Perbandingan Inferensi Kausal Versi Donald Campbell dengan Donald Rubin

T Dicky Hastjarjo

Abstract


In a psychological experiment, the manipulation of the independent variable is deliberatelyintroduced to observe its effects on the dependent variable. The cause-effect relationshipthen is inferred. This article explained briefly two models of causal inferences. One modeldeveloped by Donald Campbell is more focused on design elements in ruling out threats tovalidity. On the other hand, Rubin’s model of causal inference emphasized in mathematicalprecision of the causal effects. The comparison of the two different but complementarymodels involves both randomized experiment and observational study.

Keywords


causality; causal model; experimental validity; threats to validity

References


Campbell, D. T. (1957). Factors Relevant to the Validity of Experiments in Social Settings. Psychological Bulletin, 34, 4, 297-312.

Campbell, D.T & Stanley, J. C. (1966). Experimental and Quasi-Experimental Designs for Research. Rand McNally & Co:

Chicago. Cook, T. D., & Campbell, D. T. (1979). Quasi-Experimentation: Design & Analysis Issues for Field Settings. Houghton Mifflin Co: Boston.

Hastjarjo, T. D. (2010). Eksperimen-kuasi dan Generalisasi Inferensi Kausal. Prosiding Konferensi Nasional mengenai Psikologi Eksperimen, Yogyakarta 27 Januari 2010.

Hastjarjo, T. D. (2011a). Kausalitas menurut Tradisi Donald Campbell. Buletin Psikologi, 19, 1, 1-15. Hastjarjo, T. D. (2011b). Validitas Eksperimen. Buletin Psikologi, 19, 2, 70-80.

Pearl, Y. (2000). Causality: Models, Reasoning, and Inference. New York: Cambridge University Press. Pearl, Y. (2009). Causality: Models, Reasoning, and Inference (2nd Ed). New York: Cambridge University Press.

Rubin, B. D. (1974). Estimating Causal Effects of Treatments in Randomized and Nonrandomized Studies. Journal of Educational Psychology, 56,5, 688-701.

Rubin, B. D. (1986). Which Ifs Have Causal Answers. Journal of the American Statistical Association, 81, 396, 961-962.

Rubin, B. D. (2004). Teaching Statistical Inference for Causal Effects in Experiments and Observational Studies. Journal of Educational and Behavioral Statistics, 29, 3, 343-367.

Rubin, B. D. (2005). Causal Inference Using Potential Outcomes: Design, Modelling, Decisions. Journal of the American Statistical Association, 100, 469, 322-334.

Shadish, W. R. (2010). Campbell and Rubin: A Primer and Comparison of their Approaches to Causal Inference in Field Settings. Psychological Methods, 15, 1, 3-17. Shadish, W. R., & Cook, T. D. (1999). Comment---Design Rules: More Steps toward a Com

plete Theory of Quasi-experimentation. Statistical Science, 14, 294-300.

Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin Co: Boston.

Steyer, R. (2017). Theory of causal effects. Manuscript in preparation. FSU Jena, Jena

West, S. G., & Thoemmes, F. (2010). Campbell’s and Rubin’s Perspectives on Causal Inferences. Psychological Methods, 15, 1, 18-37.


Full Text: PDF

DOI: 10.22146/buletinpsikologi.30884

Refbacks

  • There are currently no refbacks.




Copyright (c) 2018 Buletin Psikologi

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.