Standard Statistical Model Research Articles

Nutrition transition in Vietnam: changing food supply, food prices, household expenditure, diet and nutrition outcomes

While literature has noted the presence of a nutrition transition in terms of changing nutrition outcomes in Vietnam, very limited evidence linking changes in upstream food system factors to downstream diet and nutrition changes exists. Combining available data from different sources and analyzing it through a conceptual food systems framework, our study examines different pathways of nutrition transition through food supply, food prices, household food expenditures, diets, and nutrition outcomes in Vietnam. Our findings show that while Vietnam is at the start of its nutrition transition, change is happening rapidly. Undernutrition is falling, obesity is rising, and nutrition-related chronic diseases account for a significant burden of diseases and death. In terms of changes in healthful foods, the supply of vegetables and fruits is plentiful, and expenditure on vegetables remains consistent and small. Notably however, vegetable consumption has dropped, and increasing meat and milk consumption have been double-edged swords for nutrition. In terms of foods associated with the negative sides of the nutrition transition, the availability of sweets and sweetened beverages has risen in recent years, with oils and fats rising less. The expenditure share on food eaten away from home, in many contexts a marker for less healthful diets, has increased over time. While these changes are typical of a nutrition transition, Vietnam is also somewhat of an outlier in some respects: wet markets and daily fresh food purchases continue to dominate food purchasing behaviour, and food eaten away from home means a different thing in a country renowned for its diverse and healthy street food and roadside restaurant culture. While this study brings together important data on the food system drivers of a nutrition transition in Vietnam, it cannot link each of these issues into a standard statistical model of change due to data gaps at different levels, calling for data collection improvement in future diet and food systems research. Vietnamese health policy explicitly acknowledges nutrition transition issues, with targets for obesity reduction. This work on the food system drivers of the nutrition transition points to the need to further adapt policy in other sectors beyond health, however. At the same time as making nutrient-rich foods more accessible, nutrient-poor or ultra-processed foods need to be made less accessible and desirable if additional income is to contribute to a healthy diet in limiting Vietnam’s emerging nutrition transition.

Regression Models for Compositional Data: General Log-Contrast Formulations, Proximal Optimization, and Microbiome Data Applications

Compositional data sets are ubiquitous in science, including geology, ecology, and microbiology. In microbiome research, compositional data primarily arise from high-throughput sequence-based profiling experiments. These data comprise microbial compositions in their natural habitat and are often paired with covariate measurements that characterize physicochemical habitat properties or the physiology of the host. Inferring parsimonious statistical associations between microbial compositions and habitat- or host-specific covariate data is an important step in exploratory data analysis. A standard statistical model linking compositional covariates to continuous outcomes is the linear log-contrast model. This model describes the response as a linear combination of log-ratios of the original compositions and has been extended to the high-dimensional setting via regularization. In this contribution, we propose a general convex optimization model for linear log-contrast regression which includes many previous proposals as special cases. We introduce a proximal algorithm that solves the resulting constrained optimization problem exactly with rigorous convergence guarantees. We illustrate the versatility of our approach by investigating the performance of several model instances on soil and gut microbiome data analysis tasks.

Study of angular momentum effect on the fission process by angular anisotropy method in heavy-ion-induced reactions

The study of compound nucleus characteristics through fission fragment properties is a powerful tool to understand the fission mechanism of excited nuclei formed in heavy-ion-induced reactions. In this work, angular anisotropies of fission fragments from fissioning nuclei [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] with normal behaviors in angular anisotropy have been analyzed. In this way, the quadrupole deformation parameter of the compound nucleus is calculated by comparison between the experimental data of angular anisotropy and those predicted by the standard saddle-point statistical model. Then the rotational energy, the fission barrier height, and the effective moment of inertia of the compound nucleus are obtained through the calculated quadrupole deformation parameters. It is observed that the quadrupole deformation parameter decreases with increasing the mean square angular momentum. The obtained results illustrate that the rotational energy and the effective moment of inertia increase almost linearly with increasing the mean square angular momentum, while the fission barrier height decreases as expected. However, the calculated values of fission barrier height overestimate the rotating finite-range model predictions. Also, the calculated values of effective moment of inertia represent a nearly linear trend despite those predicted by the rotating finite-range model. In order to discuss the physical ideas underlying the effect of angular momentum on the fission properties, the interaction potential energy during the capture process is studied for the lightest and heaviest reaction systems.

