Moving Towards the Post p < 0.05 Era via the Analysis of Credibility

ABSTRACT

It is now widely accepted that the techniques of null hypothesis significance testing (NHST) are routinely misused and misinterpreted by researchers seeking insight from data. There is, however, no consensus on acceptable alternatives, leaving researchers with little choice but to continue using NHST, regardless of its failings. I examine the potential for the Analysis of Credibility (AnCred) to resolve this impasse. Using real-life examples, I assess the ability of AnCred to provide researchers with a simple but robust framework for assessing study findings that goes beyond the standard dichotomy of statistical significance/nonsignificance. By extracting more insight from standard summary statistics while offering more protection against inferential fallacies, AnCred may encourage researchers to move toward the post p?<?0.05 era.     

Data-Informed Collection Decisions Using R

ABSTRACT

Collection decisions can seem daunting to a librarian who is new to the job. In charge of many new-to-her subject fund codes, the author wanted to understand what had been previously purchased using these funds and how to effectively manage a custom ebook collection. The author used the R programming language to clean and merge purchase and usage data. This article will provide an overview of tasks in R that can be leveraged for making data-informed collection decisions and for sharing information with colleagues.     

Building a Sustainable Collection Review Process: Managing Qualitative and Quantitative E-Resource Data over Time

Abstract

Comprehensive e-resource reviews often happen in response to financial crises. Data are collected, and faculty are consulted about reductions. After the review, the data are forgotten or lost until the next crisis. Librarians at one public institution were initially motivated by a financial crisis to review their e-resources. But, they also wanted to use this crisis as a means to develop persistent review criteria and a longitudinal review process. This article will summarize how they identified the principal stakeholders, review criteria, essential data, workflows, and management application to support a process that would transcend a single crisis.     

Robust bootstrap densities for dynamic conditional correlations: implications for portfolio selection and Value-at-Risk

ABSTRACT

Many financial decisions such as portfolio allocation, risk management, option pricing and hedge strategies are based on the forecast of the conditional variances, covariances and correlations of financial returns. Although the decisions depend on the forecasts covariance matrix little is known about effects of outliers on the uncertainty associated with these forecasts. In this paper we analyse these effects on the context of dynamic conditional correlation models when the uncertainty is measured using bootstrap methods. We also propose a bootstrap procedure to obtain forecast densities for return, volatilities, conditional correlation and Value-at-Risk that is robust to outliers. The results are illustrated with simulated and real data.     

Determining Usage When Vendors Do Not Provide Data

ABSTRACT

When library resource vendors do not provide usage data in consistent, manipulable formats, librarians must find other means to enable themselves to make data-driven collection development decisions. At Eastern Kentucky University (EKU) Libraries, two different approaches have been implemented: OpenURL link resolver analysis and EZproxy log analysis using grep, a GNU open source command-line utility. This column provides an overview of each solution.     

Influence diagnostics for stratified ordinal contingency tables

Influence diagnostics are investigated in this study. In particular, an approach based on the generalized linear mixed model setting is presented for formulating ordered categorical counts in stratified contingency tables. Deletion diagnostics and their first-order approximations are developed for assessing the stratum-specific influence on parameter estimates in the models. To illustrate the proposed model diagnostic technique, the method is applied to analyze two sets of data: a clinical trial and a survey study. The two examples demonstrate that the presence of influential strata may substantially change the results in ordinal contingency table analysis.     

Leveraging Vendor Assessments of Usage Data

ABSTRACT

This article summarizes a presentation given at the 2017 North Carolina Serials Conference by Judith Nagata. The speaker discussed how her library used vendor-supplied usage data and graphic representations of that data to make decisions about journals and journal packages.     

Two-stage generalized moment method approach for bidimensional random coefficient autoregressive models

ABSTRACT

A two-dimensionally indexed random coefficients autoregressive models (2D ? RCAR) and the corresponding statistical inference are important tools for the analysis of spatial lattice data. The study of such models is motivated by their second-order properties that are similar to those of 2D ? (G)ARCH which play an important role in spatial econometrics. In this article, we study the asymptotic properties of two-stage generalized moment method (2S ? GMM) under general asymptotic framework for 2D ? RCA models. So, the efficiency, strong consistency, the asymptotic normality, and hypothesis tests of 2S ? GMM estimation are derived. A simulation experiment is presented to highlight the theoretical results.     

A Smooth Nonparametric,Multivariate, Mixed-Data Location-Scale Test

Abstract

A number of tests have been proposed for assessing the location-scale assumption that is often invoked by practitioners. Existing approaches include Kolmogorov–Smirnov and Cramer–von Mises statistics that each involve measures of divergence between unknown joint distribution functions and products of marginal distributions. In practice, the unknown distribution functions embedded in these statistics are typically approximated using nonsmooth empirical distribution functions (EDFs). In a recent article, Li, Li, and Racine establish the benefits of smoothing the EDF for inference, though their theoretical results are limited to the case where the covariates are observed and the distributions unobserved, while in the current setting some covariates and their distributions are unobserved (i.e., the test relies on population error terms from a location-scale model) which necessarily involves a separate theoretical approach. We demonstrate how replacing the nonsmooth distributions of unobservables with their kernel-smoothed sample counterparts can lead to substantial power improvements, and extend existing approaches to the smooth multivariate and mixed continuous and discrete data setting in the presence of unobservables. Theoretical underpinnings are provided, Monte Carlo simulations are undertaken to assess finite-sample performance, and illustrative applications are provided.     

