Skip to main content
Fig. 3 | BMC Medical Research Methodology

Fig. 3

From: A compelling demonstration of why traditional statistical regression models cannot be used to identify risk factors from case data on infectious diseases: a simulation study

Fig. 3

Cases 3 and 4. a) Unexplained relative risk as a function of the relative susceptibility of the high- to low-risk individuals (\(\mathrm{a}\)). The different lines correspond to different levels of assortative mixing. Median and 95% CIs based on 500 simulations. b) 95% CIs for the effect of ethnicity \(\mathrm{exp}(\beta_{e})\) from the fitted Poisson regression model for varying levels of assortative mixing. The high-risk individuals are defined by a larger susceptibility than the low-risk individuals (case 3). There are 100 simulations for each assortativity level. c) Same as b), except the high-risk individuals are defined by a larger total number of contacts (case 4)

Back to article page

BMC Medical Research Methodology

ISSN: 1471-2288

Contact us