Use Of Transition Probabilities Research Articles

Assessing via Simulation the Operating Characteristics of the WHO Scale for COVID-19 Endpoints

ABSTRACTMany clinical trials of treatments for patients hospitalised for COVID-19 use an ordinal scale recommended by the World Heath Organisation. The scale represents intensity of medical intervention, with higher scores for interventions more burdensome for the patient, and highest score for death. There is uncertainty about use of this ordinal scale in testing hypotheses. With the objective of assessing the power and Type I error of potential endpoints and analyses based on the ordinal scale, trajectories of the score over 28 days were simulated for scenarios based closely on results of two trials recently published. The simulation used transition probabilities for the ordinal scale over time. No one endpoint was optimal across scenarios, but a ranked measure of trajectory fared moderately well in all scenarios. Type I error was controlled at close to the nominal level for all endpoints. Because not tied to a particular population with regard to baseline severity, the use of transition probabilities allows plausible assessment of endpoints in populations with configurations of baseline score for which data is not yet published, provided some data on the relevant transition probabilities are available. The results could support experts in the choice of endpoint based on the ordinal scale.

The impact of cigarette and e-cigarette use history on transition patterns: a longitudinal analysis of the population assessment of tobacco and health (PATH) study, 2013\u20132015

BackgroundPopulation models have been developed to evaluate the impact of new tobacco products on the overall population. Reliable input parameters such as longitudinal tobacco use transitions are needed to quantify the net population health impact including the number of premature deaths prevented, additional life years, and changes in cigarette smoking prevalence.MethodsThis secondary analysis assessed transition patterns from PATH wave 1 (2013–14) to wave 2 (2014–15) among adult exclusive cigarette smokers, exclusive e-cigarette users, and dual users. Transition probabilities were calculated by taking into account factors including cigarette smoking and e-cigarette use histories and experimental or established use behaviors. Multinomial logistic regression models were constructed to further evaluate factors associated with transition patterns.ResultsDifferential transition probabilities emerged among study subgroups when taking into account cigarette smoking and e-cigarette use histories and experimental or established use behaviors. For example, overall 45% of exclusive e-cigarette users in wave 1 continued using e-cigarettes exclusively in wave 2. However, we observed approximately 11 to 14% of wave 1 exclusive experimental e-cigarette users continued to use e-cigarette exclusively in wave 2, compared to about 62% of exclusive established e-cigarette users. The history of cigarette smoking and e-cigarette use is another important factor associated with transition patterns. Among experimental e-cigarette users, 7.5% of individuals without a history of cigarette smoking transitioned to exclusive cigarette smoking, compared to 30% of individuals with a history of cigarette smoking. Additionally, 1.3% of exclusive cigarette smokers in wave 1 transitioned to exclusive e-cigarette use, with the highest transition probability (3.7%) observed in the established cigarette smoker with a history of e-cigarette use subgroup.ConclusionsProduct use histories and current use behaviors are important factors influencing transitions between product use states. Given that experimental users’ transition behaviors may be more variable and more influenced by tobacco use history, long-term predictions made by population models could be improved by the use of transition probabilities from established users. As transition patterns might be changing over time, long-term transition patterns can be examined through analysis of future waves of PATH data.

An alternative method for evaluating stationarity in transition models

ABSTRACTTransition models are an important framework that can be used to model longitudinal categorical data. A relevant issue in applying these models is the condition of stationarity, or homogeneity of transition probabilities over time. We propose two tests to assess stationarity in transition models: Wald and likelihood-ratio tests, which do not make use of transition probabilities, using only the estimated parameters of the models in contrast to the classical test available in the literature. In this paper, we present two motivating studies, with ordinal longitudinal data, to which proportional odds transition models are fitted and the two proposed tests are applied as well as the classical test. Additionally, their performances are assessed through simulation studies. The results show that the proposed tests have good performance, being better for control of type-I error and they present equivalent power functions asymptotically. Also, the correlations between the Wald, likelihood-ratio and the classical test statistics are positive and large, an indicator of general concordance. Additionally, both of the proposed tests are more flexible and can be applied in studies with qualitative and quantitative covariates.

A Stochastic Inversion Method for Potential Field Data: Ant Colony Optimization

Simulating natural ants’ foraging behavior, the ant colony optimization (ACO) algorithm performs excellently in combinational optimization problems, for example the traveling salesman problem and the quadratic assignment problem. However, the ACO is seldom used to inverted for gravitational and magnetic data. On the basis of the continuous and multi-dimensional objective function for potential field data optimization inversion, we present the node partition strategy ACO (NP-ACO) algorithm for inversion of model variables of fixed shape and recovery of physical property distributions of complicated shape models. We divide the continuous variables into discrete nodes and ants directionally tour the nodes by use of transition probabilities. We update the pheromone trails by use of Gaussian mapping between the objective function value and the quantity of pheromone. It can analyze the search results in real time and promote the rate of convergence and precision of inversion. Traditional mapping, including the ant-cycle system, weaken the differences between ant individuals and lead to premature convergence. We tested our method by use of synthetic data and real data from scenarios involving gravity and magnetic anomalies. The inverted model variables and recovered physical property distributions were in good agreement with the true values. The ACO algorithm for binary representation imaging and full imaging can recover sharper physical property distributions than traditional linear inversion methods. The ACO has good optimization capability and some excellent characteristics, for example robustness, parallel implementation, and portability, compared with other stochastic metaheuristics.

