Statistical modelling of citation exchange among statistics journals

Scholarly journal rankings based on citation data are often met with skepticism by the scientific community. Part of the skepticism is due to the discrepancy between the common perception of journals' prestige and their ranking based on citation counts. A more serious concern is the inappropriate use of journal rankings to evaluate the scientific influence of authors. This paper focuses on analysis of the table of cross-citations among a selection of Statistics journals. Data are collected from the Web of Science database published by Thomson Reuters. Our results suggest that modelling the exchange of citations between journals is useful to highlight the most prestigious journals, but also that journal citation data are characterized by considerable heterogeneity, which needs to be properly summarized. Inferential conclusions require care in order to avoid potential over-interpretation of insignificant differences between journal ratings

Hybrid pairwise likelihood analysis of animal behavior experiments

The study of the determinants of contests between animals is an important issue in understanding animal behavior. Tournament experiments among a set of animals are used by zoologists for this purpose. From a statistical point of view, the results of these tournament experiments are naturally analyzed by paired comparison models such as the Bradley-Terry and the Thurstone models. A major complication is the presence of dependence between the outcomes of couples of contests with an animal in common. Likelihood analysis of this type of animal behavior experiments in presence of interdependence between contests is computationally demanding. An alternative fitting method that mixes optimal estimation equations and pairwise likelihood inference is then suggested. The performance of the proposed methodology is investigated by simulation studies and then applied to a real data set about adult male Cape Dwarf Chameleons

Whole-body low-dose CT recognizes two distinct patterns of lytic lesions in multiple myeloma patients with different disease metabolism at PET/MRI

We evaluated differences in density and 18F-FDG PET/MRI features of lytic bone lesions (LBLs) identified by whole-body low-dose CT (WB-LDCT) in patients affected by newly diagnosed multiple myeloma (MM). In 18 MM patients, 135 unequivocal LBLs identified by WB-LDCT were characterized for inner density (negative or positive Hounsfield unit (HU)), where negative density (HU\u2009<\u20090) characterizes normal yellow marrow whereas positive HU correlates with tissue-like infiltrative pattern. The same LBLs were analyzed by 18F-FDG PET/DWI-MRI, registering DWI signal with ADC and SUV max values. According to HU, 35 lesions had a negative density (-\u200956.94\u2009\ub1\u200931.87 HU) while 100 lesions presented positive density (44.87\u2009\ub1\u200923.89 HU). In seven patients, only positive HU LBLs were demonstrated whereas in eight patients, both positive and negative HU LBLs were detected. Intriguingly, in three patients (16%), only negative HU LBLs were shown. At 18F-FDG PET/DWI-MRI analysis, negative HU LBLs presented low ADC values (360.69\u2009\ub1\u2009154.38\u2009 7\u200910-6 mm2/s) and low SUV max values (1.69\u2009\ub1\u20090.56), consistent with fatty marrow, whereas positive HU LBLs showed an infiltrative pattern, characterized by higher ADC (mean 868.46\u2009\ub1\u2009207.67\u2009 7\u200910-6 mm2/s) and SUV max (mean 5.04\u2009\ub1\u20091.94) values. Surprisingly, histology of negative HU LBLs documented infiltration by neoplastic plasma cells scattered among adipocytes. In conclusion, two different patterns of LBLs were detected by WB-LDCT in MM patients. Both types of lesions were indicative for active disease, although only positive HU LBL were captured by 18F-FDG PET/DWI-MRI imaging, indicating that WB-LDCT adds specific information

Halogen-based reconstruction of Russian Arctic sea ice area from the Akademii Nauk ice core (Severnaya Zemlya)

The role of sea ice in the Earth climate system is still under debate, although it is known to influence albedo, ocean circulation, and atmosphere-ocean heat and gas exchange. Here we present a reconstruction of 1950 to 1998AD sea ice in the Laptev Sea based on the Akademii Nauk ice core (Severnaya Zemlya, Russian Arctic). The chemistry of halogens bromine (Br) and iodine (I) is strongly active and influenced by sea ice dynamics, in terms of physical, chemical and biological process. Bromine reacts on the sea ice surface in autocatalyzing "bromine explosion" events, causing an enrichment of the Br/Na ratio and hence a bromine excess (Br-exc) in snow compared to that in seawater. Iodine is suggested to be emitted from algal communities growing under sea ice. The results suggest a connection between Br-exc and spring sea ice area, as well as a connection between iodine concentration and summer sea ice area. The correlation coefficients obtained between Br-exc and spring sea ice (r = 0.44) as well as between iodine and summer sea ice (r = 0.50) for the Laptev Sea suggest that these two halogens could become good candidates for extended reconstructions of past sea ice changes in the Arctic

