On Wed, 21 Jul 2010 06:32:01 -0700,, Scott O Lilienfeld wrote:
>On a more conciliatory note (maybe I'm just in a charitable mood 
>this morning), Mike P. and I do agree on the merits of Don Campbell's 
>writing (and I agree with Mike that Shadish, Cook, and Campbell 
>is a treasure trove of a resource for thinking critically about 
>quasi-experimentation).  Also, a quotation from Campbell from his 
>classic 1969 American Psychologist article (Reforms as Experiments), 
>seems apropos here:
>
>"The advocated strategy in quasi-experimentation is not to throw up 
>one's hands and refuse to use the evidence because of this lack of control, 
>but rather to generate by informed criticism appropriate to this specific 
>setting as many plausible rival hypotheses as possible, and then to do 
>the supplementary research..which would reflect on these rival hypotheses."

Another quote seems apropos here.  Shadish (2010), in a Psychological
Methods article that compares the causal models implied by Campbell's
and Donald Rubin's (of missing value analysis and "potential outcomes"
theory) approaches, makes the following statement:

NOTE: CCM = Campbell's Causal Model

|Perhaps the important difference is the greater emphasis on
|human and scientific fallibility in CCM. CCM is paradoxically
|skeptical about the possibility of doing the very things that CCM
|sometimes requires to generate good causal inferences. Humans
|are poor at making many kinds of causal judgments, prone to
|confirmation biases, blind to apparent falsifications, and lazy
|about both design and identifying alternative explanations. Yet,
|in the cases where a stronger design cannot be used or fails,
|CCM is remarkably dependent on those judgments for identifying
|threats, deciding whether they have been rendered implausible
|in any given case, and summing over them to reach a
|causal conclusion, especially in weaker nonrandomized experiments.
|CCM argues, therefore, that the responsibility for being
|critical lies more with the community of scholars than with any
|given researcher, especially with those whose interests would
|most lead them to find fault (Cook, 1985). Of course, CCM
|benefits from technical advances, like propensity score analysis,
|that reduce reliance on fallible judgments. Hence, CCM has
|turned attention to incorporating such developments (e.g., Luellen,
|Shadish, & Clark, 2005; Shadish, Luellen, & Clark,
|2006). (page 8).

William R. Shadish (2010). Campbell and Rubin: A Primer and 
Comparison of Their Approaches to Causal Inference in Field Settings.
Psychological Methods, 15(1) 3–17.

-Mike Palij
New York University
[email protected]


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