Related Experiment Video
Updated: Sep 17, 2025

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
Published on: November 22, 2019
Rollout designs for lump-sum data
Qunzhi Xu1, Hongzhen Tian2, Ananda Sarkar2
1Department of Biostatistics, School of Global Public Health, New York University, New York, NY, USA.
Abstract:
This work studies rollout design problems with a focus of suitable choices of rollout rate under the standard Type I and Type II error probabilities control framework. The main challenge of rollout design is that data is often observed in a lump-sum manner from a spatio-temporal point of view: (1) temporally, only the sum of data in a given sliding time window can be observed; (2) spatially, there are two subgroups for the data at each time step: control and treatment, but one can only observe the total values instead of individual values from each subgroup. We develop rollout tests of lump-sum data under both fixed-sample-size and sequential settings, subject to the constraints on Type I and Type II error probabilities. Numerical studies are conducted to validate our theoretical results.
Related Concept Videos
Design Example: Aggregate Gradation
The grading, or particle-size distribution, of sand is determined using sieve analysis, with standard sizes ranging from 150 μm to 10 mm (ASTM No. 100 sieve to 3⁄8 in. sieve). Sand is...
Distributed Loads: Problem Solving
Resultant of a General Distributed Loading
Examples such as load distribution due to wind and load distribution on a bridge illustrate how this concept is used to analyze and design safe, reliable structures under variable loading conditions. Most structures, such as residential buildings, bridges, and towers, are...
Rolling With Slipping
An object's rolling motion is characterized by its rotation around its axis, while linear motion refers to the object's translational motion along a surface. Frictional forces can...
Rolling Without Slipping
Randomized Experiments
Simple randomization
Simple...

