Modeling survival times using frailty models

Traditional survival models, including Kaplan Meier, Nelson Aalen and Cox regression assume a homogeneous population; however, these are inappropriate in the presence of heterogeneity. The introduction of frailty models four decades ago addressed this limitation. Fundamentally, frailty models apply the same principles of survival theory, however, they incorporate a multiplicative term in the distribution to address the impact of frailty and cater for any underlying unobserved heterogeneity. These frailty models will be used to relate survival durations for censored data to a number of pre-operative, operative and post-operative patient related variables to identify risks factors. The study is mainly focused on fitting shared and unshared frailty models to account for unobserved frailty within the data and simultaneously identify the risk factors that best predict the hazard of death.peer-reviewe

Using Item response models to investigate attitudes towards divorce

Item Response Theory (IRT) is a form of latent structure analysis that is used to analyze binary or ordinal response data. IRT models are used to evaluate the relationships between the latent trait of interest and the items measuring the trait. Several IRT models will be fitted to assess the factors that lead to divorce in the Maltese Islands. The 1-PL and 2-PL logistic Rasch models are used for dichotomous responses, whereas the 1-PL rating scale and 1-PL partial-credit models are used for polytomous responses. All the models are fitted using the generalized linear latent and mixed modeling (GLLAMM) framework. The gllamm directive estimates parameters by maximum likelihood using adaptive quadrature (Rabe-Hesketh, Skrondal, and Pickles 2002; 2005). In the 1-PL Rasch model, the probability that a person agrees with a divorce-related item is modeled as a function of subject ability and item difficulty parameters. The major weakness of this model is that the items have the same discrimination parameter. In the 2-PL Birnbaum model, an item-specific weight is added so that the slope of the item response function varies between the items. The 1-PL rating scale model specifies that the items share the same rating scale structure, while the 1-PL partial credit model specifies a distinct rating scale structure for each item.peer-reviewe

Two Monte Carlo studies for latent class segmentation models

Model assessment and comparison are essential aspects of statistical inference. The likelihood ratio test is one of the main instruments for model selection; however, this is not appropriate when the model under consideration contains random effects. In this paper, we present two simulation studies for latent class segmentation models. The first Monte Carlo study compares the performance of seven Information Criteria in predicting the correct number of segments. The second study investigates factors that have an effect on segment membership and parameter recovery and affect computational effort.peer-reviewe

Market segmentation through conjoint analysis using latent class models

Conjoint Analysis is accepted by market researchers as a reliable and suitable instrument for measuring consumer preferences. The popularity of conjoint analysis hinges on the belief that it produces valid measurements of consumer preferences for the features of a product or service. It is the marketers’ methodology for assessing the impact of proposed actions on the market and finding out how buyers trade-off among competing products and suppliers. A popular application of conjoint analysis is market segmentation which addresses the heterogeneity in consumer preferences. Market segmentation assumes that a heterogeneous population is represented as a collection of homogeneous subgroups where customers in each cluster have similar needs and similar views of how to worth a product. Other applications of conjoint analysis include pricing strategies, product positioning, competitive analysis, promotional policies, new product identification and distribution decisions. This paper describes the issues in implementing conjoint analysis and then illustrates the methodology to perform market segmentation using latent class analysis. The application focuses on customer preferences when evaluating the worth of mobile phones given demographic and product- related predictors.peer-reviewe

Using multilevel random coefficient models to assess students’ spelling abilities

This paper presents statistical models that analyze cross- sectional data related to student attainment in English and Maltese spelling. For each spelling test a random sample of 2040 students, whose age ranged from 6.5 to 16 years, was selected to examine the progression of spelling skills over time. The sample comprised equal numbers of male and female students attending state, church and private schools to investigate gender and school bias in students’ spelling abilities. This hierarchical nested data can be deemed as a type of two-level data, in which the students spelling scores are level-1 units and schools are the level- 2 units. This multilevel approach provides an adequate framework for modelling hierarchical data at several levels of nesting. To inspect the effect of age on student performance in English and Maltese spelling in different schools, a random coefficient model is fitted. This allows the school-specific coefficients describing individual trajectories to vary randomly when the spelling scores are regressed against the student age.peer-reviewe

Predicting motor policy loss – a ZAIG model or a two stage neural network approach?

Artificial neural networks have increasingly being applied to solve problems which traditionally would have fallen under the domain of more classical statistical methodology, and the latter has long been a staple of popular actuarial methodology. We aim to compare a two-stage artificial neural network approach with the zero-adjusted inverse Gaussian model for predicting the claim of a motor insurance policy, which is a popular method with actuaries. The performance of both approaches is analysed by means of K-fold cross-validation. The conclusion reached is that our approach provides a comparable, if not superior, overall performance in predicting policy loss which is more robust to extreme observations.peer-reviewe

Social Media, Gender and the Mediatisation of War: Exploring the German Armed Forces’ Visual Representation of the Afghanistan Operation on Facebook

Studies on the mediatisation of war point to attempts of governments to regulate the visual perspective of their involvements in armed conflict – the most notable example being the practice of ‘embedded reporting’ in Iraq and Afghanistan. This paper focuses on a different strategy of visual meaning-making, namely, the publication of images on social media by armed forces themselves. Specifically, we argue that the mediatisation of war literature could profit from an increased engagement with feminist research, both within Critical Security/Critical Military Studies and within Science and Technology Studies that highlight the close connection between masculinity, technology and control. The article examines the German military mission in Afghanistan as represented on the German armed forces’ official Facebook page. Germany constitutes an interesting, and largely neglected, case for the growing literature on the mediatisation of war: its strong antimilitarist political culture makes the representation of war particularly delicate. The paper examines specific representational patterns of Germany’s involvement in Afghanistan and discusses the implications which arise from what is placed inside the frame of visibility and what remains out of its view