Datenverfügbarkeit und Datenzugang am Forschungsdatenzentrum der Bundesagentur für Arbeit im Institut für Arbeitsmarkt- und Berufsforschung

Zusammenfassung: Die Bundesagentur für Arbeit (BA) geh?rt zu den wichtigsten Produzenten statistischer Daten über den Arbeitsmarkt und die wirtschaftliche Entwicklung in Deutschland. Bislang bestand kein institutionalisierter Datenzugangsweg für Forschende au?erhalb des Instituts für Arbeitsmarkt- und Berufsforschung (IAB). Das Forschungsdatenzentrum (FDZ) der BA im IAB wurde mit dem Ziel eingerichtet, den Zugang zu den Daten der BA und des IAB für externe Forscher zu erschlie?en und systematisch auszubauen. In dem Beitrag beschreiben wir die im FDZ für die Fach?ffentlichkeit zug?nglich gemachten Daten der BA und des IAB sowie die verschiedenen Zugangsm?glichkeiten der wissenschaftlichen Forschung zu diesen Daten.

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Summary: The Federal Agency of Labour (BA) is one of the most important producers of offcial data on the labour market and the economic development in Germany. Until recently, there has been no institutionalized way of data access for researchers outside the Institute of Employment Research (IAB). The research data centre (FDZ) of the BA in the IAB has been established in order to develop and systematically extend the data access for scientists. In this paper we describe the data of the BA and the IAB which will be made accessible via the FDZ as well as the different modes of access to those data.

     

Characterizing Relationships Between Estimations Under a General Linear Model with Explicit and Implicit Restrictions by Rank of Matrix

In the investigation of the restricted linear model ? _r  = {y, X β | A β = b, σ² Σ}, the parameter constraints A β = b are often handled by transforming the model into certain implicitly restricted model. Any estimation derived from the explicitly and implicitly restricted models on the vector β and its functions should be equivalent, although the expressions of the estimation under the two models may be different. However, people more likely want to directly compare different expressions of estimations and yield a conclusion on their equivalence by using some algebraic operations on expressions of estimations. In this article, we give some results on equivalence of the well-known OLSEs and BLUEs under the explicitly and implicitly restricted linear models by using some expansion formulas for ranks of matrices.     

Comparing the BLUEs Under Two Linear Models

In this article, we consider two linear models, ?₁ = {y, X β, V ₁} and ?₂ = {y, X β, V ₂}, which differ only in their covariance matrices. Our main focus lies on the difference of the best linear unbiased estimators, BLUEs, of X β under these models. The corresponding problems between the models {y, X β, I _n } and {y, X β, V}, i.e., between the OLSE (ordinary least squares estimator) and BLUE, are pretty well studied. Our purpose is to review the corresponding considerations between the BLUEs of X β under ?₁ and ?₂. This article is an expository one presenting also new results.     

Produktdiversifizierung und Unternehmenserfolg: Nutzung der Forschungsdatenzentren der Statistischen ?mter

Zusammenfassung: Im Rahmen seiner industrie?konomischen Forschung beabsichtigt das DIW Berlin das Verhalten von Unternehmen auf den Produktm?rkten intensiver zu analysieren. In einem ersten Schritt soll der Zusammenhang zwischen Produktdiversifizierung, der Einführung neuer Produkte und dem Erfolg von Unternehmen im verarbeitenden Gewerbe untersucht werden. Dies soll mit Hilfe einer ?konometrischen Panelanalyse auf der Grundlage von Mikrodaten von Unternehmen erfolgen. Statt des in der Arbeitsmarktforschung üblichen Employer-Employee Datensatzes wird für diesen Zweck ein Producer-Product Datensatz ben?tigt. Erstmals sollen diese Mikrodaten im Rahmen einer Panelanalyse durch die Forschung ausgewertet werden. Dabei werden zwei getrennt durchgeführte Erhebungen, die Kostenstrukturerhebung und die Produktionserhebung, für einzelne Unternehmen zusammengefasst. M?glich wird dieses Forschungsvorhaben durch die Nutzung des auf Empfehlung der Kommission zur Verbesserung der informationellen Infrastruktur neu eingerichteten Forschungsdatenzentrums (FDZ). Das vorliegende Papier berichtet über das Forschungskonzept und die bisher erfolgten Schritte bei der Nutzung der Forschungsdatenzentren des Bundes und der L?nder am regionalen Standort Berlin.

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Summary: For a better understanding of the strategies of firms on their product markets, the DIW Berlin intends to intensify the analysis on the relationship between product diversification, including the introduction of new products and the success of firms. It is planned to do this by applying econometric panel methods on micro level data for German manufacturing enterprises. For this objective, it is necessary to create a producer-product database. This affords the merging of two different datasets of the system of surveys in manufacturing for Germany. The cost structure survey supplies information on the operating surplus of individual firms, while the production survey supplies the information on the goods produced by these firms. Conducting such an ambitious project has now been made possible in using the newly installed Research Data Centres (FDZ) for Germany. This paper gives an overview on the research project and on first experiences with the use of the local Research Data Centre in Berlin.

