The Access/Impact Problem and the Green and Gold Roads to Open Access: An Update

The research access/impact problem arises because journal articles are not accessible to all of their would-be users; hence, they are losing potential research impact. The solution is to make all articles open access (OA, i.e., accessible online, free for all). OA articles have significantly higher citation impact than non-OA articles. There are two roads to OA: the “golden” road (publish your article in an OA journal) and the “green” road (publish your article in a non-OA journal but also self-archive it in an OA archive). About 10% of journals are gold, but over 90% are already green (i.e., they have given their authors the green light to self-archive); yet only about 10–20% of articles have been self-archived. To reach 100% OA, self-archiving needs to be mandated by researchers’ employers and funders, as they are now increasingly beginning to do.     

Identification of Salmonella high risk pig-herds in Belgium by using semiparametric quantile regression

Summary.  Consumption of pork that is contaminated with Salmonella is an important source of human salmonellosis world wide. To control and prevent salmonellosis, Belgian pig-herds with high Salmonella infection burden are encouraged to take part in a control programme supporting the implementation of control measures. The Belgian government decided that only the 10% of pig-herds with the highest Salmonella infection burden (denoted high risk herds) can participate. To identify these herds, serological data reported as sample-to-positive ratios (SP-ratios) are collected. However, SP-ratios have an extremely skewed distribution and are heavily subject to confounding seasonal and animal age effects. Therefore, we propose to identify the 10% high risk herds by using semiparametric quantile regression with P -splines. In particular, quantile curves of animal SP-ratios are estimated as a function of sampling time and animal age. Then, pigs are classified into low and high risk animals with high risk animals having an SP-ratio that is larger than the corresponding estimated upper quantile. Finally, for each herd, the number of high risk animals is calculated as well as the beta–binomial p -value reflecting the hypothesis that the Salmonella infection burden is higher in that herd compared with the other herds. The 10% pig-herds with the lowest p -values are then identified as high risk herds. In addition, since high risk herds are supported to implement control measures, a risk factor analysis is conducted by using binomial generalized linear mixed models to investigate factors that are associated with decreased or increased Salmonella infection burden. Finally, since the choice of a specific upper quantile is to a certain extent arbitrary, a sensitivity analysis is conducted comparing different choices of upper quantiles.     

Coalition Formation and Cost Allocation for Joint Replenishment Systems

This paper focuses on the issues of coalition formation and cost allocation in a joint replenishment system involving a set of independent and freely interacting retailers purchasing an item from one supplier to meet a deterministic demand. The papers dealing with this problem are mainly focused on supperadditive games, where the cost savings associated with a coalition increase with the number of players in the coalition. The most relevant question addressed then is how to allocate the savings to the players. In this paper, we propose to go further by dealing with a non‐supperadditive game, where a set of independent retailers have the common understanding to share the cost savings according to the cost‐based proportional rule. In this setting, the global cost optimization is no longer a relevant approach to identify appealing coalitions for any retailer. Here, we provide an iterative procedure to form the so‐called efficient coalition structure and we show that this coalition structure has the nice properties of being (i) weakly stable in the sense of the coalition structure core and (ii) strongly stable under a given assumption. An exact fractional programming based solution is also given to generate such efficient coalitions.     

L'effet de l'erreur d'arrondi sur l'estimateur d'une densité par la méthode du noyau

In a model for rounded data suppose that the random sample X₁,.,.,X_n,. i.i.d., is transformed into an observed random sample X_1Δ,.,.,X_nΔ, where X_iΔ = 2vΔ if X_i, ∈ (2vΔ - Δ, 2vΔ + Δ), for i = 1,.,.,n. We show that the precision Δ of the observations has an important effect on the shape of the kernel density estimator, and we identify important points for the graphical display of this estimator. We examine the IMSE criteria to find the optimal window under the rounded-data model.     

