975 resultados para Average models


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Three particular geometrical shapes of parallelepiped, cylindrical and spheres were selected from potatoes (aspect ratio = 1:1, 2:1, 3:1), cut beans (length:diameter = 1:1, 2:1, 3:1) and peas respectively. The density variation of food particulates was studied in a batch fluidised bed dryer connected to a heat pump dehumidifier system. Apparent density and bulk density were evaluated with non-dimensional moisture at three different drying temperatures of 30, 40 and 50 o C. Relative humidity of hot air was kept at 15% in all drying temperatures. Several empirical relationships were developed for the determination of changes in densities with the moisture content. Simple mathematical models were obtained to relate apparent density and bulk density with moisture content.

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We have developed a new experimental method for interrogating statistical theories of music perception by implementing these theories as generative music algorithms. We call this method Generation in Context. This method differs from most experimental techniques in music perception in that it incorporates aesthetic judgments. Generation In Context is designed to measure percepts for which the musical context is suspected to play an important role. In particular the method is suitable for the study of perceptual parameters which are temporally dynamic. We outline a use of this approach to investigate David Temperley’s (2007) probabilistic melody model, and provide some provisional insights as to what is revealed about the model. We suggest that Temperley’s model could be improved by dynamically modulating the probability distributions according to the changing musical context.

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Longitudinal data, where data are repeatedly observed or measured on a temporal basis of time or age provides the foundation of the analysis of processes which evolve over time, and these can be referred to as growth or trajectory models. One of the traditional ways of looking at growth models is to employ either linear or polynomial functional forms to model trajectory shape, and account for variation around an overall mean trend with the inclusion of random eects or individual variation on the functional shape parameters. The identification of distinct subgroups or sub-classes (latent classes) within these trajectory models which are not based on some pre-existing individual classification provides an important methodology with substantive implications. The identification of subgroups or classes has a wide application in the medical arena where responder/non-responder identification based on distinctly diering trajectories delivers further information for clinical processes. This thesis develops Bayesian statistical models and techniques for the identification of subgroups in the analysis of longitudinal data where the number of time intervals is limited. These models are then applied to a single case study which investigates the neuropsychological cognition for early stage breast cancer patients undergoing adjuvant chemotherapy treatment from the Cognition in Breast Cancer Study undertaken by the Wesley Research Institute of Brisbane, Queensland. Alternative formulations to the linear or polynomial approach are taken which use piecewise linear models with a single turning point, change-point or knot at a known time point and latent basis models for the non-linear trajectories found for the verbal memory domain of cognitive function before and after chemotherapy treatment. Hierarchical Bayesian random eects models are used as a starting point for the latent class modelling process and are extended with the incorporation of covariates in the trajectory profiles and as predictors of class membership. The Bayesian latent basis models enable the degree of recovery post-chemotherapy to be estimated for short and long-term followup occasions, and the distinct class trajectories assist in the identification of breast cancer patients who maybe at risk of long-term verbal memory impairment.

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Speeding remains a significant contributing factor to road trauma internationally, despite increasingly sophisticated speed management strategies being adopted around the world. Increases in travel speed are associated with increases in crash risk and crash severity. As speed choice is a voluntary behaviour, driver perceptions are important to our understanding of speeding and, importantly, to designing effective behavioural countermeasures. The four studies conducted in this program of research represent a comprehensive approach to examining psychosocial influences on driving speeds in two countries that are at very different levels of road safety development: Australia and China. Akers’ social learning theory (SLT) was selected as the theoretical framework underpinning this research and guided the development of key research hypotheses. This theory was chosen because of its ability to encompass psychological, sociological, and criminological perspectives in understanding behaviour, each of which has relevance to speeding. A mixed-method design was used to explore the personal, social, and legal influences on speeding among car drivers in Queensland (Australia) and Beijing (China). Study 1 was a qualitative exploration, via focus group interviews, of speeding among 67 car drivers recruited from south east Queensland. Participants were assigned to groups based on their age and gender, and additionally, according to whether they self-identified as speeding excessively or rarely. This study aimed to elicit information about how drivers conceptualise speeding as well as the social and legal influences on driving speeds. The findings revealed a wide variety of reasons and circumstances that appear to be used as personal justifications for exceeding speed limits. Driver perceptions of speeding as personally and socially acceptable, as well as safe and necessary were common. Perceptions of an absence of danger associated