inst/app/www/selection_bias.md

In dhaine/episensr.app: Shiny app for episensr, basic sensitivity analysis for epidemiological results

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Selection bias occurs when the study population is not representative of the target population. Assessed exposure and outcome influence participation to the study, either from the start (recruitment of some participants is more or less likely) or during follow-up (retaining or not participants in the study).

The sensitivity analysis performed by episensr for selection bias is based on selection proportion.

In the Analysis tab, provide the 2-by-2 table of exposure and outcome and the following bias parameters:

• Selection probability among cases exposed (1),
• Selection probability among cases unexposed (2),
• Selection probability among noncases exposed (3), and
• Selection probability among noncases unexposed (4).

Alternatively provide a single positive selection-bias factor which is the ratio of the exposed versus unexposed selection probabilities comparing cases and noncases [(1 X 4) / (2 X 3) from above].

The data for the example provided come from:

• Stang A., Schmidt-Pokrzywniak A., Lehnert M., Parkin D.M., Ferlay J., Bornfeld N. et al. Population-based incidence estimates of uveal melanoma in Germany. Supplementing cancer registry data by case-control data. Eur J Cancer Prev 2006;15:165-70.

dhaine/episensr.app documentation built on Feb. 12, 2020, 9:12 a.m.