Counterfactuals and causal inference: Methods and principles for social research
| Data(s) |
2011
|
|---|---|
| Resumo |
"Most quantitative empirical analyses are motivated by the desire to estimate the causal effect of an independent variable on a dependent variable. Although the randomized experiment is the most powerful design for this task, in most social science research done outside of psychology, experimental designs are infeasible. (Winship & Morgan, 1999, p. 659)." This quote from earlier work by Winship and Morgan, which was instrumental in setting the groundwork for their book, captures the essence of our review of Morgan and Winship's book: It is about causality in nonexperimental settings. |
| Identificador |
https://serval.unil.ch/notice/serval:BIB_B252C50CF3AD https://serval.unil.ch/resource/serval:BIB_B252C50CF3AD.P001/REF http://nbn-resolving.org/urn/resolver.pl?urn=urn:nbn:ch:serval-BIB_B252C50CF3AD7 urn:nbn:ch:serval-BIB_B252C50CF3AD7 http://nbn-resolving.org/urn/resolver.pl?urn=urn:nbn:ch:serval-BIB_B252C50CF3AD7 |
| Idioma(s) |
eng |
| Direitos |
info:eu-repo/semantics/openAccess Copying allowed only for non-profit organizations https://serval.unil.ch/disclaimer |
| Fonte |
Structural Equation Modeling181152-159 |
| Palavras-Chave | #causality; counterfactuals; field research |
| Tipo |
info:eu-repo/semantics/article article |
| Formato |
application/pdf |