Hierarchical models for 2D presence/absence data having ambiguous zeroes: With a biogeographical case study on dingo behaviour

This dissertation is primarily an applied statistical modelling investigation, motivated by a case study comprising real data and real questions. Theoretical questions on modelling and computation of normalization constants arose from pursuit of these data analytic questions. The essence of the thesis can be described as follows. Consider binary data observed on a two-dimensional lattice. A common problem with such data is the ambiguity of zeroes recorded. These may represent zero response given some threshold (presence) or that the threshold has not been triggered (absence). Suppose that the researcher wishes to estimate the effects of covariates on the binary responses, whilst taking into account underlying spatial variation, which is itself of some interest. This situation arises in many contexts and the dingo, cypress and toad case studies described in the motivation chapter are examples of this. Two main approaches to modelling and inference are investigated in this thesis. The first is frequentist and based on generalized linear models, with spatial variation modelled by using a block structure or by smoothing the residuals spatially. The EM algorithm can be used to obtain point estimates, coupled with bootstrapping or asymptotic MLE estimates for standard errors. The second approach is Bayesian and based on a three- or four-tier hierarchical model, comprising a logistic regression with covariates for the data layer, a binary Markov Random field (MRF) for the underlying spatial process, and suitable priors for parameters in these main models. The three-parameter autologistic model is a particular MRF of interest. Markov chain Monte Carlo (MCMC) methods comprising hybrid Metropolis/Gibbs samplers is suitable for computation in this situation. Model performance can be gauged by MCMC diagnostics. Model choice can be assessed by incorporating another tier in the modelling hierarchy. This requires evaluation of a normalization constant, a notoriously difficult problem. Difficulty with estimating the normalization constant for the MRF can be overcome by using a path integral approach, although this is a highly computationally intensive method. Different methods of estimating ratios of normalization constants (N Cs) are investigated, including importance sampling Monte Carlo (ISMC), dependent Monte Carlo based on MCMC simulations (MCMC), and reverse logistic regression (RLR). I develop an idea present though not fully developed in the literature, and propose the Integrated mean canonical statistic (IMCS) method for estimating log NC ratios for binary MRFs. The IMCS method falls within the framework of the newly identified path sampling methods of Gelman & Meng (1998) and outperforms ISMC, MCMC and RLR. It also does not rely on simplifying assumptions, such as ignoring spatio-temporal dependence in the process. A thorough investigation is made of the application of IMCS to the three-parameter Autologistic model. This work introduces background computations required for the full implementation of the four-tier model in Chapter 7. Two different extensions of the three-tier model to a four-tier version are investigated. The first extension incorporates temporal dependence in the underlying spatio-temporal process. The second extensions allows the successes and failures in the data layer to depend on time. The MCMC computational method is extended to incorporate the extra layer. A major contribution of the thesis is the development of a fully Bayesian approach to inference for these hierarchical models for the first time. Note: The author of this thesis has agreed to make it open access but invites people downloading the thesis to send her an email via the 'Contact Author' function.

Discovering, applying and integrating self-knowledge : a grounded theory study of learning in life coaching

Professional coaching is a rapidly expanding field with interdisciplinary roots and broad application. However, despite abundant prescriptive literature, research into the process of coaching, and especially life coaching, is minimal. Similarly, although learning is inherently recognised in the process of coaching, and coaching is increasingly being recognised as a means of enhancing teaching and learning, the process of learning in coaching is little understood, and learning theory makes up only a small part of the evidence-based coaching literature. In this grounded theory study of life coaches and their clients, the process of learning in life coaching across a range of coaching models is examined and explained. The findings demonstrate how learning in life coaching emerged as a process of discovering, applying and integrating self-knowledge, which culminated in the development of self. This process occurred through eight key coaching processes shared between coaches and clients and combined a multitude of learning theory.