with faster driving speeds were evident, particularly with respect to driving alone. An important distinction between the speed-based groups related to the attention given to the driving task. Rare speeders expressed strong beliefs about the need to be mindful of safety (self and others) while excessive speeders referred to the driving task as automatic, an absent-minded endeavour, and to speeding as a necessity in order to remain alert and reduce boredom. For many drivers in this study, compliance with speed limits was expressed as discretionary rather than mandatory. Social factors, such as peer and parental influence were widely discussed in Study 1 and perceptions of widespread community acceptance of speeding were noted. In some instances, the perception that ‘everybody speeds’ appeared to act as one rationale for the need to raise speed limits. Self-presentation, or wanting to project a positive image of self was noted, particularly with respect to concealing speeding infringements from others to protect one’s image as a trustworthy and safe driver. The influence of legal factors was also evident. Legal sanctions do not appear to influence all drivers to the same extent. For instance, fear of apprehension appeared to play a role in reducing speeding for many, although previous experiences of detection and legal sanctions seemed to have had limited influence on reducing speeding among some drivers. Disregard for sanctions (e.g., driving while suspended), fraudulent demerit point use, and other strategies to avoid detection and punishment were widely and openly discussed. In Study 2, 833 drivers were recruited from roadside service stations in metropolitan and regional locations in Queensland. A quantitative research strategy assessed the relative contribution of personal, social, and legal factors to recent and future self-reported speeding (i.e., frequency of speeding and intentions to speed in the future). Multivariate analyses examining a range of factors drawn from SLT revealed that factors including self-identity (i.e., identifying as someone who speeds), favourable definitions (attitudes) towards speeding, personal experiences of avoiding detection and punishment for speeding, and perceptions of family and friends as accepting of speeding were all significantly associated with greater self-reported speeding. Study 3 was an exploratory, qualitative investigation of psychosocial factors associated with speeding among 35 Chinese drivers who were recruited from the membership of a motoring organisation and a university in Beijing. Six focus groups were conducted to explore similar issues to those examined in Study 1. The findings of Study 3 revealed many similarities with respect to the themes that arose in Australia. For example, there were similarities regarding personal justifications for speeding, such as the perception that posted limits are unreasonably low, the belief that individual drivers are able to determine safe travel speeds according to personal comfort with driving fast, and the belief that drivers possess adequate skills to control a vehicle at high speed. Strategies to avoid detection and punishment were also noted, though they appeared more widespread in China and also appeared, in some cases, to involve the use of a third party, a topic that was not reported by Australian drivers. Additionally, higher perceived enforcement tolerance thresholds were discussed by Chinese participants. Overall, the findings indicated perceptions of a high degree of community acceptance of speeding and a perceived lack of risk associated with speeds that were well above posted speed limits. Study 4 extended the exploratory research phase in China with a quantitative investigation involving 299 car drivers recruited from car washes in Beijing. Results revealed a relatively inexperienced sample with less than 5 years driving experience, on average. One third of participants perceived that the certainty of penalties when apprehended was low and a similar proportion of Chinese participants reported having previously avoided legal penalties when apprehended for speeding. Approximately half of the sample reported that legal penalties for speeding were ‘minimally to not at all’ severe. Multivariate analyses revealed that past experiences of avoiding detection and punishment for speeding, as well as favourable attitudes towards speeding, and perceptions of strong community acceptance of speeding were most strongly associated with greater self-reported speeding in the Chinese sample. Overall, the results of this research make several important theoretical contributions to the road safety literature. Akers’ social learning theory was found to be robust across cultural contexts with respect to speeding; similar amounts of variance were explained in self-reported speeding in the quantitative studies conducted in Australia and China. Historically, SLT was devised as a theory of deviance and posits that deviance and conformity are learned in the same way, with the balance of influence stemming from the ways in which behaviour is rewarded and punished (Akers, 1998). This perspective suggests that those who speed and those who do not are influenced by the same mechanisms. The inclusion of drivers from both ends of the ‘speeding spectrum’ in Study 1 provided an opportunity to examine the wider utility of SLT across the full range of the behaviour. One may question the use of a theory of deviance to investigate speeding, a behaviour that could, arguably, be described as socially acceptable and prevalent. However, SLT seemed particularly relevant to investigating speeding because of its inclusion of association, imitation, and reinforcement variables which reflect the breadth of factors already found to be potentially influential on driving speeds. In addition, driving is a learned behaviour requiring observation, guidance, and practice. Thus, the reinforcement and imitation concepts are particularly relevant to this behaviour. Finally, current speed management practices are largely enforcement-based and rely on the principles of behavioural reinforcement captured within the reinforcement