Embedding latent class regression and latent class distal outcome models into cluster-weighted latent class analysis: a detailed simulation experiment

Usually in latent class (LC) analysis, external predictors are taken to be cluster conditional probability predictors (LC models with external predictors), and/or score conditional probability predictors (LC regression models). In such cases, their distribution is not of interest. Class-specific distribution is of interest in the distal outcome model, when the distribution of the external variables is assumed to depend on LC membership. In this paper, we consider a more general formulation, that embeds both the LC regression and the distal outcome models, as is typically done in cluster-weighted modelling. This allows us to investigate (1) whether the distribution of the external variables differs across classes, (2) whether there are significant direct effects of the external variables on the indicators, by modelling jointly the relationship between the external and the latent variables. We show the advantages of the proposed modelling approach through a set of artificial examples, an extensive simulation study and an empirical application about psychological contracts among employees and employers in Belgium and the Netherlands.     

On some mixture models based on the Birnbaum-Saunders distribution and associated inference

In this paper, we consider three different mixture models based on the Birnbaum-Saunders (BS) distribution, viz., (1) mixture of two different BS distributions, (2) mixture of a BS distribution and a length-biased version of another BS distribution, and (3) mixture of a BS distribution and its length-biased version. For all these models, we study their characteristics including the shape of their density and hazard rate functions. For the maximum likelihood estimation of the model parameters, we use the EM algorithm. For the purpose of illustration, we analyze two data sets related to enzyme and depressive condition problems. In the case of the enzyme data, it is shown that Model 1 provides the best fit, while for the depressive condition data, it is shown all three models fit well with Model 3 providing the best fit.     

Toward Defining the Causal Role of Consciousness: Using Models of Memory and Moral Judgment from Cognitive Neuroscience to Expand the Sociological Dual‐Process Model

What role does “discursive consciousness” play in decision‐making? How does it interact with “practical consciousness?” These two questions constitute two important gaps in strong practice theory that extend from Pierre Bourdieu's habitus to Stephen Vaisey's sociological dual‐process model and beyond. The goal of this paper is to provide an empirical framework that expands the sociological dual‐process model in order to fill these gaps using models from cognitive neuroscience. In particular, I use models of memory and moral judgment that highlight the importance of executive functions and semantic memory. I outline each model as it pertains to the aforementioned gaps in strong practice theory. I then use the models from cognitive neuroscience to create an expanded dual‐process model that addresses how and when conscious mental systems override and interact with subconscious mental systems in the use of cultural ends for decision‐making. Finally, using this expanded model I address the sociological debate over the use of interview and survey data. My analysis reveals that surveys and interviews both elicit information encoded in declarative memory and differ primarily in the process of information retrieval that is required of respondents.     

Two-tailed asymptotic inferences for a proportion

This paper evaluates 29 methods for obtaining a two-sided confidence interval for a binomial proportion (16 of which are new proposals) and comes to the conclusion that: Wilson's classic method is only optimal for a confidence of 99%, although generally it can be applied when n≥50; for a confidence of 95% or 90%, the optimal method is the one based on the arcsine transformation (when this is applied to the data incremented by 0.5), which behaves in a very similar manner to Jeffreys’ Bayesian method. A simpler option, though not so good as those just mentioned, is the classic-adjusted Wald method of Agresti and Coull.     

Performance of coefficient of variation estimators in ranked set sampling

In this paper, we propose and evaluate the performance of different parametric and nonparametric estimators for the population coefficient of variation considering Ranked Set Sampling (RSS) under normal distribution. The performance of the proposed estimators was assessed based on the bias and relative efficiency provided by a Monte Carlo simulation study. An application in anthropometric measurements data from a human population is also presented. The results showed that the proposed estimators via RSS present an expressively lower mean squared error when compared to the usual estimator, obtained via Simple Random Sampling. Also, it was verified the superiority of the maximum likelihood estimator, given the necessary assumptions of normality and perfect ranking are met.     

