By Jfry KSmit
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This paperback version is a reprint of the 1991 variation. Time sequence: idea and strategies is a scientific account of linear time sequence types and their program to the modeling and prediction of knowledge accumulated sequentially in time. the purpose is to supply particular strategies for dealing with info and while to supply a radical figuring out of the mathematical foundation for the suggestions.
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A. Bradford Hill is credited with adapting the concept to the first human randomized clinical trial (RCT), a study of streptomycin for pneumonia in 1948. Multiple RCTs in other conditions followed right away in the 1950s, the first in psychiatry involving lithium in 1952 and the antipsychotic chlorpromazine in 1954. This is the standard history, and it is correct in the sense that Fisher and Hill were clearly the first to formally develop the concept Section 2: Bias of randomization and to recognize its conceptual importance for statistics and science.
This is confounding bias. Let us suppose that the risk of cancer is higher in women smokers than in men smokers; this is no longer confounding bias, but EM. There is some interaction between gender and cigarette smoking, such that women are more prone biologically to the harmful effects of cigarettes (this is a hypothetical example). But we have no reason to believe that being female per se leads to cancer, as opposed to being male. Gender itself does not cause cancer; it is not a confounding factor; it merely modifies the risk of cancer with the exposure, cigarette smoking.
Further, if a study does not contain any, or hardly any, persons with a potential confounding factor, then it cannot be confounded by that factor (this is called “restriction” as opposed to stratification). One of the benefits of stratification, compared to regression, is that one does not need to make certain assumptions about whether the regression model can be applied to the data (see Appendix). The key weakness is that one cannot correct for multiple confounders simultaneously, but at least one can capture major confounders with this simple method.
Applied Statistics and the SAS Programming Language by Jfry KSmit
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