Exploring spatial non-stationarity in the relationships between landslide susceptibility and conditioning factors: a local modeling approach using geographically weighted regression

Landslide susceptibility is the likelihood of landslide occurrence, in a specific place and time. The identification of the potential relationships between landslide susceptibility and conditioning factors is very important towards landslide hazard mitigation. In this paper, we implement a local statistical analysis model geographically weighted regression, in two catchment areas located in northern Peloponnese, Greece. For this purpose, we examined the following eight conditioning factors: elevation, slope, aspect, lithology, land cover, proximity to the drainage network, proximity to the road network, and proximity to faults. Moreover, the relationship between these factors and landsliding in the study area is examined. The local statistical analysis model was also evaluated by finding its differences with the performance of a standard global statistical model logistic regression. The results indicated that the global statistical model can be enhanced by the application of a local model. The outputs of the proposed approach favored a better understanding of the factors influencing landslide occurrence and may be beneficial to local authorities and decision-makers dealing with the mitigation of landslide hazard.

Estimation of an inter-rater intra-class correlation coefficient that overcomes common assumption violations in the assessment of health measurement scales

BackgroundIntraclass correlation coefficients (ICC) are recommended for the assessment of the reliability of measurement scales. However, the ICC is subject to a variety of statistical assumptions such as normality and stable variance, which are rarely considered in health applications.MethodsA Bayesian approach using hierarchical regression and variance-function modeling is proposed to estimate the ICC with emphasis on accounting for heterogeneous variances across a measurement scale. As an application, we review the implementation of using an ICC to evaluate the reliability of Observer OPTION5, an instrument which used trained raters to evaluate the level of Shared Decision Making between clinicians and patients. The study used two raters to evaluate recordings of 311 clinical encounters across three studies to evaluate the impact of using a Personal Decision Aid over usual care. We particularly focus on deriving an estimate for the ICC when multiple studies are being considered as part of the data.ResultsThe results demonstrate that ICC varies substantially across studies and patient-physician encounters within studies. Using the new framework we developed, the study-specific ICCs were estimated to be 0.821, 0.295, and 0.644. If the within- and between-encounter variances were assumed to be the same across studies, the estimated within-study ICC was 0.609. If heteroscedasticity is not properly adjusted for, the within-study ICC estimate was inflated to be as high as 0.640. Finally, if the data were pooled across studies without accounting for the variability between studies then ICC estimates were further inflated by approximately 0.02 while formerly allowing for between study variation in the ICC inflated its estimated value by approximately 0.066 to 0.072 depending on the model.ConclusionWe demonstrated that misuse of the ICC statistics under common assumption violations leads to misleading and likely inflated estimates of interrater reliability. A statistical analysis that overcomes these violations by expanding the standard statistical model to account for them leads to estimates that are a better reflection of a measurement scale’s reliability while maintaining ease of interpretation. Bayesian methods are particularly well suited to estimating the expanded statistical model.