Are Private Interests Clouding the Peer-Review Process of the WHO Bulletin? A Case Study

Readers’ trust on the medical literature has been eroded, and journal editors and some editorial boards are taking measures to ensure that authors fully and accurately report research findings and disclose conflicts of interest. This article describes a case study in which the papers editor of the World Health Organization (WHO) Bulletin influenced the content of an article that had been approved by the external reviewers. The editor objected to the publication of the large price differentials of the new molecular entities (NMEs) across the Latin American countries where they had been tested and the limited added therapeutic value of the NMEs that had been assessed by independent drug bulletins. This article summarizes the exchanges with WHO staff and posits the hypothesis that the WHO Bulletin might be affected by the shifts in WHO financing. Several authors have raised concern about the impact of financial conflicts of interest in WHO activities in the field of nutrition, intellectual property, and in the emergency response to the flu pandemic. Moreover, it has been reported that powerful WHO contributors pressured WHO into revising its publication policy. This is the first time that authors question if these conflicts of interest are also affecting the editorial independence of the WHO Bulletin.     

Statistical concepts of a priori and a posteriori risk classification in insurance

Everyday we face all kinds of risks, and insurance is in the business of providing us a means to transfer or share these risks, usually to eliminate or reduce the resulting financial burden, in exchange for a predetermined price or tariff. Actuaries are considered professional experts in the economic assessment of uncertain events, and equipped with many statistical tools for analytics, they help formulate a fair and reasonable tariff associated with these risks. An important part of the process of establishing fair insurance tariffs is risk classification, which involves the grouping of risks into various classes that share a homogeneous set of characteristics allowing the actuary to reasonably price discriminate. This article is a survey paper on the statistical tools for risk classification used in insurance. Because of recent availability of more complex data in the industry together with the technology to analyze these data, we additionally discuss modern techniques that have recently emerged in the statistics discipline and can be used for risk classification. While several of the illustrations discussed in the paper focus on general, or non-life, insurance, several of the principles we examine can be similarly applied to life insurance. Furthermore, we also distinguish between a priori and a posteriori ratemaking. The former is a process which forms the basis for ratemaking when a policyholder is new and insufficient information may be available. The latter process uses additional historical information about policyholder claims when this becomes available. In effect, the resulting a posteriori premium allows one to correct and adjust the previous a priori premium making the price discrimination even more fair and reasonable.     

A social policy model for the reconciliation of employment and family life from a gender equality perspective

The issue of family–employment reconciliation has rapidly evolved from being ignored to a certain dejá vu perception in public debate, as a result of its media success during the last decade. This is even more the case in Spain, where it was only in the late 1990s, when a law was passed to regulate and extend parental and other leave for workers with close relatives in need of care, that reconciliation policies began to be generally discussed and considered. In a context of quick population aging as a consequence of low fertility, concern on labor force supply in the middle term is high on the agenda. Women are increasingly considered to be necessary both as workers and mothers (of future workers), thus raising awareness of the importance of social policies to make their double presence in both worlds possible. There is now general agreement from the right to the left on the urgency to develop family–employment policies. But what is not generally addressed is the impact of such policies on gender equality, a dimension which tends to be either ignored or taken for granted. Not all reconciliation measures have the same effects on the women and men relationship. Some of them push forward equality, whereas others go backwards. Efficiency in making job and family responsibilities compatible does not always go hand in hand with increasing equality. The paper presents a theoretical model for the reconciliation of work and family life from a gender equality perspective. The three main kinds of instruments available in social policy – services, leave, and cash – are examined in four different cases: care of under-threes, care of sick children, coordination of work and school schedules, and care of children during school holidays. Each case is looked at considering its effects on social and gender equality, as well as child welfare. The model includes as active agents of the system the State (promotes and regulates), families and individuals (those directly implicated), and the market as labor market, on the one hand, and supplier of private services, on the other.