376 research outputs found
On a class of time-Fractional continuous-State branching processes
We propose a class of non-Markov population models with continuous or discrete state space via a limiting procedure involving sequences of rescaled and randomly time-changed Galton – Watson processes. The class includes as specific cases the classical continuous-state branching processes and Markov branching processes. Several results such as the expressions of moments and the branching inequality governing the evolution of the process are presented and commented. The generalized Feller branching diffusion and the fractional Yule process are analyzed in detail as special cases of the general model
Towards Validation and Verification of Autonomous Vision-Based Navigation for Interplanetary Spacecraft
Strong existence and uniqueness of the stationary distribution for a stochastic inviscid dyadic model
We consider an inviscid stochastically forced dyadic model, where the additive noise acts only on the first component. We prove that a strong solution for this problem exists and is unique by means of uniform energy estimates. Moreover, we exploit these results to establish strong existence and uniqueness of the stationary distribution
Multidimensional item response theory models for dichotomous data in customer satisfaction evaluation
In this paper, multidimensional item response theory models for dichotomous data, developed in the fields of psychometrics and ability assessment, are discussed in connection with the problem of evaluating customer satisfaction. These models allow us to take into account latent constructs at various degrees of complexity and provide interesting new perspectives for services quality assessment. Markov chain Monte Carlo techniques are considered for estimation. An application to a real data set is also presente
A proposal for the multidimensional extension of CUB models
Particular emphasis has been put, lately, on the analysis of categorical data and many proposals have appeared, ranging from pure methodological contributions to more applicative ones. Among such proposals, the CUB class of distributions, a mixture model for the analysis of ordinal data that has been successfully employed in various fields, seems of particular interest. CUB are univariate models that do not
possess, at present, a multivariate version: aim of the present work is to investigate the feasibility of building a higher-dimensional version of such models and its possible applications. In order to achieve such results, we propose to employ techniques typical of the framework of copula models, that have proven to be valid tools for multivariate models construction and data analysi
Missing data and parameters estimates in multidimensional item response models
Statistical analyses of data based on surveys usually face the problem
of missing data. However, some statistical methods require a complete data
matrix to be applicable, hence the need to cope with such missingness. Literature
on imputation abounds with contributions concerning quantitative responses, but
seems to be poor with respect to the handling of categorical data. The present
work aims at evaluating the impact of different imputation methods on
multidimensional IRT models estimation for dichotomous data
Hardware-In-the-loop Validation of Autonomous Interplanetary Navigation Algorithms for Interplanetary Cruises with the Optical Star Stimulator
Multidimensional extensions of IRT models and their application to customer satisfaction evaluation
Multidimensional IRT models (MIRTM), developed in the fields of psychometrics
and ability assessment, are here considered in connection with the problem of evaluating customer satisfaction. Different models, that allow us to take into account more complex and, possibly, more realistic latent constructs than those usually assumed, are presented and discussed. Eventually, these models are applied to a real dataset, MCMC techniques for the estimation are implemented and analogies and differences with results from previous analyses on the same survey in the literature are discussed
Longitudinal study of the relationship between patients' medication adherence and quality of life outcomes and illness perceptions and beliefs about cardiac rehabilitation
Background Adherence to medication regimens is essential for preventing and reducing adverse outcomes among patients with coronary artery disease (CAD). Greater understanding of the relation between negative illness perceptions, beliefs about cardiac rehabilitation (CR) and medication adherence may help inform future approaches to improving medication adherence and quality of life (QoL) outcomes. The aims of the study are: 1) to compare changes in illness perceptions, beliefs about CR, medication adherence and QoL on entry to a CR programme and 6 months later; 2) to examine associations between patients’ illness perceptions and beliefs about CR at baseline and medication adherence and QoL at 6 months. Methods A longitudinal study of 40 patients with CAD recruited from one CR service in Scotland. Patients completed the Medication Adherence Report Scale, Brief Illness Perception Questionnaire, Beliefs about CR questionnaire and the Short-Form 12 Health Survey. Data were analysed using the Wilcoxon Signed Ranks test, Pearson Product Moment correlation and Bayesian multiple logistic regression. Results Most patients were men (70%), aged 62.3 mean (SD 7.84) years. Small improvements in ‘perceived suitability’ of CR at baseline increased the odds of being fully adherent to medication by approximately 60% at 6 months. Being fully adherent at baseline increased the odds of staying so at 6 months by 13.5 times. ‘Perceived necessity, concerns for exercise and practical barriers’ were negatively associated with reductions in the probability of full medication adherence of 50, 10, and 50%. Small increases in concerns about exercise decreased the odds of better physical health at 6 months by about 50%; and increases in practical barriers decreased the odds of better physical health by about 60%. Patients perceived fewer consequences of their cardiac disease at 6 months. Conclusions Patients’ beliefs on entry to a CR programme are especially important to medication adherence at 6 months. Negative beliefs about CR should be identified early in CR to counteract any negative effects on QoL. Interventions to improve medication adherence and QoL outcomes should focus on improving patients’ negative beliefs about CR and increasing understanding of the role of medication adherence in preventing a future cardiac event
- …