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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Confounding | 5/5 | https://en.wikipedia.org/wiki/Confounding | reference | science, encyclopedia | 2026-05-05T09:49:43.772485+00:00 | kb-cron |
== Criticism == Concerns have been raised that confounding in medical research can product false null results due to decreasing exposure reliability and increasing sibling-correlations.
== Artifacts == Artifacts are variables that should have been systematically varied, either within or across studies, but that were accidentally held constant. Artifacts are thus threats to external validity. Artifacts are factors that covary with the treatment and the outcome. Campbell and Stanley identify several artifacts. The major threats to internal validity are history, maturation, testing, instrumentation, statistical regression, selection, experimental mortality, and selection-history interactions. One way to minimize the influence of artifacts is to use a pretest-posttest control group design. Within this design, "groups of people who are initially equivalent (at the pretest phase) are randomly assigned to receive the experimental treatment or a control condition and then assessed again after this differential experience (posttest phase)". Thus, any effects of artifacts are (ideally) equally distributed in participants in both the treatment and control conditions.
== See also == Observational interpretation fallacy Anecdotal evidence – Evidence relying on personal testimony Causal inference – Branch of statistics Epidemiological method – Scientific method in the specific field Simpson's paradox – Error in statistical reasoning with groups Omitted-variable bias
== References ==
== Further reading == Pearl, J. (January 1998). "Why there is no statistical test for confounding, why many think there is, and why they are almost right" (PDF). UCLA Computer Science Department, Technical Report R-256. Montgomery, D. C. (2001). "Blocking and Confounding in the
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Factorial Design". Design and Analysis of Experiments (5th ed.). Wiley. pp. 287–302. This textbook has an overview of confounding factors and how to account for them in design of experiments.{{cite book}}: CS1 maint: postscript (link) Brewer, M. B. (2000). "Research design and issues of validity". In Reis, H. T.; Judd, C. M. (eds.). Handbook of Research. New York: Cambridge University Press. pp. 3–16. ISBN 9780521551281. Smith, E. R. (2000). "Research design". In Reis, H. T.; Judd, C. M. (eds.). Handbook of research methods in social and personality psychology. New York: Cambridge University Press. pp. 17–39. ISBN 9780521551281.
== External links ==
Tutorial: Confounding and Effect Measure Modification (Boston University School of Public Health) Linear Regression (Yale University) Tutorial by University of New England