THE CONVERGENCE RATE OF SEQUENTIAL FIXED-WIDTH CONFIDENCE INTERVALS FOR REGULAR FUNCTIONALS

Let X₁X₂,.be i.i.d. random variables and let U_n= (n r)^-1S?^(n,r) h (X_i1,., X_ir,) be a U-statistic with EU_n= v, v unknown. Assume that g(X₁) =E[h(X₁,.,X_r) - v |X₁]has a strictly positive variance s?². Further, let a be such that φ(a) - φ(-a) =α for fixed α, 0 < α < 1, where φ is the standard normal d.f., and let S²_n be the Jackknife estimator of n Var U_n. Consider the stopping times N(d)= min {n: S²_n: + n^-1≤²a^-2},d > 0, and a confidence interval for v of length 2d,of the form I_n,d= [U_n,-d, Un + d]. We assume that Var U_n is unknown, and hence, no fixed sample size method is available for finding a confidence interval for v of prescribed width 2d and prescribed coverage probability α Turning to a sequential procedure, let I_N(d),d be a sequence of sequential confidence intervals for v. The asymptotic consistency of this procedure, i.e. lim_{d → 0}P(v ∈ I_N(d),d)=α follows from Sproule (1969). In this paper, the rate at which |P(v ∈ I_N(d),d) converges to α is investigated. We obtain that |P(v ∈ I_N(d),d) - α| = 0 (d^{1/2-(1+k)/2(1+m)}), d → 0, where K = max {0,4 - m}, under the condition that E|h(X₁, X_r)|^m < ∞m > 2. This improves and extends recent results of Ghosh & DasGupta (1980) and Mukhopadhyay (1981).     

ASYMPTOTIC EXPANSIONS APPLIED TO F-TEST CRITERIA

Using asymptotic expansions of the Kummer hypergeometric function, the sequential. F-test criterion is evaluated asymptotically in terms of the sample size. The continuation region inequalities for the test are inverted and expressed in terms of known test criteria. A rapidly converging algorithm for carrying out the sequential procedure is provided. This makes the F-test easier for the practitioner to use. Almost sure finite termination of the sequential. F-test is asserted by appealing to the continuation inequalities and a heuristic asymptotic expansion of the test criterion. Average stopping times of the sequential procedure for a variety of population means and population number configurations are tabulated. The computer symbolic manipulation program MAPLE was used to derive some formulae.     

An extension of play against the random past strategy. Choosing the right experts on IBM forecasts

In sequential plays with two players, the players have the opportunity to use information on opponents’ past moves in selecting a move for the current stage. Strategies for Player II are considered in our study, in particular, play against the random past (PRP) strategy. In this paper, PRP strategy will be reviewed and discussed. Hannan consistency of PRP strategy in term of regret (difference in average loss and an envelope loss) on k-extended Bayes envelope risk problem in matching binary bits game will be shown. The simulation of two-experts selection problem on real experts’ forecasting data of IBM share earnings confirms the consistency of PRP strategy.     

Design and analysis considerations for comparing dynamic treatment regimens with binary outcomes from sequential multiple assignment randomized trials

In behavioral, educational and medical practice, interventions are often personalized over time using strategies that are based on individual behaviors and characteristics and changes in symptoms, severity, or adherence that are a result of one's treatment. Such strategies that more closely mimic real practice, are known as dynamic treatment regimens (DTRs). A sequential multiple assignment randomized trial (SMART) is a multi-stage trial design that can be used to construct effective DTRs. This article reviews a simple to use ‘weighted and replicated’ estimation technique for comparing DTRs embedded in a SMART design using logistic regression for a binary, end-of-study outcome variable. Based on a Wald test that compares two embedded DTRs of interest from the ‘weighted and replicated’ regression model, a sample size calculation is presented with a corresponding user-friendly applet to aid in the process of designing a SMART. The analytic models and sample size calculations are presented for three of the more commonly used two-stage SMART designs. Simulations for the sample size calculation show the empirical power reaches expected levels. A data analysis example with corresponding code is presented in the appendix using data from a SMART developing an effective DTR in autism.     

