Knowledge extraction from a large on-line survey: a case study for a higher education corporate marketing

For a higher education public institution, young in relative terms, featuring local competition with another private and both long-established and reputed one, it is of great importance to become a reference university institution to be better known and felt with identification in the society it belongs to and ultimately to reach a good position within the European Higher Education Area. These considerations have made the university governors setting up the objective of achieving an adequate management of the university institutional brand focused on its logo and on image promotion, leading to the establishment of a university shop as it is considered a highly adequate instrument for such promotion. In this context, an on-line survey is launched on three different kinds of members of the institution, resulting in a large data sample. Different kinds of variables are analysed through appropriate exploratory multivariate techniques (symmetrical methods) and regression-related techniques (non-symmetrical methods). An advocacy for such combination is given as a conclusion. The application of statistical techniques of data and text mining provides us with empirical insights about the institution members’ perceptions and helps us to extract some facts valuable to establish policies that would improve the corporate identity and the success of the corporate shop.     

A general hazard model for lifetime data in the presence of cure rate

Historically, the cure rate model has been used for modeling time-to-event data within which a significant proportion of patients are assumed to be cured of illnesses, including breast cancer, non-Hodgkin lymphoma, leukemia, prostate cancer, melanoma, and head and neck cancer. Perhaps the most popular type of cure rate model is the mixture model introduced by Berkson and Gage [1]. In this model, it is assumed that a certain proportion of the patients are cured, in the sense that they do not present the event of interest during a long period of time and can found to be immune to the cause of failure under study. In this paper, we propose a general hazard model which accommodates comprehensive families of cure rate models as particular cases, including the model proposed by Berkson and Gage. The maximum-likelihood-estimation procedure is discussed. A simulation study analyzes the coverage probabilities of the asymptotic confidence intervals for the parameters. A real data set on children exposed to HIV by vertical transmission illustrates the methodology.     

Two-tailed asymptotic inferences for a proportion

This paper evaluates 29 methods for obtaining a two-sided confidence interval for a binomial proportion (16 of which are new proposals) and comes to the conclusion that: Wilson's classic method is only optimal for a confidence of 99%, although generally it can be applied when n≥50; for a confidence of 95% or 90%, the optimal method is the one based on the arcsine transformation (when this is applied to the data incremented by 0.5), which behaves in a very similar manner to Jeffreys’ Bayesian method. A simpler option, though not so good as those just mentioned, is the classic-adjusted Wald method of Agresti and Coull.     

Eliciting expert judgements about a set of proportions

Eliciting expert knowledge about several uncertain quantities is a complex task when those quantities exhibit associations. A well-known example of such a problem is eliciting knowledge about a set of uncertain proportions which must sum to 1. The usual approach is to assume that the expert's knowledge can be adequately represented by a Dirichlet distribution, since this is by far the simplest multivariate distribution that is appropriate for such a set of proportions. It is also the most convenient, particularly when the expert's prior knowledge is to be combined with a multinomial sample since then the Dirichlet is the conjugate prior family. Several methods have been described in the literature for eliciting beliefs in the form of a Dirichlet distribution, which typically involve eliciting from the expert enough judgements to identify uniquely the Dirichlet hyperparameters. We describe here a new method which employs the device of over-fitting, i.e. eliciting more than the minimal number of judgements, in order to (a) produce a more carefully considered Dirichlet distribution and (b) ensure that the Dirichlet distribution is indeed a reasonable fit to the expert's knowledge. The method has been implemented in a software extension of the Sheffield elicitation framework (SHELF) to facilitate the multivariate elicitation process.     

Modeling Lifetimes by a Stochastic Process Hitting a Critical Point

First hitting times arise naturally in survival analysis where the underlying stochastic counting process represents the strength of the health of an individual. The patient experiences a clinical endpoint when this process reaches a critical point for the first time. We propose a very flexible and unified first hitting time density function in a stochastic carcinogenesis counting process, and its mathematical properties are investigated. The Poisson and negative binomial first hitting time models are addressed and two examples with real data are presented.     

