scholarly journals Conditional estimation after a two-stage diagnostic biomarker study that allows early termination for futility

2012 ◽  
Vol 31 (5) ◽  
pp. 420-435 ◽  
Author(s):  
Joseph S. Koopmeiners ◽  
Ziding Feng ◽  
Margaret Sullivan Pepe
Keyword(s):  
Early Termination ◽  
Diagnostic Biomarker ◽  
Two Stage ◽  
Conditional Estimation

scholarly journals Conditional estimation of sensitivity and specificity from a phase 2 biomarker study allowing early termination for futility

2008 ◽  
Vol 28 (5) ◽  
pp. 762-779 ◽  
Author(s):  
Margaret Sullivan Pepe ◽  
Ziding Feng ◽  
Gary Longton ◽  
Joseph Koopmeiners
Keyword(s):  
Sensitivity And Specificity ◽  
Early Termination ◽  
Phase 2 ◽  
Conditional Estimation

A Two-Stage Conditional Estimation Procedure for Unrestricted Latent Class Models

1980 ◽  
Vol 5 (2) ◽  
pp. 129-156 ◽  
Author(s):  
George B. Macready ◽  
C. Mitchell Dayton
Keyword(s):  
General Class ◽  
Latent Class ◽  
Estimation Procedure ◽  
Error Rates ◽  
Latent Class Models ◽  
Parameter Estimates ◽  
Probability Models ◽  
Two Stage ◽  
Conditional Estimation ◽  
Class Models

A variety of latent class models has been presented during the last 10 years which are restricted forms of a more general class of probability models. Each of these models involves an a priori dependency structure among a set of dichotomously scored tasks that define latent class response patterns across the tasks. In turn, the probabilities related to these latent class patterns along with a set of “Omission” and “intrusion” error rates for each task are the parameters used in defining models within this general class. One problem in using these models is that the defining parameters for a specific model may not be “identifiable.” To deal with this problem, researchers have considered curtailing the form of the model of interest by placing restrictions on the defining parameters. The purpose of this paper is to describe a two-stage conditional estimation procedure which results in reasonable estimates of specific models even though they may be nonidentifiable. This procedure involves the following stages: (a) establishment of initial parameter estimates and (b) step-wise maximum likelihood solutions for latent class probabilities and classification errors with iteration of this process until stable parameter estimates across successive iterations are obtained.

scholarly journals Two-stage biomarker panel study and estimation allowing early termination for futility

Biostatistics ◽  
2015 ◽  
Vol 16 (4) ◽  
pp. 799-812 ◽  
Author(s):  
Shanshan Zhao ◽  
Yingye Zheng ◽  
Ross L. Prentice ◽  
Ziding Feng
Keyword(s):  
Panel Study ◽  
Early Termination ◽  
Two Stage ◽  
Biomarker Panel

scholarly journals Two-stage aerodynamic optimization method based on early termination of CFD convergence and variable-fidelity model

2021 ◽  
Vol 39 (1) ◽  
pp. 148-158
Author(s):  
Ji Miao ◽  
Chunlin Gong ◽  
Chunna Li
Keyword(s):  
Optimization Method ◽  
Aerodynamic Performance ◽  
Early Termination ◽  
Computational Time ◽  
High Fidelity ◽  
Aerodynamic Optimization ◽  
Two Stage ◽  
Optimization Stage ◽  
Variable Fidelity ◽  
Fidelity Model

Efficient aerodynamic design optimization method is of great value for improving the aerodynamic performance of little UAV's airfoil. Using engineering or semi-engineering estimation method to analyze aerodynamic forces in solving aerodynamic optimization problems costs little computational time, but the accuracy cannot be guaranteed. However, CFD method ensuring high accuracy needs much more computational cost, which is unfordable for optimization. Surrogate-based optimization can reduce the number of high-fidelity analyses to increase the optimization efficiency. However, the cost of CFD analyses is still huge for aerodynamic optimization due to multiple design variables, multi-optimal and strong nonlinearities. To solve this problem, a two-stage aerodynamic optimization method based on early termination of CFD convergence and variable-fidelity model is proposed. In the first optimization stage, the solutions by early termination CFD convergence and the convergenced CFD solutions are regarded as low-and high-fidelity data respectively for building variable-fidelity model. Then, the multi-island genetic algorithm is used in the global optimization based on the built variable-fidelity model. The modeling efficiency can be greatly improved due to many cheap low-fidelity data. In the second stage optimization, the global optimum from the first optimization stage is treated as the start of the Hooke-Jeeves algorithm to search locally based on convergenced CFD computations in order to acquire better-optimum. The proposed method is utilized in optimizing the aerodynamic performance of the airfoil of little UAV, and is compared with the EGO method based on single-fidelity Kriging surrogate model. The results show that the present two-level aerodynamic optimization method consumes less time.

scholarly journals Conditional estimation in two-stage adaptive designs

Biometrics ◽  
2017 ◽  
Vol 73 (3) ◽  
pp. 895-904 ◽  
Author(s):  
Per Broberg ◽  
Frank Miller
Keyword(s):  
Adaptive Designs ◽  
Two Stage ◽  
Conditional Estimation

scholarly journals Early termination of a two-stage study to develop and validate a panel of biomarkers

2012 ◽  
Vol 32 (6) ◽  
pp. 1027-1037 ◽  
Author(s):  
Joseph S. Koopmeiners ◽  
Rachel Isaksson Vogel
Keyword(s):  
Early Termination ◽  
Two Stage

scholarly journals Two-stage procedures for selecting the best diagnostic biomarkers

2008 ◽  
Vol 366 (1874) ◽  
pp. 2293-2299
Author(s):  
Aiyi Liu ◽  
Chengqing Wu ◽  
Kai F Yu
Keyword(s):  
Joint Distribution ◽  
Nuisance Parameters ◽  
Correct Selection ◽  
Diagnostic Biomarker ◽  
Two Stage ◽  
Classification Rate ◽  
Diagnostic Biomarkers ◽  
Probability Of Correct Selection ◽  
Simulation Results ◽  
Dichotomous Outcomes

Considered in the paper is the problem of selecting a diagnostic biomarker that has the highest classification rate among several candidate markers with dichotomous outcomes. The probability of correct selection depends on a number of nuisance parameters from the joint distribution of the biomarkers and thus can be substantially affected if these nuisance parameters are misspecified. A two-stage procedure is proposed to compute the needed sample size that achieves the desired level of correct selection, as so confirmed by simulation results.

Two-stage self-seeding method for preparation of single crystals of poly(phenylene sulfide)

1989 ◽  
Vol 47 ◽  
pp. 368-369
Author(s):  
Sengshiu Chung ◽  
Peggy Cebe
Keyword(s):  
Single Crystals ◽  
High Performance ◽  
Dilute Solution ◽  
Two Stage ◽  
Annealing Behavior ◽  
High Performance Polymers ◽  
Seeding Method ◽  
Phenylene Sulfide

We are studying the crystallization and annealing behavior of high performance polymers, like poly(p-pheny1ene sulfide) PPS, and poly-(etheretherketone), PEEK. Our purpose is to determine whether PPS, which is similar in many ways to PEEK, undergoes reorganization during annealing. In an effort to address the issue of reorganization, we are studying solution grown single crystals of PPS as model materials.Observation of solution grown PPS crystals has been reported. Even from dilute solution, embrionic spherulites and aggregates were formed. We observe that these morphologies result when solutions containing uncrystallized polymer are cooled. To obtain samples of uniform single crystals, we have used two-stage self seeding and solution replacement techniques.

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