ArticleScientific reports2024
Design and modeling of order of addition experiment with component effects.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Two-level non-regular fractional factorial designs for public health studies.BMC medical research methodology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
An order of addition experiment is an experiment to study how the order of addition of components affect the results, with the objective of predicting and determining the optimal order of addition of components. Order of addition experiment are also commonly used in the drug combination therapy, where experimenting with all drugs combinations is unaffordable. To solve this problem, we constructed a new design table, two-level component factorial design table (TLCF), which combine the component orthogonal array design table and the two-level partial factorial design table by matrix product. TLCF can explore the order and dosage effect of components on the results and can greatly reduce the number of experiments. We also prove that the relative D-efficiency of the TLCF can reach 100% and solve an explicit expression for the D-efficiency of the full design. In the simulation experiment, we compare the D-efficiency of the TLCF with the random design table to prove the superiority of TLCF. Finally, we give a treatment plan for the combination of three drugs for glioblastoma based on the TLCF, which provides a new perspective for the precision treatment of patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.