Description Usage Arguments Details Value Author(s) Examples

View source: R/boot.paired.bca.R

Obtains a paired-samples confidence interval and (optionally) performs a paired-samples hypothesis test for the difference between two population means, using the BCa bootstrap method.

1 2 3 |

`x` |
a (non-empty) numeric vector of data values. |

`y` |
a (non-empty) numeric vector of data values. |

`variable` |
an optional character string that gives the name of the variable under consideration. |

`null.hyp` |
the null-hypothesis value; if omitted, no hypothesis test is performed. |

`alternative` |
a character string specifying the alternative hypothesis; must be one of "two.sided" (default), "greater", or "less". |

`conf.level` |
the confidence level (between 0 and 1); default is 0.95. |

`type` |
a character string specifying the type of CI; if user-supplied, must be one of "two-sided", "upper-bound", or "lower-bound"; defaults to "two-sided" if alternative is "two.sided", "upper-bound" if alternative is "less", and "lower-bound" if alternative is "greater". |

`R` |
the number of bootstrap replications; default is 9999. |

Note that `x`

and `y`

must have the same length, as together they represent
the paired data. Also note, for instance, that `alternative = "greater"`

is the
alternative that `x`

variable has a larger mean than `y`

variable.

A list with class "boot.paired" containing the following components:

`Boot.values ` |
the point estimates for the differences between the means obtained from the bootstrap. |

`Confidence.limits ` |
the confidence limit(s) for the confidence interval. |

`Header ` |
the main title for the output. |

`Variable ` |
the name of the variable under consideration or NULL |

`Pop.1 ` |
the first population. |

`Pop.2 ` |
the second population. |

`n ` |
the sample size. |

`Statistic ` |
the name of the statistic, here diff.mean. |

`Observed ` |
the observed point estimate for the difference between the means. |

`Replications ` |
the number of bootstrap replications. |

`Mean ` |
the mean of the bootstrap values. |

`SE ` |
the standard deviation of the bootstrap values. |

`Bias ` |
the difference between the mean of the bootstrap values and the observed value. |

`Percent.bias ` |
the percentage bias: 100*|Bias/Observed|. |

`Null ` |
the null-hypothesis value or NULL. |

`Alternative ` |
the alternative hypothesis or NULL. |

`P.value ` |
the P-value or a statement like P < 0.001 or NULL. |

`p.value ` |
the P-value or NULL. |

`Level ` |
the confidence level. |

`Type ` |
the type of confidence interval. |

`Confidence.interval ` |
the confidence interval. |

Neil A. Weiss

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
# The number of inappropriate words out of 10 that were identified in the
# Times New Roman (TNR) and Gigi fonts by each of 25 participants.
data("fonts")
str(fonts)
attach(fonts)
# 90% confidence interval for the difference between the mean number of
# inappropriate words out of 10 identified for the TNR and Gigi fonts.
boot.paired.bca(TNR, GIGI, conf.level = 0.90)
# A right-tailed test with null hypothesis 2, and a 95% (default) lower
# confidence bound for the difference between the mean number of
# inappropriate words out of 10 identified for the TNR and Gigi fonts.
boot.paired.bca(TNR, GIGI, null.hyp = 2, alternative = "greater")
# Not significant at the 5% level.
# A right-tailed test with null hypothesis 1, and a 95% (default) lower
# confidence bound for the difference between the mean number of
# inappropriate words out of 10 identifiedd for the TNR and Gigi fonts.
boot.paired.bca(TNR, GIGI, null.hyp = 1, alternative = "greater")
# Significant at the 5% level.
detach(fonts) # clean up
``` |

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