Description Usage Arguments Value Examples

Simple sensitivity analysis to correct for selection bias using estimates of the selection proportions.

1 |

`case` |
Outcome variable. If a variable, this variable is tabulated against. |

`exposed` |
Exposure variable. |

`bias_parms` |
Selection probabilities. Either a vector of 4 elements between 0 and 1 defining the following probabilities in this order can be provided: 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).
or a single positive selection-bias factor which is the ratio of the exposed versus unexposed selection probabilities comparing cases and noncases [(1*4)/(2*3) from above]. |

`alpha` |
Significance level. |

A list with elements:

`model` |
Bias analysis performed. |

`obs.data` |
The analyzed 2 x 2 table from the observed data. |

`corr.data` |
The same table corrected for selection proportions. |

`obs.measures` |
A table of odds ratios and relative risk with confidence intervals. |

`adj.measures` |
Selection bias corrected measures of outcome-exposure relationship. |

`bias.parms` |
Input bias parameters: selection probabilities. |

`selbias.or` |
Selection bias odds ratio based on the bias parameters chosen. |

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
# The data for this example 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.
selection(matrix(c(136, 107, 297, 165),
dimnames = list(c("UM+", "UM-"), c("Mobile+", "Mobile-")),
nrow = 2, byrow = TRUE),
bias_parms = c(.94, .85, .64, .25))
selection(matrix(c(136, 107, 297, 165),
dimnames = list(c("UM+", "UM-"), c("Mobile+", "Mobile-")),
nrow = 2, byrow = TRUE),
bias_parms = 0.43)
``` |

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