The Rising Tide Is Not Lifting All Ships Equally

Population and Environment -     

Teaching Bayesian Statistics Using Sampling Methods and MINITAB

Bayesian statistics can be hard to teach at an elementary level due to the difficulty in deriving the posterior distribution for interesting nonconjugate problems. One attractive method of summarizing the posterior distribution is to directly simulate from the probability distribution of interest and then explore the simulated sample. We illustrate the use of Rubin's Sampling-Importance-Resampling (SIR) algorithm to simulate posterior distributions for three inference problems. In each example, we focus on the construction of the prior distribution and then use exploratory data analysis techniques to describe the posterior samples and make inferences. The use of MINITAB macros is presented to illustrate the ease of performing this simulation on standard statistical computer programs.     

Training Police Social Workers: A Neglected Area of Social Work Education

This article begins with a discussion of the vital need for collaboration between social work and law enforcement professionals, with particular emphasis on the need for comprehensive training programs combining criminal justice and social work knowledge. It then documents several historical recommendations for training police social workers that are relevant today, and suggests that social work education programs of the future include provisions for transmitting social work knowledge to police officers. Similarly, social workers planning to practice in criminal justice settings need to have training in the administration of justice.     

Inferring an Augmented Bayesian Network to Confront a Complex Quantitative Microbial Risk Assessment Model with Durability Studies: Application to Bacillus Cereus on a Courgette Purée Production Chain

The Monte Carlo (MC) simulation approach is traditionally used in food safety risk assessment to study quantitative microbial risk assessment (QMRA) models. When experimental data are available, performing Bayesian inference is a good alternative approach that allows backward calculation in a stochastic QMRA model to update the experts’ knowledge about the microbial dynamics of a given food‐borne pathogen. In this article, we propose a complex example where Bayesian inference is applied to a high‐dimensional second‐order QMRA model. The case study is a farm‐to‐fork QMRA model considering genetic diversity of Bacillus cereus in a cooked, pasteurized, and chilled courgette purée. Experimental data are Bacillus cereus concentrations measured in packages of courgette purées stored at different time‐temperature profiles after pasteurization. To perform a Bayesian inference, we first built an augmented Bayesian network by linking a second‐order QMRA model to the available contamination data. We then ran a Markov chain Monte Carlo (MCMC) algorithm to update all the unknown concentrations and unknown quantities of the augmented model. About 25% of the prior beliefs are strongly updated, leading to a reduction in uncertainty. Some updates interestingly question the QMRA model.     

Figuration und Emergenz

The paper reconstructs the methodology of Norbert Elias against the background of his ontology. Thereby Robert van Kriekens thesis will be defended that Elias is a proponent of a “third sociology”. His ontology shows that figurations are integrated wholes. Human beings form the parts of this wholes and necessarily build up social relations based upon their “relational properties”. This model of social wholes builds the finishing part of a mereological ontology of layers of the natural and social world. Physical-chemical wholes can reductively explained, biological and sociological wholes are ontologically and epistemologically irreducible because of phenomena of emergence. This ontology of Elias serves as a background for his methodology which does not favour individualist but moderat holist or relationalist explanations. With a new definition of social emergence it can be shown that relations are central factors of sociological explanations which can be found in Elias’ historical-sociological studies.?Keywords:Norbert Elias ? Ontology ? Methodology ? Third sociology ? Part-whole ? Methodological individualism ? Methodological relationalism ? Relational sociology ? Emergence ? Figuration ? Micro-macro     

Testing the proportional odds assumption in multiply imputed ordinal longitudinal data

A popular choice when analyzing ordinal data is to consider the cumulative proportional odds model to relate the marginal probabilities of the ordinal outcome to a set of covariates. However, application of this model relies on the condition of identical cumulative odds ratios across the cut-offs of the ordinal outcome; the well-known proportional odds assumption. This paper focuses on the assessment of this assumption while accounting for repeated and missing data. In this respect, we develop a statistical method built on multiple imputation (MI) based on generalized estimating equations that allows to test the proportionality assumption under the missing at random setting. The performance of the proposed method is evaluated for two MI algorithms for incomplete longitudinal ordinal data. The impact of both MI methods is compared with respect to the type I error rate and the power for situations covering various numbers of categories of the ordinal outcome, sample sizes, rates of missingness, well-balanced and skewed data. The comparison of both MI methods with the complete-case analysis is also provided. We illustrate the use of the proposed methods on a quality of life data from a cancer clinical trial.     

A Simulation Study Comparing Multiple Imputation Methods for Incomplete Longitudinal Ordinal Data

Multiple imputation (MI) is now a reference solution for handling missing data. The default method for MI is the Multivariate Normal Imputation (MNI) algorithm that is based on the multivariate normal distribution. In the presence of longitudinal ordinal missing data, where the Gaussian assumption is no longer valid, application of the MNI method is questionable. This simulation study compares the performance of the MNI and ordinal imputation regression model for incomplete longitudinal ordinal data for situations covering various numbers of categories of the ordinal outcome, time occasions, sample sizes, rates of missingness, well-balanced, and skewed data.     

Moderater methodologischer Holismus

Zusammenfassung Der Aufsatz nimmt eine undeutlich gebliebene anti-reduktionistische Tendenz der Weberschen Soziologie auf, Handlungs- und Ordnungsebene gleichberechtigt nebeneinander zu stellen. Vor diesem Hintergrund wird vorgeschlagen, die methodologische Position eines moderaten Holismus als ad?quaten Standpunkt für das Weber-Paradigma anzunehmen. Er verbindet eine Ontologie begrenzt holistischen Charakters mit dem individualistischen Makro-Mikro-Makro-Modell der Erkl?rung, das sich aber im Detail von dem Modell in der Version Hartmut Essers unterscheidet. Der moderate methodologische Holismus wird von drei anderen methodologischen Positionen auf der Grundlage neuerer emergenztheoretischer überlegungen unterschieden und am Beispiel der Protestantischen Ethik und der Weberschen Herrschaftssoziologie als Hintergrund eines ad?quaten Erkl?rungsmodells vorgestellt. Weiterhin wird demonstriert, dass jede Handlungstheorie im Sinne Webers mit dem Prinzip „Gründe als Ursachen“ eine holistische Grundorientierung besitzt, die konsequenter Weise auf der Ordnungsebene nicht auβer Kraft gesetzt werden sollte. Diese Version des Weber-Paradigmas hat eine ontologisch begründete N?he zu einer historisch und empirisch ausgerichteten Soziologie.      

Modified goodness-of-fit test for the laplace distribution

In this paper critical values of the Anderson-Darling and Cra[macute]er-von Mises are given for the Laplace distribution for maximum likelihood estimation of the location and scale parameters. The power of these tests is investigated for a number of alternative distributions. The Anderson-Darling test yields higher power generally than the Cra[macute]er-von Mises test.