Monday, June 20, 2016

Don't under estimate the power of maturation

Between baby birds and aging humans, it is easy for me be reminded of "maturation."  Once, about 50 years ago, a very good professor asked me to teach a class that he was going to have to miss.  He told me what he wanted the class to learn.  It was the chapter from the Handbook of Educational Research by Donald Campbell and Julian Stanley about how to run experiments in educational research.  I had never heard of the chapter but I read it fully. What a treasure!

Today, seeing baby tree swallows maturing by the hour and thinking of Father's Day, my own father, my stepfather, my fatherhood, it came to mind that maturing, that is, growing older, is a very important factor.  True, the nature of the parents and the house they run is very important, too.  But is far from the whole story.  Their list of important experimental variables that can influence an experiment and cause misinterpretation of the results is:

1. History, the specific events occurring between the first and second measurement in addition to the experimental variable.

2. Maturation, processes within the respondents operating as a function of the passage of time per se (not specific to the particular events), including growing older, growing hungrier, growing more tired, and the like.

3. Testing, the effects of taking a test upon the scores of a second testing. 4. Instrumentation, in which changes in the calibration of a measuring instrument or changes in the observers or scorers used may produce changes in the obtained measurements.

5. Statistical regression, operating where groups have been selected on the basis of their extreme scores,

6. Biases resulting in differential selection of respondents for the comparison groups.

7. Experimental mortality, or differential loss of respondents from the comparison groups.

8. Selection-maturation interaction, etc., which in certain of the multiple-group quasi-experimental designs, such as Design 10, is confounded with, i.e., might be mistaken for, the effect of the experimental variable.

9. The reactive or interaction effect of testing, in which a pretest might increase or decrease the respondent's sensitivity or responsiveness to the experimental variable and thus make the results obtained for a pretested population unrepresentative of the effects of the experimental variable for the unpretested universe from which the experimental respondents were selected.

10. The interaction effects of selection biases and the experimental variable.

11. Reactive effects of experimental arrangements, which would preclude generalization about the effect of the experimental variable upon persons being exposed to it in nonexperimental settings.

12. Multiple-treatment interference, likely to occur whenever multiple treatments are applied to the same respondents, because the effects of prior treatments are not usually erasable. This is a particular problem for one-group designs.

Campbell, Donald T.; Stanley, Julian C.. Experimental and Quasi-Experimental Designs for Research (Kindle Locations 116-131). Ravenio Books. Kindle Edition.

Your son may turn out to be a wonderful person but a good deal of those fine qualities he shows may actually come from the design of the human being and the many fortuitous influences he happened to run into while living.

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