Neutron width statistics in a realistic resonance-reaction model

A recent experiment on s-wave neutron scattering from $^{192,194,196}$Pt found that the reduced neutron width distributions deviate significantly from the expected Porter-Thomas distribution (PTD), and several explanations have been proposed within the statistical model of compound nucleus reactions. Here, we study the statistics of reduced neutron widths in the reaction $n+ ^{194}$Pt within a model that combines the standard statistical model with a realistic treatment of the neutron channel. We find that, if the correct secular energy dependence of the average neutron widths is used, then the reduced neutron width distribution is in excellent agreement with the PTD for a reasonable range of the neutron-nucleus coupling strength and depth of the neutron channel potential. Within our parameter range, there can be a near-threshold bound or virtual state of the neutron channel potential that modifies the energy dependence of the average width from the $\sqrt{E}$ dependence, commonly assumed in experimental analysis, in agreement with the proposal of H. A. Weidenm\"uller [1]. In these cases, the reduced neutron width distributions extracted using the $\sqrt{E}$ dependence are significantly broader than the PTD. We identify a relatively narrow range of parameters where this effect is significant.

Fission time scale from pre-scission neutron and α multiplicities in the O16 + Pt194 reaction

Pre- and post-scission $\ensuremath{\alpha}$-particle multiplicities have been measured for the reaction $^{16}O+^{194}Pt$ at 98.4 MeV forming $^{210}Rn$ compound nucleus. $\ensuremath{\alpha}$ particles were measured at various angles in coincidence with the fission fragments. Moving source technique was used to extract the pre- and post-scission contributions to the particle multiplicity. Study of the fission mechanism using the different probes are helpful in understanding the detailed reaction dynamics. The neutron multiplicities for this reaction have been reported earlier. The multiplicities of neutrons and $\ensuremath{\alpha}$ particles were reproduced using standard statistical model code joanne2 by varying the transient (${\ensuremath{\tau}}_{tr}$) and saddle to scission (${\ensuremath{\tau}}_{ssc}$) times. This code includes deformation dependent-particle transmission coefficients, binding energies and level densities. Fission time scales of the order of 50--65 $\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}21}$ s are required to reproduce the neutron and $\ensuremath{\alpha}$-particle multiplicities.

Influence of non-local thermodynamic equilibrium and Zeeman effects on magnetic equilibrium reconstruction using spectral motional Stark effect diagnostic.

The Motional Stark Effect (MSE) diagnostic is a well established technique to infer the local internal magnetic field in fusion plasmas. In this paper, the existing forward model which describes the MSE data is extended by the Zeeman effect, fine-structure, and relativistic corrections in the interpretation of the MSE spectra for different experimental conditions at the tokamak ASDEX Upgrade. The contribution of the non-Local Thermodynamic Equilibrium (non-LTE) populations among the magnetic sub-levels and the Zeeman effect on the derived plasma parameters is different. The obtained pitch angle is changed by 3°…4° and by 0.5°…1° including the non-LTE and the Zeeman effects into the standard statistical MSE model. The total correction is about 4°. Moreover, the variation of the magnetic field strength is significantly changed by 2.2% due to the Zeeman effect only. While the data on the derived pitch angle still could not be tested against the other diagnostics, the results from an equilibrium reconstruction solver confirm the obtained values for magnetic field strength.

Effect of collective enhancement in level density in the fission of pre-actinides

Fission fragment angular distributions for three reactions, $^{19}\mathrm{F}+^{182}\mathrm{W},^{19}\mathrm{F}+^{187}\mathrm{Re}$, and $^{19}\mathrm{F}+^{193}\mathrm{Ir}$, are measured in the laboratory energy range of 82--120 MeV. Extracted fission cross sections of the present systems as well as those of three others from literature $(^{19}\mathrm{F}+^{192}\mathrm{Os},^{19}\mathrm{F}+^{194}\mathrm{Pt}$, and $^{19}\mathrm{F}+^{197}\mathrm{Au})$ are compared with the predictions of a statistical model which takes into account the effects of shell, orientation degree of freedom, and collective enhancement in level density (CELD). In all the cases, the standard statistical model predictions overestimate the measured fission cross section, indicating the presence of some amount of dynamical effects in the exit channel. A dissipation strength of $2\ifmmode\times\else\texttimes\fi{}{10}^{21}\phantom{\rule{4pt}{0ex}}{\mathrm{s}}^{\ensuremath{-}1}$ is found to be sufficient to reproduce the data of all the reactions. No scaling of fission barrier height to fit the data is required.