Modeling Human Interindividual Variability in Metabolism and Risk: The Example of 4-Aminobiphenyl

We investigate, through modeling, the impact of interindividual heterogeneity in the metabolism of 4-aminobiphenyl (ABP) and in physiological factors on human cancer risk: A physiological pharmacokinetic model was used to quantify the time course of the formation of the proximate carcinogen, N-hydroxy-4-ABP and the DNA-binding of the active species in the bladder. The metabolic and physiologic model parameters were randomly varied, via Monte Carlo simulations, to reproduce interindividual variability. The sampling means for most parameters were scaled from values developed by Kadlubar et al. (Cancer Res., 51 : 4371, 1991) for dogs; variances were obtained primarily from published human data (e.g., measurements of ABP N-oxidation, and arylamine N-acetylation in human liver tissue). In 500 simulations, theoretically representing 500 humans, DNA-adduct levels in the bladder of the most susceptible individuals are ten thousand times higher than for the least susceptible, and the 5th and 95th percentiles differ by a factor of 160. DNA binding for the most susceptible individual (with low urine pH, low N-acetylation and high N-oxidation activities) is theoretically one million-fold higher than for the least susceptible (with high urine pH, high N-acetylation and low N-oxidation activities). The simulations also suggest that the four factors contributing most significantly to interindividual differences in DNA-binding of ABP in human bladder are urine pH, ABP N-oxidation, ABP N-acetylation and urination frequency.     

Resolving Coparenting Dissatisfaction In Couples: A Preliminary Task Analysis Study

This study explored the change that unfolded when parents resolved their coparenting dissatisfaction during an Integrative Brief Systemic Intervention (IBSI) for parent couples. We conducted a task analysis (Greenberg, 2007) to build a model of resolving coparenting dissatisfaction. We compared a postulated model of change (rational model) based on theoretical and clinical assumptions to the observations of the actual change process that couples experienced in an IBSI (empirical analysis). The empirical analysis was conducted on six IBSI therapy cases (three exhibiting positive development and three exhibiting no development). We defined positive development in IBSI as moving from coparenting dissatisfaction to coparenting satisfaction. The final rational–empirical model included six steps that facilitated the resolution of coparenting dissatisfaction. This study contributes to deepening the knowledge of how coparenting may change during marital therapy.     

Statistical inference for the quintile share ratio

In recent years, the Quintile Share Ratio (or QSR) has become a very popular measure of inequality. In 2001, the European Council decided that income inequality in European Union member states should be described using two indicators: the Gini Index and the QSR. The QSR is generally defined as the ratio of the total income earned by the richest 20% of the population relative to that earned by the poorest 20%. Thus, it can be expressed using quantile shares, where a quantile share is the share of total income earned by all of the units up to a given quantile. The aim of this paper is to propose an improved methodology for the estimation and variance estimation of the QSR in a complex sampling design framework. Because the QSR is a non-linear function of interest, the estimation of its sampling variance requires advanced methodology. Moreover, a non-trivial obstacle in the estimation of quantile shares in finite populations is the non-unique definition of a quantile. Thus, two different conceptions of the quantile share are presented in the paper, leading us to two different estimators of the QSR. Regarding variance estimation, [Osier, 2006] and [Osier, 2009] proposed a variance estimator based on linearization techniques. However, his method involves Gaussian kernel smoothing of cumulative distribution functions. Our approach, also based on linearization, shows that no smoothing is needed. The construction of confidence intervals is discussed and a proposition is made to account for the skewness of the sampling distribution of the QSR. Finally, simulation studies are run to assess the relevance of our theoretical results.     

The Access/Impact Problem and the Green and Gold Roads to Open Access

Abstract

The research access/impact problem arises because journal articles are not accessible to all of their would-be users; hence, they are losing potential research impact. The solution is to make all articles Open Access (OA; i.e., accessible online, free for all). OA articles have significantly higher citation impact than non-OA articles. There are two roads to OA: the “golden” road (publish your article in an OA journal) and the “green” road (publish your article in a non-OA journal but also self-archive it in an OA archive). Only 5% of journals are gold, but over 90% are already green (i.e., they have given their authors the green light to self-archive); yet only about 10–20% of articles have been self-archived. To reach 100% OA, self-archiving needs to be mandated by researchers' employers and funders, as the United Kingdom and the United States have recently recommended, and universities need to implement that mandate.     

Asymptotic power efficiency for a location and scale problem

The asymptotic power efficiency of the class of linear rank tests relative to the asymptotically most powerful rank test is derived for a two sample location and scale problem and numerical evaluations are presented for two special tests.     

ERRATA CORRIGE: “ARE MUSLIM IMMIGRANTS DIFFERENT IN TERMS OF CULTURAL INTEGRATION?”

We are thankful to Michael Lundholm and Mahmood Arai for pointing us towards a coding error which invalidates the regressions in our paper. Correcting the code leads to a decrease in sample sizes, though much smaller than Arai et al. (2011) claim based on their “replication”. An appropriate redefinition of the variables and of the model specification allows us to reproduce the substance of the empirical analysis in our original published paper. Although the results are now less clear‐cut, our analysis remains essentially unchanged.