proptest: Proportion test

In robust2sls: Outlier Robust Two-Stage Least Squares Inference and Testing

Proportion test

Description

proptest() conducts a test whether the false outlier detection rate (FODR) in the sample deviates significantly from its expected value (population FODR) under the null hypothesis that there are no outliers in the sample.

Usage

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

Arguments

robust2sls_object	An object of class "robust2sls" or a list of such 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.

Details

See outlier_detection() and multi_cutoff() for creating an object of class "robust2sls" or a list thereof.

Value

proptest() returns a data frame with the iteration (m) to be tested, the actual iteration that was tested (generally coincides with the iteration that was specified to be tested but is the convergent iteration if the fixed point is tested), the setting of the probability of exceeding the cut-off (gamma), the type of t-test (one- or two-sided), the value of the test statistic, its p-value, the significance level alpha, and the decision. The number of rows of the data frame corresponds to the length of the argument robust2sls_object.

robust2sls documentation built on June 8, 2025, 10:28 a.m.