Omecamtiv mecarbil in chronic heart failure with reduced ejection fraction, GALACTIC‐HF: baseline characteristics and comparison with contemporary clinical trials

Aims: The safety and efficacy of the novel selective cardiac myosin activator, omecamtiv mecarbil, in patients with heart failure with reduced ejection fraction (HFrEF) is tested in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC‐HF) trial. Here we describe the baseline characteristics of participants in GALACTIC‐HF and how these compare with other contemporary trials. Methods and Results: Adults with established HFrEF, New York Heart Association functional class (NYHA) ≥ II, EF ≤35%, elevated natriuretic peptides and either current hospitalization for HF or history of hospitalization/ emergency department visit for HF within a year were randomized to either placebo or omecamtiv mecarbil (pharmacokinetic‐guided dosing: 25, 37.5 or 50 mg bid). 8256 patients [male (79%), non‐white (22%), mean age 65 years] were enrolled with a mean EF 27%, ischemic etiology in 54%, NYHA II 53% and III/IV 47%, and median NT‐proBNP 1971 pg/mL. HF therapies at baseline were among the most effectively employed in contemporary HF trials. GALACTIC‐HF randomized patients representative of recent HF registries and trials with substantial numbers of patients also having characteristics understudied in previous trials including more from North America (n = 1386), enrolled as inpatients (n = 2084), systolic blood pressure &lt; 100 mmHg (n = 1127), estimated glomerular filtration rate &lt; 30 mL/min/1.73 m2 (n = 528), and treated with sacubitril‐valsartan at baseline (n = 1594). Conclusions: GALACTIC‐HF enrolled a well‐treated, high‐risk population from both inpatient and outpatient settings, which will provide a definitive evaluation of the efficacy and safety of this novel therapy, as well as informing its potential future implementation

Stochastic dynamic Thurstone-Mosteller models for sports tournaments

In the course of national sports tournaments, usually lasting several months, it is expected that the abilities of teams taking part in the tournament change in time. A dynamic extension of the Thurstone-Mosteller model for paired comparison data is introduced to model the outcomes of sporting contests allowing for time-varying abilities. It is assumed that the development of teams' abilities follows a stationary process and a team-specific home effect is considered. The likelihood function of the proposed model requires the approximation of a high dimensional integral. This difficulty is overcome by means of maximum simulated likelihood via the Geweke-Hajivassiliou-Keane algorithm. Ranking of teams and forecasting future match results are performed through a Metropolis-Hastings algorithm. The methodology is applied to sports data with and without tied contests, namely the 2006-2007 Italian volleyball league and the 2008-2009 Italian Serie A football season

Hybrid pairwise likelihood analysis of animal behavior experiments

The study of the determinants of contests between animals is an important issue in understanding animal behavior. Tournament experiments among a set of animals are used by zoologists for this purpose. From a statistical point of view, the results of these tournament experiments are naturally analyzed by paired comparison models such as the Bradley-Terry and the Thurstone models. A major complication is the presence of dependence between the outcomes of couples of contests with an animal in common. Likelihood analysis of this type of animal behavior experiments in presence of interdependence between contests is computationally demanding. An alternative fitting method that mixes optimal estimation equations and pairwise likelihood inference is then suggested. The performance of the proposed methodology is investigated by simulation studies and then applied to a real data set about adult male Cape Dwarf Chameleons

A note on composite likelihood inference and model selection

A composite likelihood consists in a combination of valid likelihood objects, usually related to small subsets of data. The merit of composite likelihood is to reduce the computational complexity so that it is possible to deal with large datasets and very complex models, even when the use of standard likelihood or Bayesian methods is not feasible. In this paper, we aim to suggest an integrated, general approach to inference and model selection using composite likelihood methods. In particular, we introduce an information criterion for model selection based on composite likelihood. Applications to modelling time series of counts through dynamic generalized linear models and to the analysis of the well-known Old Faithful geyser dataset are also given

A Model for Correlated Paired Comparison Data.

Paired comparison data arise when objects are compared in couples. This type of data occurs in many applications. Traditional models developed for the analysis of paired comparison data assume independence among all observations, but this seems unrealistic because comparisons with a common object are naturally correlated. A model that introduces correlation between comparisons with at least a common object is discussed. The likelihood function of the proposed model involves the approximation of a high dimensional integral. To overcome numerical difficulties a pairwise likelihood approach is adopted. The methodology is illustrated through the analysis of the 2006/2007 Italian men’s volleyball tournament and the 2008/2009 season of the Italian water polo league