The Entropy Theoretic Measure for Manpower Systems in Perspective

This study provides a realistic appraisal of the use of entropy measures in manpower systems. The appraisal shows that the existing entropy measures for manpower systems give a partial picture of the behavioural mechanism of the system. Consequent upon this, we propose the use of transition probabilities of the imbedded Markov chain for manpower systems as inputs in the entropy statistic. The proposal is illustrated by refining the basic Shannon entropy rate and implemented in Matlab computing environment.Keywords: entropy, manpower system, Markov chain, Matlab package.

Transitional probabilities and positional frequency phonotactics in a hierarchical model of speech segmentation

The present study explored the influence of a new metrics of phonotactics on adults' use of transitional probabilities to segment artificial languages. We exposed French native adults to continuous streams of trisyllabic nonsense words. High-frequency words had either high or low congruence with French phonotactics, in the sense that their syllables had either high or low positional frequency in French trisyllabic words. At test, participants heard low-frequency words and part-words, which differed in their transitional probabilities (high for words, low for part-words) but were matched for frequency and phonotactic congruency. Participants' preference for words over part-words was found only in the high-congruence languages. These results establish that subtle phonotactic manipulations can influence adults' use of transitional probabilities to segment speech and unambiguously demonstrate that this prior knowledge interferes directly with segmentation processes, in addition to affecting subsequent lexical decisions. Implications for a hierarchical theory of segmentation cues are discussed.

DNA Binding Site Characterization by Means of RÉnyi Entropy Measures on Nucleotide Transitions

In this work, parametric information-theory measures for the characterization of binding sites in DNA are extended with the use of transitional probabilities on the sequence. We propose the use of parametric uncertainty measures such as Rényi entropies obtained from the transition probabilities for the study of the binding sites, in addition to nucleotide frequency-based Rényi measures. Results are reported in this work comparing transition frequencies (i.e., dinucleotides) and base frequencies for Shannon and parametric Rényi entropies for a number of binding sites found in E. Coli, lambda and T7 organisms. We observe that the information provided by both approaches is not redundant. Furthermore, under the presence of noise in the binding site matrix we observe overall improved robustness of nucleotide transition-based algorithms when compared with nucleotide frequency-based method.

Use of transition probabilities to estimate the effect of smoking on the duration of episodes of respiratory symptoms in diary data: the Swiss Study on Air Pollution and Lung Diseases in Adults (SAPALDIA).

Incompletely documented symptom episodes pose methodological problems in the analysis of diary data. The aim of this study was to develop a method of estimating the average durations of symptomatic and nonsymptomatic episodes, respectively, coping with the problem of bias due to undocumented days and censored episodes that is found in most diary studies. The authors derived their outcome variables from a Markov model using transition probabilities. To evaluate this method, the authors assessed the impact of active smoking on the duration of episodes of bronchitis symptoms and the corresponding nonsymptomatic periods, respectively, using diary data (1992-1993) obtained from 801 participants in the Swiss Study on Air Pollution and Lung Diseases in Adults. Covariate-adjusted distribution curves for the mean durations of individual episodes were estimated by Cox regression. Median values for light smokers (<10 cigarettes/day) were 60.0 symptom-free days (95% confidence interval (CI) 42.0-78.5) and 4.0 symptomatic days (95% CI 3.0-6.0), respectively, compared with medians of only 21.0 days (95% CI 16.2-29.8) for periods without bronchitis symptoms and 6.0 days (95% CI 4.9-9.0) for episodes of bronchitis symptoms in heavy smokers (> or =30 cigarettes/day). The authors suggest that the Markov method is a feasible approach to the assessment of long term effects of smoking and environmental risk factors on the average duration of symptomatic and nonsymptomatic respiratory episodes.

A tutorial discussion on measurements of rotational temperature in inductively coupled plasmas

The intensities in the rotational fine structure of electronic bands such as B 2Σ + u → X 2Σ + g of N + 2, A 2Σ + → X 2Π i, of OH and B 3Σ u − → X 3Σ − g of O 2 are often used for measurements of rotational temperature prevailing in plasma sources such as the inductively coupled plasmas (ICP) and microwave induced plasmas (MIP). Certain misconceptions (such as the incorrect use of Hund's rule, the use of transition probability in conjuction with the equation for line strength, and the incorrect assignment of rotational lines) in the calculations of rotational temperatures have led to erroneous results. The main point of this paper is to emphasize that the interpretation of the rotational intensity distribution depends on both the angular momentum coupling and on the resolution of the instrument used. In this report, the introductory theory of rotational temperature measurement is reviewed and examples of correct and incorrect calculations are cited for ICP and MIP discharges sustained in argon, helium, argon-nitrogen, argon-oxygen and argon-air.

Nonresonant wave-particle interaction in semiclassical quasilinear theory.

A nonresonant nature of wave-particle interaction is clarified from the viewpoint of quantum mechanics. The interaction of particles and quasiparticles can be described by the use of transition probability which is found to have both resonant and nonresonant contributions. The resonant transition probability is known as Fermi's golden rule, which is now supplemented by the nonresonant contribution, resulting in the proper conservation of energy and momentum in the particle-quasiparticle system.

Beam-foil excitation of xenon, 4 MeV

We have measured the optical spectrum from beam-foil excited xenon in the wavelength region 20–600 nm, at a projectile energy of 4 MeV. Relative initial level populations have been deduced for levels of silver-like xenon (Xe VIII), by use of transition probabilities calculated in the numerical Coulomb approximation. The results are in accordance with recent works with multiply charged lighter ions, namely that some of the low-lying levels are excited strongly through selective quasi-molecular inner-shell electron promotion processes. In addition, there is a strong excitation of high-lying Rydberg states ( n = 10) caused by quasi-resonant pick-up of electrons from the valence band of the foil.