Providing the confidence interval of Spearman's rank correlation by Bootstrap, and define the specific H0 as per your request, that is based on Fisher's Z transformation of the correlation but with the variance recommended by Bonett and Wright (2000), not the same as Pearson's.

## Usage

```
spearmanTest(
x,
y,
h0 = 0,
conf.level = 0.95,
alternative = c("two.sided", "less", "greater"),
nrep = 1000,
rng.seed = NULL,
...
)
```

## Arguments

- x
(

`numeric`

)

one measurement.- y
(

`numeric`

)

another measurement.- h0
(

`numeric`

)

a specified hypothesized value of the difference between the two correlations, default is 0.- conf.level
(

`numeric`

)

significance level for the returned confidence interval and hypothesis.- alternative
(

`string`

)

string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less".- nrep
(

`integer`

)

number of replicates for bootstrapping, default is 1000.- rng.seed
(

`integer`

)

number of the random number generator seed for bootstrap sampling. If set to NULL currently in the R session used RNG setting will be used.- ...
other arguments to be passed to

`cor.test()`

.

## Value

a named vector contains correlation coefficient (`cor`

), confidence
interval(`lowerci`

and `upperci`

), Z statistic (`Z`

) and p-value (`pval`

)

## See also

`cor.test()`

`boot()`

to see the detailed arguments.

## Examples

```
x <- c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1)
y <- c(2.6, 3.1, 2.5, 5.0, 3.6, 4.0, 5.2, 2.8, 3.8)
spearmanTest(x, y, h0 = 0.5, alternative = "greater")
#> $stat
#> cor lowerci upperci Z pval
#> 0.6000000 -0.1581140 0.9765538 0.3243526 0.3728355
#>
#> $method
#> [1] "Spearman's correlation"
#>
#> $conf.level
#> [1] 0.95
#>
```