). The relative validity of inferences about mediation as a function of research design characteristics. Organizational Research Methods, 11, 326-352.
• Tzelgov, J. y Henik, A. (1991). Suppression situations in psychological research: definitions, implications and applications. Psychological Bulletin, 109, 534-536.
• Zhao, X., Lynch, J.G. & Chen, Q. (2010). Reconsidering Baron and Kenny: myths and truths about mediation analysis. Journal of Consumer Research, 37 (august), electronically published February 15, 2010.
• Wu, A.D. y Zumbo, B.D. (2008). Understanding and using mediators and moderators. Social Indicators Research, 87, 367-392.