1,720,972 research outputs found
The effects of adaptation on maximum likelihood inference for nonlinear models with normal errors
No full textThis work studies the properties of the maximum likelihood estimator (MLE) of a multidimensional parameter in a nonlinear model with additive Gaussian errors. The observations are collected in a two-stage experimental design and are dependent because the second stage design is determined by the observations at the first stage. The MLE maximizes the total likelihood.
Unlike most theory in the literature, the approximation made to the distribution of the MLE only involves taking the second stage sample size to infinity, as the resulting approximate model retains the dependency between stages, and therefore, more closely reflects the actual two-stage experiment.
It is proved that the MLE is consistent and that its asymptotic distribution is a specific Gaussian mixture, via stable convergence. Finally, the efficiency of the adaptive procedure relative to the fixed procedure is illustrated by a simulation study under three parameter dose–response Emax and Exponential models
A New Approach to Dose Finding For Phase I Clinical Trials
No full textIn a phase I clinical trial, we are interested in finding a dose J-L that will produce toxicity at an acceptable probability level r in the target population. In this paper, we investigate different estimators of the target dose 1-l to be used with the up-and-down Biased Coin Design (BCD) introduced by Durham and Flournoy (1994). These estimators of 1-l are derived using isotonic regression, maximum likelihood, weighted lea.c:;t squares and the simple empirical mean. Given a vector of probability of toxicity at the different doses,we show how to derive the exact distribution of these (and many other) estimators in the BCD setting. However, due to computational limitations, for modest samples (n > 15) the exact method becomes infeasible and bootstrap methods are used. A modified isotonic regression estimate is shown to perform very well, in terms of mean square error (MSE) and average time to converge, in all the scenarios we have studied.
Key Words: Up-and-down design, isotonic regression, sequential estimation, quantal estimation, logistic regression, experimental design
Multivariate Optimizing Up and Down Design
No full textSuppose we are interested in finding the optimal dose of two drugs (for example, Tylenol and Aspirin), that is, we are interested in determining the dose combination that maximizes the probability of patients’ success. We assume responses are binary, either failure or success, and that the treatments to be used in the study are selected from a lattice of combination drugs. We extend the univariate Optimizing Up-and-Down Design of Kpamegan (2001), using ideas from stochastic approximation, in a way that the number of subjects at each stage is independent of the number of predictor variables (e.g. drugs).
keywords and phrases: Simultaneous perturbation stochastic approximation, Adaptive designs, Optimal dose, Phase II clinical trials, Markov chain, combination therapy, random walk, up-and-down designs, dose finding
A new tool for comparing adaptive designs; a posteriori efficiency
No full textIn this work, we consider an adaptive linear regression model designed to explain the patient’s response in a clinical trial. Patients are assumed to arrive sequentially. The adaptive nature of this statistical model allows the error terms to depend on the past which has not been permitted in other adaptive models in the literature.
Some techniques of the theory of optimal designs are used in this framework to define new concepts: a-posteriori efficiency and mean a-posteriori efficiency. We then explicitly relate the variance of the allocation rule to the mean a-posteriori efficiency. These measures are useful for studying the comparative performance of adaptive designs. As an example, a comparative study is made among several design- adaptive designs to establish their properties with respect to a criterion of interest
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A Graphical Method for Comparing Response-Adaptive Randomization Procedures
No full textResponse-adaptive randomization procedures have a dual goal of estimating the treatment effect and randomizing patients with a higher probability of receiving the superior treatment. These are competing objectives, and no procedure in the literature is “perfect” with respect to both objectives. For clinical trials of two treatments, we discuss metrics for comparing response-adaptive randomization procedures that can be represented graphically to compare designs. These metrics involve the simulated distribution of the set of jointly sufficient statistics for estimating functions of the unknown parameters. We explore the binary response and normal cases, and compare numerous procedures found in the literature. We distinguish between metrics of efficiency and metrics that measure ethical cost. Each of these is a function of the joint sufficient statistics. When graphed against each other, we can gauge competing designs in obtaining these competing objectives. We find that, contrary to asymptotic results, tuning parameters that affect the variability of the procedure do not have much impact in the finite case. We also find that procedures that target an optimal allocation based on ethical and efficiency considerations generally provide a better compromise design than procedures that do not
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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