When relative and absolute information matter: Compositional predictor with a total in generalized linear models

The analysis of compositional data (CoDa) consists in the study of the relative importance of parts of a whole rather than the size of the whole because absolute information is either unavailable or not of interest. On the other hand, when absolute and relative information are both relevant, research hypotheses concern both. This article introduces a model including both the logratios used in CoDa and a total variable carrying absolute information as predictors in an otherwise standard statistical model. It shows how logratios can be tailored to the researchers’ hypotheses and alternative ways of computing the total. The interpretational advantages with respect to traditional approaches are presented and the equivalence and invariance properties are proven. A sequence of nested models is presented to test the relevance of relative and absolute information. The approach can be applied to dependent metric, binary, ordinal or count variables. Two illustrations are provided, the first on tourist expenditure and satisfaction and the second on solid waste management and floating population.

Baysian estimation of [formula omitted] from a small sample of Gaussian data

The classical statistical uncertainty problem of estimation of upper tail probabilities on the basis of a small sample of observations of a Gaussian random variable is considered. Predictive posterior estimation is discussed, adopting the standard statistical model with diffuse priors of the two normal distribution parameters. Rarely the uncertainty of the predictive estimate itself is quantified in practice. By considering the exceedance probability as a random variable over the posterior probability distribution of the parameters, an explicit expression for the distribution of this random variable is obtained. It is shown that the usual elementary estimate based on the normal distribution is very close to the median of this distribution. For increasing exceedance level the distribution skewness increases so that the predictive estimate, which is equal to the mean of the distribution, comes further and further out in the upper tail of the distribution. The dual frequentist’s confidence interval approach is shown to have difficulties not present for the Bayesian approach.

Fusion-fission study at IUAC: Recent results

Several properties observed in heavy ion induced fission led to the conclusion that fission is not always originated from fully equilibrated compound nucleus. Soon after the collision of two nuclei, it forms a di-nuclear system than can fission before a compound nucleus is formed. This process termed quasi-fission is a major hurdle to the formation of heavier elements by fusion. Fission originated before complete equilibration showed anomalously large angular anisotropy and mass distribution wider than what is expected from compound nucleus fission. The standard statistical model fails to predict the outcome of quasi-fission and currently no dynamical model is fully developed to predict all the features of quasi-fission. Though much progress has been made in recent times, a full understanding of the fission dynamics is still missing. Experiments identifying the influence of entrance channel parameters on dynamics of fusion-fission showed contrasting results. At IUAC accelerator facility many experiments have been performed to make a systematic study of fission dynamics using mass distribution, angular distribution and neutron multiplicity measurements in mass region around A ∼ 200. Recent measurement on mass distribution of fission fragment from reaction 19 F +206,208 Pb around fusion barrier energy showed the influence of multi-mode fission in enhancing the mass variance at low excitation energy. In this talk I will present some of these results.

Are Mendel's Data Reliable? The Perspective of a Pea Geneticist.

Mendel's data exhibit remarkable agreement to the ratios he predicted. In this article, alternative explanations for this close agreement (that inheritance in pea does not conform to the standard statistical model, that data were omitted, that ambiguous data were categorized to better match predicted ratios, and that some data were deliberately falsified) are tested using approaches that are designed to distinguish between these alternatives. The possibility that garden pea (Pisum sativum L.) naturally produces segregation ratios more closely matching Mendelian expectations than predicted by statistical models is rejected. Instead the opposite is found to be the case, making Mendel's results even more remarkable. Considerable evidence is introduced that Mendel omitted some of his experimental results, but this alternative cannot adequately explain the low average deviation from expectations that is characteristic of the segregation data he presented. An underlying bias in Mendel's data favoring the predicted ratio is present, but my analysis could not clearly determine whether the bias was caused by misclassifying ambiguous phenotypes or deliberate falsification of the results. A number of Mendel's statements are argued to be unrealistic in terms of practical pea genetics, suggesting that his text does not represent a strictly accurate description of his experimental methods. Mendel's article is probably best regarded as his attempt to present his model in a simple and convincing format with a minimum of additional details that might obscure his message.