     

Publications and Information of the United States Government in an Electronic Age

Abstract

The OMB is making policy decisions regarding information that have far-reaching implications. Its directives instruct agencies to confine their dissemination activities to that information necessary for the transaction of the public business as stipulated in existing statutory law. These directives support a shift in the agencies' emphasis from publishing printed materials to making information available in electronic format. They also give the OMB license to proceed as it so desires.     

Model fusion and multiple testing in the likelihood paradigm: shrinkage and evidence supporting a point null hypothesis

ABSTRACT

According to the general law of likelihood, the strength of statistical evidence for a hypothesis as opposed to its alternative is the ratio of their likelihoods, each maximized over the parameter of interest. Consider the problem of assessing the weight of evidence for each of several hypotheses. Under a realistic model with a free parameter for each alternative hypothesis, this leads to weighing evidence without any shrinkage toward a presumption of the truth of each null hypothesis. That lack of shrinkage can lead to many false positives in settings with large numbers of hypotheses. A related problem is that point hypotheses cannot have more support than their alternatives. Both problems may be solved by fusing the realistic model with a model of a more restricted parameter space for use with the general law of likelihood. Applying the proposed framework of model fusion to data sets from genomics and education yields intuitively reasonable weights of evidence.     

XML

Abstract

XML offers some significant enhancements and functionality over what can be achieved with HTML. Among them:

o ? XML is a language for defining markup languages. It is not restricted in scope to the fixed tags defined in HTML. Document types can be created that are customized to the application, type of data, and user community for which it is intended.

? Information content can be richer and easier to use, both because of the richer flexibility of tags and the hypertext linking abilities of XML are greater than those offered in HTML.

? Information should be more usable and accessible. Because of the nature of XML, communities will be able to create applications customized to their needs, rather than being restricted to software provided by major vendors as has become the case with HTML.

? XML files are valid SGML. They can be used in SGML environments outside of the Web. At the same time XML has removed many of the complexities inherent in SGML, providing a more simple model and thus making it easier to develop XML applications that would be the case for SGML.

     

A study of generalized skew-normal distribution

Following the paper by Genton and Loperfido [Generalized skew-elliptical distributions and their quadratic forms, Ann. Inst. Statist. Math. 57 (2005), pp. 389–401], we say that Z has a generalized skew-normal distribution, if its probability density function (p.d.f.) is given by f(z)=2φ _p (z; ξ, Ω)π (z?ξ), z∈? ^p , where φ _p (·; ξ, Ω) is the p-dimensional normal p.d.f. with location vector ξ and scale matrix Ω, ξ∈? ^p , Ω>0, and π is a skewing function from ? ^p to ?, that is 0≤π (z)≤1 and π (?z)=1?π (z), ? z∈? ^p . First the distribution of linear transformations of Z are studied, and some moments of Z and its quadratic forms are derived. Next we obtain the joint moment-generating functions (m.g.f.’s) of linear and quadratic forms of Z and then investigate conditions for their independence. Finally explicit forms for the above distributions, m.g.f.’s and moments are derived when π (z)=κ (α′z), where α∈? ^p and κ is the normal, Laplace, logistic or uniform distribution function.     

Treatment Choice With Trial Data: Statistical Decision Theory Should Supplant Hypothesis Testing

Abstract

A central objective of empirical research on treatment response is to inform treatment choice. Unfortunately, researchers commonly use concepts of statistical inference whose foundations are distant from the problem of treatment choice. It has been particularly common to use hypothesis tests to compare treatments. Wald’s development of statistical decision theory provides a coherent frequentist framework for use of sample data on treatment response to make treatment decisions. A body of recent research applies statistical decision theory to characterize uniformly satisfactory treatment choices, in the sense of maximum loss relative to optimal decisions (also known as maximum regret). This article describes the basic ideas and findings, which provide an appealing practical alternative to use of hypothesis tests. For simplicity, the article focuses on medical treatment with evidence from classical randomized clinical trials. The ideas apply generally, encompassing use of observational data and treatment choice in nonmedical contexts.     

Partly linear models on Riemannian manifolds

In partly linear models, the dependence of the response y on (x ^T, t) is modeled through the relationship y=x ^T β+g(t)+?, where ? is independent of (x ^T, t). We are interested in developing an estimation procedure that allows us to combine the flexibility of the partly linear models, studied by several authors, but including some variables that belong to a non-Euclidean space. The motivating application of this paper deals with the explanation of the atmospheric SO₂ pollution incidents using these models when some of the predictive variables belong in a cylinder. In this paper, the estimators of β and g are constructed when the explanatory variables t take values on a Riemannian manifold and the asymptotic properties of the proposed estimators are obtained under suitable conditions. We illustrate the use of this estimation approach using an environmental data set and we explore the performance of the estimators through a simulation study.