We propose an adaptive truncated product method that facilitates the selection of the truncation point among a set of candidates. To efficiently estimate the distribution of the proposed method when the p-values are correlated, we develop a single-layer bootstrap procedure.

For general inferential families with a mixture of one- and two-sided inferences two procedures are proposed to compare several treatments with a control under heteroscedasticity. Critical constants required for the proposed procedures are tabulated, and a numerical example is given.