Description Usage Arguments Details Author(s) References See Also Examples

The `hnplot`

function constructs a (half-) normal plot of effects (see Daniel 1959) that is traditionally used to identify active effects in a screening experiment. Reference lines and various other options and extensions are supported.

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`effects` |
Numeric vector of effects or contrasts to be explored. |

`ref` |
Logical value. If |

`half` |
Logical value. If |

`horiz` |
Logical value. If |

`method` |
Character value. When |

`a` |
The adjustment used in scaling and centering ranks in the interval (0, 1). The |

`col` |
Scalar or vector of colors; or a logical value. If logical, a value of |

`pch` |
Plotting character(s) to use. |

`alpha` |
Numeric value. If specified, a null reference distribution for |

`ID` |
Logical or numeric value. If logical and |

`...` |
Additional graphical parameters (see |

Use of `half = FALSE`

is not recommended because it can be misleading to the user. Inactive effects are those that are close to zero, and a regular normal plot displays deviations from normality rather than deviations from zero.

Russell V. Lenth

Daniel, C (1959)
Use of Half-Normal Plots in Interpreting Factorial Two-Level Experiments.
*Technometrics*, 1(4), 311-341

Mee, R (2015)
Discussion: Better, not Fewer, Plots.
*Journal of Quality Technology*, 47(2), 107-109

Other ways of assessing active effects include a dot plot with a reference curve (`refplot`

), a pareto plot of effects (see `parplot`

), and a tabular style of presenting effects and *P* values (see `eff.test`

). For more information on methods, see `PSE`

and `ref.dist`

.

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