A grounded theory study of technology appropriation in anaesthesia

The human-technology nexus is a strong focus of Information Systems (IS) research; however, very few studies have explored this phenomenon in anaesthesia. Anaesthesia has a long history of adoption of technological artifacts, ranging from early apparatus to present-day information systems such as electronic monitoring and pulse oximetry. This prevalence of technology in modern anaesthesia and the rich human-technology relationship provides a fertile empirical setting for IS research. This study employed a grounded theory approach that began with a broad initial guiding question and, through simultaneous data collection and analysis, uncovered a core category of technology appropriation. This emergent basic social process captures a central activity of anaesthestists and is supported by three major concepts: knowledge-directed medicine, complementary artifacts and culture of anaesthesia. The outcomes of this study are: (1) a substantive theory that integrates the aforementioned concepts and pertains to the research setting of anaesthesia and (2) a formal theory, which further develops the core category of appropriation from anaesthesia-specific to a broader, more general perspective. These outcomes fulfill the objective of a grounded theory study, being the formation of theory that describes and explains observed patterns in the empirical field. In generalizing the notion of appropriation, the formal theory is developed using the theories of Karl Marx. This Marxian model of technology appropriation is a three-tiered theoretical lens that examines appropriation behaviours at a highly abstract level, connecting the stages of natural, species and social being to the transition of a technology-as-artifact to a technology-in-use via the processes of perception, orientation and realization. The contributions of this research are two-fold: (1) the substantive model contributes to practice by providing a model that describes and explains the human-technology nexus in anaesthesia, and thereby offers potential predictive capabilities for designers and administrators to optimize future appropriations of new anaesthetic technological artifacts; and (2) the formal model contributes to research by drawing attention to the philosophical foundations of appropriation in the work of Marx, and subsequently expanding the current understanding of contemporary IS theories of adoption and appropriation.

Pretreatment malnutrition and quality of life - association with prolonged length of hospital stay among patients with gynecological cancer: A cohort study

Background Length of hospital stay (LOS) is a surrogate marker for patients' well-being during hospital treatment and is associated with health care costs. Identifying pretreatment factors associated with LOS in surgical patients may enable early intervention in order to reduce postoperative LOS. Methods This cohort study enrolled 157 patients with suspected or proven gynecological cancer at a tertiary cancer centre (2004-2006). Before commencing treatment, the scored Patient Generated - Subjective Global Assessment (PG-SGA) measuring nutritional status and the Functional Assessment of Cancer Therapy-General (FACT-G) scale measuring quality of life (QOL) were completed. Clinical and demographic patient characteristics were prospectively obtained. Patients were grouped into those with prolonged LOS if their hospital stay was greater than the median LOS and those with average or below average LOS. Results Patients' mean age was 58 years (SD 14 years). Preoperatively, 81 (52%) patients presented with suspected benign disease/pelvic mass, 23 (15%) with suspected advanced ovarian cancer, 36 (23%) patients with suspected endometrial and 17 (11%) with cervical cancer, respectively. In univariate models prolonged LOS was associated with low serum albumin or hemoglobin, malnutrition (PG-SGA score and PG-SGA group B or C), low pretreatment FACT-G score, and suspected diagnosis of cancer. In multivariable models, PG-SGA group B or C, FACT-G score and suspected diagnosis of advanced ovarian cancer independently predicted LOS. Conclusions Malnutrition, low quality of life scores and being diagnosed with advanced ovarian cancer are the major determinants of prolonged LOS amongst gynecological cancer patients. Interventions addressing malnutrition and poor QOL may decrease LOS in gynecological cancer patients.

Performance study of two different compensating devices in a custom power park

Simulation study of a custom power park (CPP) is presented. It is assumed that the park contains unbalanced and nonlinear loads in addition to a sensitive load. Two different types of compensators are used separately to protect the sensitive load against unbalance and distortion caused by the other loads. It has been shown that a shunt compensator can regulate the voltage of the CPP bus, whereas the series compensator can only regulate the sensitive load terminal voltage. Additional issues such as the load transfer through a static transfer switch, detection of sag/fault etc. are also discussed. The concepts are validated through PSCAD/EMTDC simulation studies on a sample distribution system.