Intelligent Constructing Efficient Statistical Decisions via Pivot-Based Elimination of Unknown (Nuisance) Parameters from Underlying Models

2021 ◽  
Vol 55 (5) ◽  
pp. 469-489
Author(s):  
N. A. Nechval ◽  
G. Berzins ◽  
K. N. Nechval ◽  
Zh. Tsaurkubule
Methodology ◽  
2018 ◽  
Vol 14 (4) ◽  
pp. 188-196 ◽  
Author(s):  
Esther T. Beierl ◽  
Markus Bühner ◽  
Moritz Heene

Abstract. Factorial validity is often assessed using confirmatory factor analysis. Model fit is commonly evaluated using the cutoff values for the fit indices proposed by Hu and Bentler (1999) . There is a body of research showing that those cutoff values cannot be generalized. Model fit does not only depend on the severity of misspecification, but also on nuisance parameters, which are independent of the misspecification. Using a simulation study, we demonstrate their influence on measures of model fit. We specified a severe misspecification, omitting a second factor, which signifies factorial invalidity. Measures of model fit showed only small misfit because nuisance parameters, magnitude of factor loadings and a balanced/imbalanced number of indicators per factor, also influenced the degree of misfit. Drawing from our results, we discuss challenges in the assessment of factorial validity.


1996 ◽  
Vol 28 (2) ◽  
pp. 336-337
Author(s):  
Hulling Le

Two sets of k labelled points, or configurations, in ℝm are defined to have the same shape if they differ only in translation, rotation and scaling. An important matter in practice is the estimation of the shape of the means; the shape determined by the means of data on the vertices of configurations. However, statistical models for vertices-based shapes always involve some unknown samplewise nuisance parameters associated with ambiguity of location, rotation and scaling. The use of procrustean mean shapes for a finite set of configurations, which are usually formulated directly in terms of their vertices, will enable one to eliminate these nuisance parameters.


Author(s):  
Alessandro Baldi Antognini ◽  
Marco Novelli ◽  
Maroussa Zagoraiou

AbstractThe present paper discusses drawbacks and limitations of likelihood-based inference in sequential clinical trials for treatment comparisons managed via Response-Adaptive Randomization. Taking into account the most common statistical models for the primary outcome—namely binary, Poisson, exponential and normal data—we derive the conditions under which (i) the classical confidence intervals degenerate and (ii) the Wald test becomes inconsistent and strongly affected by the nuisance parameters, also displaying a non monotonic power. To overcome these drawbacks, we provide a very simple solution that could preserve the fundamental properties of likelihood-based inference. Several illustrative examples and simulation studies are presented in order to confirm the relevance of our results and provide some practical recommendations.


Economica ◽  
1955 ◽  
Vol 22 (87) ◽  
pp. 279
Author(s):  
M. Shubik ◽  
David Blackwell ◽  
M. A. Girshick

2006 ◽  
Vol 1 (4) ◽  
pp. 3 ◽  
Author(s):  
Li Zhang ◽  
Margaret Sampson ◽  
Jessie McGowan

Introduction - This study applied the principles of evidence based information practice to clarify the role of information specialists and librarians in the preparation of Cochrane systematic reviews and to determine whether information specialists impact the quality of searching in Cochrane systematic reviews. Objectives - This research project sought to determine how the contribution of the person responsible for searching in the preparation of Cochrane systematic reviews was reported; whether the contribution was recognized through authorship or acknowledgement; the qualifications of the searcher; and the association between the type of contributorship and characteristics of the search strategy, assessability, and the presence of certain types of errors. Methods - Data sources: The Cochrane Database of Systematic Reviews, The Cochrane Library 3 (2002). Inclusion criteria: The study included systematic reviews that met the following criteria: one or more sections of the Cochrane Highly Sensitive Search Strategy were utilised, primary studies were either randomised controlled trials (RCTs) or quasi-RCTs, and included and excluded studies were clearly identified. Data extraction: Two librarians assessed the searches for errors, establishing consensus on discordant ratings. Results - Of the 169 reviews screened for this project, 105 met all eligibility criteria. Authors fulfilled the searching role in 41.9% of reviews studied, acknowledged persons or groups in 13.3%, a combination in 9.5%, and the role was not reported in 35.2% of reviews. For the 78 reviews in which meta-analyses were performed, the positions of those responsible for statistical decisions were examined for comparative purposes. The statistical role was performed by an author in 47.4% of cases and unreported in the same number of cases. Insufficient analyzable data was obtained regarding professional qualifications (3/105 for searching, 2/78 for statistical decisions). Search quality was assessed for 66 searches across 74 reviews. In general, it was more possible to assess the search quality when the searcher role was reported. An association was found between the reporting of searcher role and the presence of a consequential error. There was no association between the number of consequential errors and how the contribution of the searcher was reported. Conclusions - Qualifications of the persons responsible for searching and statistical decision-making were poorly reported in Cochrane reviews, but more complete role reporting is associated with greater assessability of searches and fewer substantive errors in search strategies.


2018 ◽  
Vol 15 (4) ◽  
pp. 352-358 ◽  
Author(s):  
Pamela A Shaw

Before a novel treatment can be deemed a clinical success, an assessment of its risk–benefit profile must be made. One of the inherent challenges for this assessment comes from the multiplicity that arises from comparing treatment groups across multiple outcomes. Composite outcomes that summarize a patient’s clinical status, or severity, across a prioritized list of safety and efficacy outcomes have become increasing popular. In this article, we review these approaches and illustrate through examples some of the challenges and complexities of a composite derived from prioritized outcomes, such as the win ratio. These challenges include the difficult tension between the analytical validity that comes from choosing a pre-specified outcome and an evaluation that is responsive to unexpected safety events that arise during the course of a trial. Other challenges include a sensitivity of the resulting test statistic to the underlying censoring distribution and other nuisance parameters. Approaches that resolve some of the difficulties of the analytical challenges associated with prioritized outcomes are then discussed. Ultimately, a composite outcome of net clinical benefit is another decision tool, but one to be used alongside more traditional analyses of efficacy and safety, and with the broader perspective that investigators, the data safety monitoring board, and regulators bring to an evaluation of risk–benefit.


Author(s):  
D. V. Lindley ◽  
Morris de Groot

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