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1985 | Buch

Sequential Analysis

Tests and Confidence Intervals

verfasst von: David Siegmund

Verlag: Springer New York

Buchreihe : Springer Series in Statistics

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Über dieses Buch

The modern theory of Sequential Analysis came into existence simultaneously in the United States and Great Britain in response to demands for more efficient sampling inspection procedures during World War II. The develop­ ments were admirably summarized by their principal architect, A. Wald, in his book Sequential Analysis (1947). In spite of the extraordinary accomplishments of this period, there remained some dissatisfaction with the sequential probability ratio test and Wald's analysis of it. (i) The open-ended continuation region with the concomitant possibility of taking an arbitrarily large number of observations seems intol­ erable in practice. (ii) Wald's elegant approximations based on "neglecting the excess" of the log likelihood ratio over the stopping boundaries are not especially accurate and do not allow one to study the effect oftaking observa­ tions in groups rather than one at a time. (iii) The beautiful optimality property of the sequential probability ratio test applies only to the artificial problem of testing a simple hypothesis against a simple alternative. In response to these issues and to new motivation from the direction of controlled clinical trials numerous modifications of the sequential probability ratio test were proposed and their properties studied-often by simulation or lengthy numerical computation. (A notable exception is Anderson, 1960; see III.7.) In the past decade it has become possible to give a more complete theoretical analysis of many of the proposals and hence to understand them better.

Inhaltsverzeichnis

Frontmatter
Chapter I. Introduction and Examples
Abstract
In very general terms there are two reasons for introducing sequential methods into statistical analysis. One is to solve more efficiently a problem which has a fixed sample solution. The other is to deal with problems for which no fixed sample solution exists. It is the first category which is the primary concern of this book, but we begin here with a few comments about the second.
David Siegmund
Chapter II. The Sequential Probability Ratio Test
Abstract
We begin by recalling the Neyman-Pearson Lemma for testing a simple hypothesis against a simple alternative. Let x denote a (discrete or continuous) random variable (or vector) with probability density function f.
David Siegmund
Chapter III. Brownian Approximations and Truncated Tests
Abstract
The central role of the normal distribution in statistics arises because of its simplicity and usefulness as an approximation to other probability distributions. In sequential analysis considerable additional simplification results from approximating sums of independent random variables x l + · · · + x n in discrete time by a Brownian motion process W(t), 0 ≤ t < ∞ in continuous time. Although this approximation is rarely quantitatively adequate (cf. Section 5), its comparative simplicity leads to appreciable qualitative insight; and quantitatively it does provide a first, crude approximation which can often be used as a basis for subsequent refinement. This chapter is concerned primarily with sequential tests for the mean of a Brownian motion process. Various truncated modifications of the sequential probability ratio test will be introduced, and problems of estimates and attained significance levels relative to sequential tests will be discussed.
David Siegmund
Chapter IV. Tests with Curved Stopping Boundaries
Abstract
The stopping rules of Chapter II and III are defined by the crossing of linear boundaries by random walks (or Brownian motion). The linear boundaries arise naturally from sequential probability ratio tests of simple hypotheses against simple alternatives. For problems involving several parameters or composite hypotheses we shall want to consider curved stopping boundaries, which are more difficult to investigate; and only rarely can one obtain exact results even for Brownian motion.
David Siegmund
Chapter V. Examples of Repeated Significance Tests
Abstract
We consider below a number of examples of repeated significance tests in order to discover the extent to which the methods of Chapter IV can be adapted to a variety of more difficult problems. Often precise development of an asymptotic theory analogous to that obtained in Chapter IV for normally distributed data of known variability is complicated, and hence we shall concentrate on the use of normal approximations to obtain a rough idea of the probabilities and expected sample sizes involved. For continuously monitored tests Brownian motion provides simple approximations. For group tests one can use a discrete time normal approximation to take into account the sometimes substantial excess over the stopping boundary.
David Siegmund
Chapter VI. Allocation of Treatments
Abstract
In comparative studies generally and especially in clinical trials the allocation of treatments and the appropriate use of randomization are particularly important. The present chapter discusses three related aspects of this general subject, in the simple context of the comparison of two treatments. Section 1 is concerned with sequential two population randomization tests when allocation is at random. Section 2 gives a very brief introduction to the notion of biased randomization to force balancing in small experiments. Sections 3–5 involve the adaptive allocation of treatments during the course of experimentation in such a way that the less desirable treatment is used a minimum number of times. A central result is Theorem 6.20.
David Siegmund
Chapter VII. Interval Estimation of Prescribed Accuracy
Abstract
For a fixed sample problem the accuracy of an estimator of a parameter θ typically depends on the unknown value of θ and perhaps also on the value of an unknown nuisance parameter λ. To achieve estimators of prescribed accuracy, it seems natural to proceed sequentially, to get some preliminary idea of the value of (θ,λ) and use the preliniminary information to determine the final sample size.
David Siegmund
Chapter VIII. Random Walk and Renewal Theory
Abstract
Wald’s approximations to the power function and expected sample size of a sequential probability ratio test are based on ignoring the discrepancy between the (log) likelihood ratio and the stopping boundary, thus replacing a random variable by a constant. In what follows we develop methods to approximate this discrepancy and hence to obtain more accurate results. Some of the approximations have already been stated and used in III.5 and IV.3. The present chapter is concerned with linear stopping boundaries; and the more difficult non-linear case is discussed in Chapter IX. An alternative method for linear problems is given in Chapter X.
David Siegmund
Chapter IX. Nonlinear Renewal Theory
Abstract
This chapter is concerned with first passages of random walks to nonlinear boundaries. Suitable generalizations of the renewal theory of Chapter VIII are developed in order to justify and generalize the approximations suggested in IV.3.
David Siegmund
Chapter X. Corrected Brownian Approximations
Abstract
Although we have informally thought of Brownian motion as a continuous approximation to random walks in discrete time, the approximations of Chapters IV and V, which are developed more completely in Chapter IX, do not actually utilize this idea. For example, Theorem 9.54 and Corollary 9.55, which are used as partial justification for (4.40), (4.41), (4.49), and (4.50), involve probabilities of large deviations, which can be quite different for Brownian motion and for random walk in discrete time.
David Siegmund
Chapter XI. Miscellaneous Boundary Crossing Problems
Abstract
The subject of this chapter is several results which can be obtained by refinements of the methods developed in Chapters IV and IX. Some of them have already been used in Chapters IV and V.
David Siegmund
Backmatter
Metadaten
Titel
Sequential Analysis
verfasst von
David Siegmund
Copyright-Jahr
1985
Verlag
Springer New York
Electronic ISBN
978-1-4757-1862-1
Print ISBN
978-1-4419-3075-0
DOI
https://doi.org/10.1007/978-1-4757-1862-1