`R/ti_ctplot.R`

`ti_ctplot.Rd`

The function for plotting the heatmap to evaluate the PPQ plan based on the specification test, given lower and upper specification limits.

ti_ctplot(attr.name, attr.unit, Llim, Ulim, mu, sigma, n, n.batch, alpha, coverprob, side, test.point)

attr.name | user-defined attribute name for PPQ assessment |
---|---|

attr.unit | user-defined attribute unit |

Llim | lower specification limit |

Ulim | upper specification limit |

mu | hypothetical mean of the attribute |

sigma | hypothetical standard deviation of the attribute |

n | sample size (number of locations) per batch |

n.batch | number of batches for passing PPQ during validation |

alpha | significant level for constructing the tolerance interval. |

coverprob | coverage probability for constructing the tolerance interval |

side | whether a 1-sided or 2-sided tolerance interval is required (determined by side = 1 or side = 2, respectively). |

test.point | (optional) actual process data points for testing whether the processes pass PPQ |

Heatmap (or Contour Plot) for PPQ Assessment.

Burdick, R. K., LeBlond, D. J., Pfahler, L. B., Quiroz, J., Sidor, L., Vukovinsky, K., & Zhang, L. (2017).
Statistical Applications for Chemistry, Manufacturing and Controls (CMC) in the Pharmaceutical Industry.
*Springer*.

`ti_pp`

and `ti_occurve`

.

Yalin Zhu

if (FALSE) { mu <- seq(95,105,0.1) sigma <- seq(0.1,2.5,0.1) ti_ctplot(attr.name = "Sterile Concentration Assay", attr.unit = "%", mu = mu, sigma = sigma, Llim=95, Ulim=105) ti_ctplot(attr.name = "Extractable Volume", attr.unit = "% of NV=1mL", Llim = 100, Ulim = Inf, mu=seq(100, 110, 0.5), sigma=seq(0.2, 15 ,0.5), n=40, alpha = 0.05, coverprob = 0.675, side=1) }