Logratio approach to statistical analysis of 2×2 compositional tables

Compositional tables represent a continuous counterpart to well-known contingency tables. Their cells contain quantitatively expressed relative contributions of a whole, carrying exclusively relative information and are popularly represented in proportions or percentages. The resulting factors, corresponding to rows and columns of the table, can be inspected similarly as with contingency tables, e.g. for their mutual independent behaviour. The nature of compositional tables requires a specific geometrical treatment, represented by the Aitchison geometry on the simplex. The properties of the Aitchison geometry allow a decomposition of the original table into its independent and interactive parts. Moreover, the specific case of 2×2 compositional tables allows the construction of easily interpretable orthonormal coordinates (resulting from the isometric logratio transformation) for the original table and its decompositions. Consequently, for a sample of compositional tables both explorative statistical analysis like graphical inspection of the independent and interactive parts or any statistical inference (odds-ratio-like testing of independence) can be performed. Theoretical advancements of the presented approach are demonstrated using two economic applications.     

A Nonstationary Cylinder–Based Model Describing Group Dispersal in a Fragmented Habitat

□ A doubly nonstationary cylinder-based model is built to describe the dispersal of a population from a point source. In this model, each cylinder represents a fraction of the population, i.e., a group. Two contexts are considered: The dispersal can occur in a uniform habitat or in a fragmented habitat described by a conditional Boolean model. After the construction of the models, we investigate their properties: the first and second order moments, the probability that the population vanishes, and the distribution of the spatial extent of the population.     

Life Goals and Well-Being: Does Financial Status Matter? Evidence from a Representative Hungarian Sample

Previous research with the Aspiration Index suggests that the importance of intrinsic life goals (e.g. personal growth and relationships) is in positive association with indicators of well-being, whereas an orientation toward extrinsic life goals (e.g. wealth and appearance) is connected with decreased positive functioning. Our study extended the scope of previous research by analyzing the role of financial status (income and subjective financial status). Examining a nationally representative cross-sectional sample of 4,841 Hungarian adults, we found that after controlling for several sociodemographic variables intrinsic goal importance was in a positive relationship with subjective well-being (SWB) and meaning in life (ML), whereas the contribution of extrinsic life goals was weak to SWB and negative to ML. Moreover, no moderation effects were found for indices of financial status, indicating that the relationship between life goals and well-being is the same for poorer and for richer respondents. Results show that the basic assumptions of the Aspiration Index research are also valid when testing on a societal level.     

Subjective Welfare, Well-Being, and Self-Reported Food Hypersensitivity in Four European Countries: Implications for European Policy

This study estimates the effects of food hypersensitivity on individuals?? perceived welfare and well-being compared to non-food hypersensitive individuals. Study respondents were recruited in the Netherlands, Poland, Spain and UK. The difference in welfare between food hypersensitive respondents and those asymptomatic to foods was estimated using a subjective welfare approach, including income evaluation. Well-being was measured using the Cantril Ladder-of-Life Scale, and health status using the Self-Perceived Health Scale. The difference in well-being, welfare and health status between participant groups was explained further using a number of background variables. No significant within-country differences in welfare between food hypersensitive respondents and respondents asymptomatic to foods were found. In terms of well-being, adult food hypersensitive respondents and their spouses reported significantly less happiness than respondents and their spouses asymptomatic to foods in the Netherlands and Poland. In Spain, the spouses of the food hypersensitive respondents were significantly less happy than respondents aymptomatic to foods. The well-being of children did not significantly differ between groups. The degree of severity of food hypersensitivity was negatively related to overall health status. In Poland, food hypersensitive respondents reported worse health status compared to asymptomatic respondents. In Spain, the converse was true. Food hypersensitive respondents were generally less happy with their life as a whole than respondents asymptomatic to foods, presumably because they experienced more negative effects, which were not related to perceived health status.