Results 31 to 40 of about 15,601,125 (299)
Confidence Regions for the Multinomial Parameter With Small Sample Size [PDF]
Accepted for publication in Journal of the American Statistical Association (JASA)
Chafai, Djalil, Concordet, Didier
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Relative power and sample size analysis on gene expression profiling data [PDF]
Background: With the increasing number of expression profiling technologies, researchers today are confronted with choosing the technology that has sufficient power with minimal sample size, in order to reduce cost and time.
Boer, J.M. +29 more
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This study addresses the instability of statistical modeling for small-sample maximum friction torque data under multiple temperature conditions. Within the Weibull distribution framework, a sample-aggregation method is proposed, and a unified modeling ...
Shenglei Liu, Liqiang Zhang, Liyang Xie
doaj +1 more source
Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size Applications. [PDF]
In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of ...
Elias Chaibub Neto
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Recalibrating single-study effect sizes using hierarchical Bayesian models
IntroductionThere are growing concerns about commonly inflated effect sizes in small neuroimaging studies, yet no study has addressed recalibrating effect size estimates for small samples. To tackle this issue, we propose a hierarchical Bayesian model to
Zhipeng Cao +41 more
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Though small size samples can be planned and justified based on scarcity of time, money and manpower, there are situations making more accuracy a must and needing larger samples sizes. That’s why rare adverse drug reactions are identified only after a drug comes into the market and a large population is exposed to it.
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Why sample size estimates? [PDF]
Sample size estimates are critical to the planning and interpretation of clinical studies, whether they are descriptive or analytical. Too small a sample size will result in imprecise estimates in a descriptive study and failure to achieve ’statistical ...
Weber, Ellen J +3 more
core +1 more source
Prediction method of pipeline corrosion depth based on the correlation and Bayesian inference
The number of samples for detecting corrosion characteristic value is difficult to reach a large enough size in practical engineering, which leads to the pipeline corrosion evaluation results tend to be aggressive.
Kaikai CHENG +4 more
doaj +1 more source
Addressing the sample size problem in behavioural operational research: Simulating the newsvendor problem [PDF]
Laboratory-based experimental studies with human participants are beneficial for testing hypotheses in behavioural operational research. However, such experiments are not without their problems. One specific problem is obtaining a sufficient sample size,
Dimitriou, S. +8 more
core +1 more source
Research on Digital Twin Driven Rolling Bearing Model-Data Fusion Life Prediction Method
In industry, accurate remaining useful life (RUL) prediction is critical in improving system reliability and reducing downtime and accident risk. Numerous data-driven RUL prediction approaches have been proposed and achieved impressive performance in RUL
Wentao Zhao +5 more
doaj +1 more source

