Open AccessIdentification of Maximum Safe Dose Based on Ratio of Normally Distributed Data under Heteroscedasticity
Author(s) -
Emmanuel Dodzi Kpeglo,
Michael Jackson Adjabui,
Jakperik Dioggban
Publication year - 2022
Publication title -
journal of mathematics research
Language(s) - English
Resource type - Journals
eISSN - 1916-9809
pISSN - 1916-9795
DOI - 10.5539/jmr.v14n3p1
Subject(s) - heteroscedasticity , mathematics , confidence interval , homogeneity (statistics) , statistics , sample size determination , population , variance (accounting) , econometrics , medicine , environmental health , accounting , business
In most of the various stepwise confidence interval procedures formulated for identifying maximum safe dose (MSD), homogeneity of variances among different dose levels were required. But in practice, homogeneity of variance is often in doubt. This paper proposes a stepwise confidence set procedure for identifying MSD of drugs based on ratio of population means for normally distributed data under heteroscedasticity without the need for multiplicity adjustment. The procedure employed Fieller's method and obtained individual (1-α)100% confidence intervals for identification of the MSD. We illustrate the procedure with a real life example. In addition, we show that power of the procedure increases with increasing ratio of means, and sample size. Power however decreases with increase in clinical relevance margins. We also illustrate that the new procedure can properly control familywise error rate (FWER).