Description Usage Arguments Details Value See Also

`nestedRanksTest_Z`

is used by `nestedRanksTest`

to
calculate the Z-score for the ranks of responses `y`

divided
into two treatment levels.

1 | ```
nestedRanksTest_Z(y, n1, n2)
``` |

`y` |
Values to be ranked for the test. Its length must
be equal to the sum of |

`n1` |
The first |

`n2` |
The final |

Values across both treatments are ranked using the base R function
`rank`

with `ties.method = "average"`

, which assigns
tied values their average rank. The Mann-Whitney-Wilcoxon test
statistic is computed from these ranks. Because the value of the
statistic is sample-size dependent (between `-n1*n2`

and
`n1*n2`

), it is scaled to be `[-1,+1]`

by dividing by
`n1*n2`

.

The bottleneck for bootstrapping is calculation of ranks, so the most
straightforward way to speed up `nestedRanksTest`

would come from
speeding up `rank`

. Because of the checks performed prior to
calling this routine, it should be sufficient to use a stripped-down
function that simply does the equivalent of making an `.Internal`

call, which is not allowed within package code. As of this writing, this
is sufficient:

`rank_new <- function (x) .Internal(rank(x, length(x), "average"))`

For the example data this is 8-9 times faster than the base R `rank`

,
because it avoids error-checking overhead. For longer vectors, the
advantage decreases such that at 10000 elements it is 20-30%.

The calculated Z-score

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