Smoothed model checking for uncertain Continuous-Time Markov Chains

We consider the problem of computing the satisfaction probability of a formula for stochastic models with parametric uncertainty. We show that this satisfaction probability is a smooth function of the model parameters under mild conditions. This enables us to devise a novel Bayesian statistical algorithm which performs model checking simultaneously for all values of the model parameters from observations of truth values of the formula over individual runs of the model at isolated parameter values. This is achieved by exploiting the smoothness of the satisfaction function: by modelling explicitly correlations through a prior distribution over a space of smooth functions (a Gaussian Process), we can condition on observations at individual parameter values to construct an analytical approximation of the function itself. Extensive experiments on non-trivial case studies show that the approach is accurate and considerably faster than naive parameter exploration with standard statistical model checking methods.

Modeling and Simulation Tools: From Systems Biology to Systems Medicine.

Modeling is an integral component of modern biology. In this chapter we look into the role of the model, as it pertains to Systems Medicine, and the software that is required to instantiate and run it. We do this by comparing the development, implementation, and characteristics of tools that have been developed to work with two divergent methodologies: Systems Biology and Pharmacometrics. From the Systems Biology perspective we consider the concept of "Software as a Medical Device" and what this may imply for the migration of research-oriented, simulation software into the domain of human health.In our second perspective, we see how in practice hundreds of computational tools already accompany drug discovery and development at every stage of the process. Standardized exchange formats are required to streamline the model exchange between tools, which would minimize translation errors and reduce the required time. With the emergence, almost 15 years ago, of the SBML standard, a large part of the domain of interest is already covered and models can be shared and passed from software to software without recoding them. Until recently the last stage of the process, the pharmacometric analysis used in clinical studies carried out on subject populations, lacked such an exchange medium. We describe a new emerging exchange format in Pharmacometrics which covers the non-linear mixed effects models, the standard statistical model type used in this area. By interfacing these two formats the entire domain can be covered by complementary standards and subsequently the according tools.

Assimilation of Tropical Cyclone Observations: Improving the Assimilation of TCVitals, Scatterometer Winds, and Dropwindsonde Observations

Abstract The standard statistical model of data assimilation assumes that the background and observation errors are normally distributed, and the first- and second-order statistical moments of the two distributions are known or can be accurately estimated. Because these assumptions are never satisfied completely in practice, data assimilation schemes must be robust to errors in the underlying statistical model. This paper tests simple approaches to improving the robustness of data assimilation in tropical cyclone (TC) regions. Analysis–forecast experiments are carried out with three types of data—Tropical Cyclone Vitals (TCVitals), DOTSTAR, and QuikSCAT—that are particularly relevant for TCs and with an ensemble-based data assimilation scheme that prepares a global analysis and a limited-area analysis in a TC basin simultaneously. The results of the experiments demonstrate that significant analysis and forecast improvements can be achieved for TCs that are category 1 and higher by improving the robustness of the data assimilation scheme.

Enhanced γ-Ray Emission from Neutron Unbound States Populated in β Decay.

