SEQUENTIAL ESTIMATION IN EXPONENTIAL CLINICAL TRIALS

指数临床试验中的序贯估计

• 批准号: 3291347
• 负责人: NITIS MUKHOPADHYAY
• 金额: $ 3.1万
• 依托单位: UNIVERSITY OF CONNECTICUT STORRS
• 依托单位国家: 美国
• 财政年份: 1985
• 资助国家: 美国
• 起止时间: 1985-09-01 至 1986-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3291347
• 关键词: computer simulation; human mortality; human therapy evaluation; mathematical model; statistics /biometry

Patients are allocated to indenpendent treatments A sub 1, A sub 2, and we observe the subjects survival times which are assumed to have the probability density function f (x; mu sub i, sigma sub i) under the treatment A sub i with f (x; mu, sigma) = sigma minus 1 exp (-(x-mu)/sigma) for x greater than mu, i = 1,2. We let mu sub i epsilon equal from minus infinity to infinity, sigma sub i epsilon equal zero to infinity, and i equaling 1,2. The problems of constructing fixed width confidence intervals of mu sub 1, a minimum risk permit estimator of theta sub 1, a minimum risk estimator of sigma sub 1 for the treatment A sub 1 are discussed. For these series of one-sample problems for A sub 1 (similarly A sub 2), the modified two-stage, sequential and three-stage procedures are utilized. The problem of constructing fixed-width confidence intervals for mu sub 1 - mu sub 2, a minimum risk point estimator of theta sub 1- theta sub 2 are also studied. In the two sample case when the form of the density function is unspecified, a fixed width confidence interval is proposed for mu sub 1- mu sub 2. Again, modified two-stage, sequential and thru-stage procedures are utilized. Extensive uses of the computer simulations will be made to study the moderate sample performances of all the proposed procedures. Various theoretical expansions of some characteristics of our procedures will be studied via non-linear renewal theory. This comprehensive study will fill many significant gaps in the existing literature of sequential exponential clinical trials, and also it will definitely open up many other avenues of interesting research in the future.

患者被分配到独立治疗A sub 1，A sub 2，我们 观察受试者的生存时间， 概率密度函数f（x; mu sub i，sigma sub i）， f（x; mu，sigma）= sigma-1 exp（-（x-mu）/sigma）的处理A sub i 对于大于μ的x，i = 1，2。 我们让mu sub i等于 无穷大到无穷大，sigma sub i等于零到无穷大，并且i 等于1，2 本文讨论了mu sub 1的定宽置信区间的构造问题， θ sub 1的最小风险允许估计量，θ sub 1的最小风险估计量， 讨论了处理Asub 1的σ sub 1。 对于这一系列的 单样本问题为A分1（类似A分2），修改后的 采用两阶段、连续和三阶段的方法。 本文讨论了μ sub 1 - μ sub 2，theta sub 1- theta sub 2的最小风险点估计是 并研究了 在两个样本的情况下，当密度函数的形式 是未指定的，一个固定宽度的置信区间，建议为mu sub 1- mu sub 2. 同样，改进的两阶段、顺序和贯穿阶段程序 被利用。 将广泛使用计算机模拟来研究 所有拟议程序的样本性能适中。 各种 我们程序的一些特征的理论扩展将是 通过非线性更新理论研究。 这项全面的研究将填补 在现有的文献中的许多显着差距的顺序指数 临床试验，而且它肯定会开辟许多其他途径， 未来的有趣研究。