Description Usage Arguments Details Value Author(s) References Examples

Estimates the calibration equation based on CV information

1 | ```
calfun(x, y, CVx, CVy = CVx, lambda0 = 1)
``` |

`x` |
old VD measurements |

`y` |
reference (new) VD measurements |

`CVx` |
CV% of the old VD measurements |

`CVy` |
CV% of the new VD measurements |

`lambda0` |
the CV ratio of the new vs old measurements |

Estimation of the calibration equation. It covers 4 scenarios: Only CVx is known; only CVy is known; both CVx and CVy are known; and Only the ratio of CVy to CVx is known.

`coef ` |
estimated coefficients of the linear function |

`se ` |
standard errors of the estimated coefficients |

`lower CI` |
the lower end of the 95% CI of the regression coefficients |

`upper CI` |
the upper end of the 95% CI of the regression coefficients |

Durazo-Arvizu, Ramon; Sempos, Chris; Tian, Lu

Tian L., Durazo-Arvizu R. A., Myers G., Brooks S., Sarafin K., and Sempos C. T. (2014), The estimation of calibration equations for variables with heteroscedastic measurement errors, Statist. Med., 33, pages 4420-4436

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