sumtest {robust2sls}

Scaling sum proportion test across different cut-offs

Description

sumtest() uses the estimations across several cut-offs to test whether the sum of the deviations between sample and population FODR differ significantly from its expected value. \[\sum_{k = 1}^{K} \sqrt{n}(\widehat{\gamma}_{c_{k}} - \gamma_{c_{k}}) \]

Usage

sumtest(robust2sls_object, alpha, iteration, one_sided = FALSE)

Arguments

robust2sls_object

A list of "robust2sls" objects.

alpha

A numeric value between 0 and 1 representing the significance level of the test.

iteration

An integer >= 0 or the character "convergence" that determines which iteration is used for the test.

one_sided

A logical value whether a two-sided test (FALSE) should be conducted or a one-sided test (TRUE) that rejects only when the false outlier detection rate is above its expected value.

Value

sumtest() returns a data frame with one row storing the iteration that was tested, the value of the test statistic (t-test), the type of the test (one- or two-sided), the corresponding p-value, the significance level, and whether the null hypothesis is rejected. The data frame also contains an attribute named "gammas" that records which gammas determining the different cut-offs were used in the scaling sum test.