Total absorption spectroscopy is used to investigate the β-decay intensity to states above the neutron separation energy followed by γ-ray emission in (87,88)Br and (94)Rb. Accurate results are obtained thanks to a careful control of systematic errors. An unexpectedly large γ intensity is observed in all three cases extending well beyond the excitation energy region where neutron penetration is hindered by low neutron energy. The γ branching as a function of excitation energy is compared to Hauser-Feshbach model calculations. For (87)Br and (88)Br the γ branching reaches 57% and 20%, respectively, and could be explained as a nuclear structure effect. Some of the states populated in the daughter can only decay through the emission of a large orbital angular momentum neutron with a strongly reduced barrier penetrability. In the case of neutron-rich (94)Rb the observed 4.5% branching is much larger than the calculations performed with standard nuclear statistical model parameters, even after proper correction for fluctuation effects on individual transition widths. The difference can be reconciled by introducing an enhancement of 1 order of magnitude in the photon strength to neutron strength ratio. An increase in the photon strength function of such magnitude for very neutron-rich nuclei, if it proves to be correct, leads to a similar increase in the (n,γ) cross section that would have an impact on r process abundance calculations.

Review Content Analytics for the Prediction of Learner\'s Feedback with Multivariate Regression Model

E-learning facilitates both synchronous and asynchronous learning and it plays very important role in the teaching learning process. A large group of learners are engaged in the idea exchange independently by interacting with the members present in the learning management system. In order to generate meaningful learning outcome of the individual peer learners, the feedback review is very essential to extract the conceptual content which reflect the instantaneous learner’s behavior, emotions, capabilities, interestingness and difficulties and to fits them effectively. Collecting feedback in the form of numeric scale is very tough for both the learners and facilitators while specifying the rating, but it is too easy for the learners provide feedback in the form of text messages. The key challenge for analyzers is to extract the meaningful feedback content and dynamic rating of the learner’s feedback related to various conceptual contexts. We propose a novel method using multivariate predictive model for conceptual content analytics based on e-learners reviews using standard statistical model inverse regression. Finally the analysis is used in the prediction studies and to illustrate their effectiveness against the learner’s feedback.

Spallation reaction versus heavy-ion fusion: Fission excitation functions as a fundamental probe of presaddle nuclear dissipation

Due to nuclear dissipation, fission cross sections drop with respect to standard statistical model predictions. Using the stochastic dynamical model of fission, we calculate the drop of fission cross sections, ${\ensuremath{\sigma}}_{f}^{\mathrm{drop}}$, as a function of presaddle dissipation strength ($\ensuremath{\beta}$) under two contrasting initial conditions for produced $^{224}\mathrm{Th}$ compound nuclei: (i) high excitation energy but low angular momentum (available in spallation reactions) and (ii) low excitation energy but high angular momentum (available in heavy-ion fusion). We find that the former type of conditions not only significantly increases the influence of friction on fission cross sections but also substantially enhances the sensitivity of ${\ensuremath{\sigma}}_{f}^{\mathrm{drop}}$ to $\ensuremath{\beta}$. Our findings suggest that on the experimental side, to accurately obtain information of presaddle friction strength with fission excitation function, it is optimal to choose the spallation reaction approach induced by energetic protons as a way to populate excited nuclear systems.

Unequal We Fight: Between- and Within-Group Inequality and Ethnic Civil War

When and why ethnic groups rebel remains a central puzzle in the civil war literature. In this paper, we examine how different types of inequalities affect both an ethnic group’s willingness and opportunity to fight. We argue that political and economic inter-group inequalities motivate ethnic groups to initiate a fight against the state, and that intra-group economic inequality lowers their elite’s costs of providing the necessary material and/or purposive incentives to overcome collective action problems inherent to rebel recruitment. We therefore predict that internally unequal ethnic groups excluded from power and/or significantly richer or poorer relative to the country’s average are most likely to engage in a civil war. To assess our claim empirically, we develop a new global measure of economic inequality by combining high-resolution satellite images of light emissions, spatial population data, and geocoded ethnic settlement areas. After validating our measure at the country- and group level, we include it in a standard statistical model of civil war onset and find considerable support for our theoretical prediction: greater economic inequality within an ethnic group significantly increases the risk of conflict, especially if political or economic inequalities between groups provide a motive.