By Maurice G. Kendall, William R. Buckland

ISBN-10: 0050022806

ISBN-13: 9780050022801

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27463 _outcome Istudy_2 Istudy_3 Istudy_4 exposed _cons _outcome Istudy_2 Istudy_3 Istudy_4 exposed Coef. Std. Err. 0289 P>|z| [95% Conf. 665 Odds Std. Err. 290 [95% Conf. 672. The Pseudo R2 which is automatically given by STATA is difficult to interpret and should not be quoted. It is printed automatically and illustrates one of the hazards of reading routine output. 9 Matched case–control studies In matched case–control studies each case is matched directly with one or more controls. For a valid analysis the matching should be taken into account.

Report how the assumptions underlying the model were tested and verified. In particular is linearity plausible? • Report any sensitivity analysis carried out. • Report all the variables included in the model. For a stepwise regression, report all the variables that could have entered the model. • Note that if an interaction term is included in a model, the main effects must be included. 11: • Note the value of R2. With a large study, the coefficients in the model can be highly significant, but only explain a low proportion of the variability of the outcome variable.

10 Instead we use a method known as conditional logistic regression. 1 It is a flexible method, that with most modern softwares allow cases to have differing numbers of controls; it is not required to have exact 1:1 matching. The logic for a conditional likelihood is quite complex, but the argument can be simplified. 1), and for pair i the probability of an event for the case was i0 and for the control i1. Given that we know that one of the pair must be the case, that is, there must be one and only one event in the pair, conditional on the pair, the probability of the event happening for the case is simply i0/(i0 ϩ i1).

### A dictionary of statistical terms by Maurice G. Kendall, William R. Buckland

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