The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Control of Confounding in the Assessment of Medical Technology
Abstract
Greenland S (Division of Epidemiology, School of Public Health, University of California, Los Angeles, CA 90024, USA) and Neutra R. Control of confounding in the assessment of medical technology. International Journal of Epidemiology 1980, 9: 361–367. Separation of the effects of extraneous variables from the effects of a factor under study (often termed control of confounding) is one of the key prerequisites for validly estimating the magnitude of the study factor's effects. Because of the phenomenon of confounding by indication, confounding of effects of different factors is a common problem in the assessment of medical technology. We give several examples illustrating that the decision of whether a recorded variable is a confounder in a data-set must be decided on the basis of subject-matter knowledge and clinical judgement. There is no alternative to use of such judgement; statistical selection procedures based on significance tests, such as stepwise regression, can be particularly misleading.
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Citations
Cites
An Improper Use of Statistical Significance Testing in Studying Covariables
DALES, L. G., & URY, H. K. (1978) · International Journal of Epidemiology · doi:10.1093/ije/7.4.373 · Cited by 169
Cited by
Vandenbroucke, J. P., von Elm, E., Altman, D. G., Gøtzsche, P. C., Mulrow, C. D., Pocock, S. J., Poole, C., Schlesselman, J. J., Egger, M., & Initiative, F. T. S. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040297 · Cited by 8,613
“Of note, we and others do not advise selecting confounders based solely on statistical significance testing [147,159,160].”
Marginal Structural Models and Causal Inference in Epidemiology
Robins, J. M., Hernán, M. Á., & Brumback, B. (2000) · Epidemiology · doi:10.1097/00001648-200009000-00011 · Cited by 5,581
Vandenbroucke, J. P., Elm, E. V., Altman, D. G., Gøtzsche, P. C., Mulrow, C. D., Pocock, S. J., Poole, C., Schlesselman, J. J., Egger, M., & initiative, F. T. S. (2007) · Annals of Internal Medicine · doi:10.7326/0003-4819-147-8-200710160-00010-w1 · Cited by 3,543
Vandenbroucke, J. P., von Elm, E., Altman, D. G., Gøtzsche, P. C., Mulrow, C. D., Pocock, S. J., Poole, C., Schlesselman, J. J., & Egger, M. (2014) · International Journal of Surgery · doi:10.1016/j.ijsu.2014.07.014 · Cited by 2,969
Evaluating non-randomised intervention studies
Deeks, J., Dinnes, J., D'Amico, R., Sowden, A., Sakarovitch, C., Song, F., Petticrew, M., & Altman, D. (2003) · Health Technology Assessment · doi:10.3310/hta7270 · Cited by 2,907
Metadata
- Authors
- GREENLAND, S., & NEUTRA, R.
- Venue
- International Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 1980-12-01
- Volume
- 9
- Issue
- 4
- Pages
- 361-367
- ISSN
- 0300-5771 (ISSN-L)
- 1464-3685
- OpenAlex
- W2155199182
- Cited by
- 201
- References
- 1
- FWCI
- 1.18
- Type
- journal article
- Language
- en
- Open access
- closed
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- GREENLAND, S., & NEUTRA, R. (1980). Control of Confounding in the Assessment of Medical Technology. International Journal of Epidemiology. https://doi.org/10.1093/ije/9.4.361
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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