Sample-Targeted Clinical Trial Adaptation

Authors: Ognjen Arandjelovic

AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental Experiments on simulated data are used to illustrate the effectiveness of our method and its application in practice. In this section we apply the derived results on experimental data, and evaluate and discuss the performance of the proposed methodology. We adopt the evaluation protocol standard in the domain of adaptive trials research, and obtain data using a simulated experiment.
Researcher Affiliation Academia Ognjen Arandjelovi c Centre for Pattern Recognition and Data Analytics Deakin University, Australia
Pseudocode No The paper describes mathematical derivations and concepts but does not include structured pseudocode or an algorithm block.
Open Source Code No The paper does not provide an explicit statement or link indicating that the source code for the described methodology is publicly available.
Open Datasets No We simulated a trial involving 180 individuals, half of which were assigned to the control and the other half to the treatment group. (The paper describes generating its own simulated data, not using a publicly available one.)
Dataset Splits No The paper describes a simulated experiment and its data generation process but does not specify any training, validation, or test dataset splits.
Hardware Specification No The paper does not specify any hardware details (e.g., CPU, GPU models, memory) used for running the experiments.
Software Dependencies No The paper does not specify any software dependencies with version numbers used for the experiments.
Experiment Setup Yes Experimental setup We simulated a trial involving 180 individuals, half of which were assigned to the control and the other half to the treatment group. The starting beliefs of participants, i.e. their beliefs before the onset of the trial, are initialized to: b(c) i = 1 for i = 1 . . . 9 0 for i = 10 . . . 81 1 for i = 82 . . . 90. w(t) i (k + 1) and w(c) i (k + 1) are drawn from Wt N(0.02, 0.05) and Wc N(0.00, 0.05) respectively. b(t) i (k + 1) = b(t) i (k) + 0.01 e(t) i (k + 1) + ω(t) i (k + 1)