  In this article, we study the hypothesis testing of the blip / net effects of
treatments in a treatment sequence. We illustrate that the likelihood ratio
test and the score test may suffer from the curse of dimensionality, the null
paradox and the high-dimensional constraint on standard parameters under the
null hypothesis. On the other hand, we construct the Wald test via a small
number of point effects of treatments in single-point causal inference. We show
that the Wald test can avoid these problems under the same assumptions as the
Wald test for testing the point effect of treatment. The simulation study
illustrates that the Wald test achieves the nominal level of type I error and a
low level of type II error. A real medical example illustrates how to conduct
the Wald test in practice.
