Description Usage Arguments Details Value Note Author(s) References Examples

Computes the cross-cut test and its sensitivity analysis. The cross-cut test is a nonparametric test of dose-response correlation with good design sensitivity when used for causal inference in observational studies.

1 |

`x` |
Doses of treatment. |

`y` |
Response. |

`ct` |
The quantile that defines the cross-cut. By default, the cross-cut is at the outer .25 of the data, the lower 25 percent and the upper 75 percent. |

`gamma` |
Sensitivity parameter, gamma>=1. |

`LS` |
If LS=TRUE, a large sample test is performed. If LS=FALSE, an exact test is performed. For LS=FALSE, the mh function in the 'sensitivity2x2xk' package is used. For LS=TRUE, the mhLS function in the 'sensitivity2x2xk' package is used. |

Performs a one-sided test of no association against positive association, together with a sensitivity analysis. The method is described in Rosenbaum (2016), used in Rosenbaum (2017). An adaptive cross-cut statistic is discussed in Rosenbaum and Small (2017); it cuts at several quantiles and picks the best. See Section 19.4 of "Design of Observational Studies"", second edition.

`quantiles ` |
Quantiles that define the crosscut |

`table ` |
A 2x2 table |

`output ` |
Output from mh or mhLS when applied to table. The functions mh and mhLS are from the sensitivity2x2xk package. The output includes a one-sided P-value. |

The 'crosscut' function makes use of 'mh' and 'mhLS' from the 'sensitivity2x2xk' package.

Paul R. Rosenbaum

Rosenbaum, P. R. (2016) <doi:10.1111/biom.12373> "The crosscut statistic and its sensitivity to bias in observational studies with ordered doses of treatment". Biometrics, 72(1), 175-183.

Rosenbaum, P. R. (2017) <doi:10.1214/17-STS621> "The general structure of evidence factors in observational studies". Statist Sci 32, 514-530.

Rosenbaum, P. R. and Small, D. S. (2017) <doi:10.1111/biom.12591> "An adaptive Mantelâ€“Haenszel test for sensitivity analysis in observational studies". Biometrics, 73(2), 422-430.

1 2 3 4 5 6 7 | ```
data(periodontal)
attach(periodontal)
crosscut(cigsperday[z==1],pcteither[z==1]-pcteither[z==0],ct=.2)
crosscut(cigsperday[z==1],pcteither[z==1]-pcteither[z==0],ct=.2,gamma=1.25)
crosscut(cigsperday[z==1],pcteither[z==1]-pcteither[z==0],ct=.2,gamma=1.25,LS=TRUE)
crosscut(cigsperday[z==1],pcteither[z==1]-pcteither[z==0],ct=1/3)
detach(periodontal)
``` |

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