sumtest: Scaling sum proportion test across different cut-offs

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

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. \loadmathjax \mjdeqn\sum_k = 1^K \sqrtn(\widehat\gamma_c_k - \gamma_c_k) sum k = (1 to K) sqrt(n) (gammahat_c_k - gamma_ck)

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.

robust2sls documentation built on Jan. 11, 2023, 5:13 p.m.