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Is it a fair interpretation of what you are saying to say that the process of correlating phenomena needs to be distinguished from the value of some form of correlation coefficient? I certainly agree with that. - - - The observation that a correlation exists is one point in an inductive argument about causation. The entire argument shows causation. If we cannot show some form of correlation an important element of a casual inference is missing. Of course, the mere existence of a correlation, by itself, does not constitute a complete complete argument about causation. Related to this, I don't put a lot of faith in any single study, but find plausability in a range of studies about a phenomenon. - - - Where do you put dose-response curves in your epistemology? How do you deal with statements like: Larger speed differences resulted in larger doppler shifts. More ionizing radiation resulted in more deaths. More time spent memorizing vocabulary words resulted in more words recalled a week later. More stress increased performance up to a point and then increased stress lowered performance. More exposure to a treatment results in a higher probability of recovery. - - - Usually I think of X in the manipulated range as causal of Y _in a population_. Often we cannot get to a deterministic cause, but to stochastic or probabilistic causation. BY ITSELF, the demonstration that people who smoked more were more likely to get cancer was insufficient for some researchers. However, after DNA was discovered and better understood, and the mechanism induced in vitro and in vivo, even the Tobacco Institute has recognized the causation. Dennis Roberts wrote: > At 07:36 AM 12/5/01 -0500, Karl L. Wuensch wrote: > > > Accordingly, I argue that correlation is a necessary but not a > > sufficient condition to make causal inferences with reasonable > > confidence. Also necessary is an appropriate method of data > > collection. To make such causal inferences one must gather the data by > > experimental means, controlling extraneous variables which might confound > > the results. Having gathered the data in this fashion, if one can > > establish that the experimentally manipulated variable is correlated with > > the dependent variable (and that correlation does not need to be linear), > > then one should be (somewhat) comfortable in making a causal > > inference. That is, when the data have been gathered by experimental > > means and confounds have been eliminated, correlation does imply causation. > > the problem with this is ... does higher correlation mean MORE cause? lower > r mean LESS cause? > > in what sense can think of cause being more or less? you HAVE to think that > way IF you want to use the r value AS an INDEX MEASURE of cause ... > > personally, i think it is dangerous in ANY case to say that r = cause ... > > if you can establish that as A goes up ... so does B ... where you > manipulated A and measured B ... (or vice versa) ... then it is fair to say > that the causal connection THAT IS IMPLIED BECAUSE OF THE WAY THE DATA WERE > MANIPULATED/COLLECTED also has a concomitant r ... BUT, i think one still > needs to be cautious when then claiming that the r value itself is an > indicant OF cause > > > > > > > So why is it that many persons believe that one can make causal > > inferences with confidence from the results of two-group t tests and > > ANOVA but not with the results of correlation/regression techniques. I > > believe that this delusion stems from the fact that experimental research > > typically involves a small number of experimental treatments that data > > from such research are conveniently evaluated with two-group t tests and > > ANOVA. Accordingly, t tests and ANOVA are covered when students are > > learning about experimental research. Students then confuse the > > statistical technique with the experimental method. I also feel that the > > use of the term "correlational design" contributes to the problem. When > > students are taught to use the term "correlational design" to describe > > nonexperimental methods of collecting data, and cautioned regarding the > > problems associated with inferring causality from such data, the students > > mistake correlational statistical techniques with "correlational" data > > collection methods. I refuse to use the word "correlational" when > > describing a design. I much prefer "nonexperimental" or "observational." > > > > > > > > In closing, let me be a bit picky about the meaning of the word > > "imply." Today this word is used most often to mean "to hint" or "to > > suggest" rather than "to have as a necessary part." Accordingly, I argue > > that correlation does imply (hint at) causation, even when the > > correlation is observed in data not collected by experimental means. Of > > course, with nonexperimental models, the potential causal explanations of > > the observed correlation between X and Y must include models that involve > > additional variables and which differ with respect to which events are > > causes and which effects. > > > >---------- > >Karl L. Wuensch, Department of Psychology, > >East Carolina University, Greenville NC 27858-4353 > >Voice: 252-328-4102 Fax: 252-328-6283 > ><mailto:[EMAIL PROTECTED]>[EMAIL PROTECTED] > >http://core.ecu.edu/psyc/wuenschk/klw.htm > > _________________________________________________________ > dennis roberts, educational psychology, penn state university > 208 cedar, AC 8148632401, mailto:[EMAIL PROTECTED] > http://roberts.ed.psu.edu/users/droberts/drober~1.htm > > ================================================================= > Instructions for joining and leaving this list and remarks about > the problem of INAPPROPRIATE MESSAGES are available at > http://jse.stat.ncsu.edu/ > ================================================================= --------------E98CFE9DA7C53331DB22D947 Content-Type: text/x-vcard; charset=us-ascii; name="Arthur.Kendall.vcf" Content-Transfer-Encoding: 7bit Content-Description: Card for Art Kendall Content-Disposition: attachment; filename="Arthur.Kendall.vcf" begin:vcard n:Kendall;Art tel;work:301-864-5570 x-mozilla-html:FALSE adr:;;;;;; version:2.1 email;internet:[EMAIL PROTECTED] fn:Art Kendall end:vcard --------------E98CFE9DA7C53331DB22D947-- ================================================================= Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =================================================================