A case study in identifying targeted patients population in major depressive disorder by enhanced enrichment design

Despite advances in clinical trial design, failure rates near 80% in phase 2 and 50% in phase 3 have recently been reported. The challenges to successful drug development are particularly acute in central nervous system trials such as for pain, schizophrenia, mania, and depression because high‐placebo response rates lessen assay sensitivity, diminish estimated treatment effect sizes, and thereby decrease statistical power. This paper addresses the importance of rigorous patient selection in major depressive disorder trials through an enhanced enrichment paradigm. This approach led to a redefinition of an ongoing, blinded phase 3 trial algorithm for patient inclusion (1) to eliminate further randomization of transient placebo responders and (2) to exclude previously randomized transient responders from the primary analysis of the double blind phase of the trial. It is illustrated for a case study for the comparison between brexpiprazole + antidepressant therapy and placebo + antidepressant therapy. Analysis of the primary endpoint showed that efficacy of brexpiprazole versus placebo could not be established statistically if the original algorithm for identification of placebo responders was used, but the enhanced enrichment approach did statistically demonstrate efficacy. Additionally, the enhanced enrichment approach identified a target population with a clinically meaningful treatment effect. Through its successful identification of a target population, the innovative enhanced enrichment approach enabled the demonstration of a positive treatment effect in a very challenging area of depression research.     

Management sampling for larvae of the colorado potato beetle

Summary Untreated plot of ‘Kennebec’ and ‘Superior’ potatoes were sampled for Colorado potato beetle (CPB) at L'Assomption, Quebec, in 1982, 1986 and 1987. Numbers of CPB larvae per stalk were counted on 74 occasions for sample sizes ranging from 50 to 200 stalks. Regression techniques were used to estimate the relationship between mean and cumulative proportion of stalks infected. These were used to set up binomial sequential probability ratio test (SPRT) sampling plans for pest management decision making with tally numbers (or tally thresholds, cutoff numbers) equal to 0,1,...10. A binomial scheme defined by tally number equal to 4 is proposed for general use, and corresponding plans are given, with estimated operating characteristic and average sample number curves.     

The exact risk performance of a pre-test estimator in a heteroskedastic linear regression model under the balanced loss function

We examine the risk of a pre-test estimator for regression coefficients after a pre-test for homoskedasticity under the Balanced Loss Function (BLF). We show analytically that the two stage Aitken estimator is dominated by the pre-test estimator with the critical value of unity, even if the BLF is used. We also show numerically that both the two stage Aitken estimator and the pre-test estimator can be dominated by the ordinary least squares estimator when “goodness of fit” is regarded as more important than precision of estimation.     

A Comparison of the Cost-efficiencies of the Sequential, Group-sequential, and Variable-sample-size-sequential Probability Ratio Tests

Wald and Wolfowitz (1948) have shown that the Sequential Probability Ratio Test (SPRT) for deciding between two simple hypotheses is, under very restrictive conditions, optimal in three attractive senses. First, it can be a Bayes-optimal rule. Second, of all level α tests having the same power, the test with the smallest joint-expected number of observations is the SPRT, where this expectation is taken jointly with respect to both data and prior over the two hypotheses. Third, the level α test needing the fewest conditional-expected number of observat ions is the SPRT, where this expectation is now taken with respect to the data conditional on either hypothesis being true. Principal among the strong restrictions is that sampling can proceed only in a one-at-a-time manner. In this paper, we relax some of the conditions and show that there are sequential procedures that strictly dominate the SPRT in all three senses. We conclude that the third type of optimality occurs rarely and that decision-makers are better served by looking for sequential procedures that possess the first two types of optimality. By relaxing the one-at-a-time sampling restriction, we obtain optimal (in the first two senses) variable-s ample-size- sequential probability ratio tests.     

序贯观察与选择问题解决策略的比较研究

序贯观察与选择问题是一类动态决策问题,描述了人们在优劣随机出现的备选择方案中,何时停止取样观察以获得最大的决策收益.已有研究证明,截止阀法则是解决该类决策问题的最主要方法之一.其中,一种策略是基于取样观察选项中的一个最大值选项为标杆,然后选择第一个大于此标杆的选项.若考虑决策的有限理性假设,决策者还可以基于取样观察选项中仅次于最大值的选项为标杆.很显然,标杆不同会导致序贯搜索选项的数量以及决策收益会有很大的差异.另外,还可以考虑基于"特定"事件的决策策略以及"变种"的标杆策略,本文分别就这几种标杆策略进行了系统地探讨与比较.     

有限理性下序贯价格竞争的动态演化

本文建立了两个企业的序贯价格竞争模型,基于有限理性预期调整,研究了企业博弈的动态演化特征,分析了模型的均衡解及其稳定性条件。研究发现,边界解和纳什均衡解是一定参数条件下的局部稳定均衡。基于有限理性的动态博弈能够实现基于完全信息的纳什均衡。单纯跟随策略是一定条件下的均衡策略,并能使跟随企业获得更高的销售价格。企业之间报价的相互跟随程度和企业预期的调整速度将会影响均衡点的稳定性。本文对模型进行了数值模拟分析,当参数不满足稳定性条件时会出现分岔、奇异吸引子等混沌现象。本文的主要研究结果对相关行业的企业竞争和稳定市场有启发意义。