component of SLT. Thus, the application of SLT to a behaviour such as speeding offers promise in advancing our understanding of the factors that influence speeding, as well as extending our knowledge of the application of SLT. Moreover, SLT could act as a valuable theoretical framework with which to examine other illegal driving behaviours that may not necessarily be seen as deviant by the community (e.g., mobile phone use while driving). This research also made unique contributions to advancing our understanding of the key components and the overall structure of Akers’ social learning theory. The broader SLT literature is lacking in terms of a thorough structural understanding of the component parts of the theory. For instance, debate exists regarding the relevance of, and necessity for including broader social influences in the model as captured by differential association. In the current research, two alternative SLT models were specified and tested in order to better understand the nature and extent of the influence of differential association on behaviour. Importantly, the results indicated that differential association was able to make a unique contribution to explaining self-reported speeding, thereby negating the call to exclude it from the model. The results also demonstrated that imitation was a discrete theoretical concept that should also be retained in the model. The results suggest a need to further explore and specify mechanisms of social influence in the SLT model. In addition, a novel approach was used to operationalise SLT variables by including concepts drawn from contemporary social psychological and deterrence-based research to enhance and extend the way that SLT variables have traditionally been examined. Differential reinforcement was conceptualised according to behavioural reinforcement principles (i.e., positive and negative reinforcement and punishment) and incorporated concepts of affective beliefs, anticipated regret, and deterrence-related concepts. Although implicit in descriptions of SLT, little research has, to date, made use of the broad range of reinforcement principles to understand the factors that encourage or inhibit behaviour. This approach has particular significance to road user behaviours in general because of the deterrence-based nature of many road safety countermeasures. The concept of self-identity was also included in the model and was found to be consistent with the definitions component of SLT. A final theoretical contribution was the specification and testing of a full measurement model prior to model testing using structural equation modelling. This process is recommended in order to reduce measurement error by providing an examination of the psychometric properties of the data prior to full model testing. Despite calls for such work for a number of decades, the current work appears to be the only example of a full measurement model of SLT. There were also a number of important practical implications that emerged from this program of research. Firstly, perceptions regarding speed enforcement tolerance thresholds were highlighted as a salient influence on driving speeds in both countries. The issue of enforcement tolerance levels generated considerable discussion among drivers in both countries, with Australian drivers reporting lower perceived tolerance levels than Chinese drivers. It was clear that many drivers used the concept of an enforcement tolerance in determining their driving speed, primarily with the desire to drive faster than the posted speed limit, yet remaining within a speed range that would preclude apprehension by police. The quantitative results from Studies 2 and 4 added support to these qualitative findings. Together, the findings supported previous research and suggested that a travel speed may not be seen as illegal until that speed reaches a level over the prescribed enforcement tolerance threshold. In other words, the enforcement tolerance appears to act as a ‘de facto’ speed limit, replacing the posted limit in the minds of some drivers. The findings from the two studies conducted in China (Studies 2 and 4) further highlighted the link between perceived enforcement tolerances and a ‘de facto’ speed limit. Drivers openly discussed driving at speeds that were well above posted speed limits and some participants noted their preference for driving at speeds close to ‘50% above’ the posted limit. This preference appeared to be shaped by the perception that the same penalty would be imposed if apprehended, irrespective of what speed they travelling (at least up to 50% above the limit). Further research is required to determine whether the perceptions of Chinese drivers are mainly influenced by the Law of the People’s Republic of China or by operational practices. Together, the findings from both studies in China indicate that there may be scope to refine enforcement tolerance levels, as has happened in other jurisdictions internationally over time, in order to reduce speeding. Any attempts to do so would likely be assisted by the provision of information about the legitimacy and purpose of speed limits as well as risk factors associated with speeding because these issues were raised by Chinese participants in the qualitative research phase. Another important practical implication of this research for speed management in China is the way in which penalties are determined. Chinese drivers described perceptions of unfairness and a lack of transparency in the enforcement system because they were unsure of the penalty that they would receive if apprehended. Steps to enhance the perceived certainty and consistency of the system to promote a more equitable approach to detection and punishment would appear to be welcomed by the general driving public and would be more consistent with the intended theoretical (deterrence) basis that underpins the current speed enforcement approach. The use of mandatory, fixed penalties may assist in this regard. In many countries, speeding attracts penalties that are dependent on the severity of the offence. In China, there may be safety benefits gained from the introduction of a similar graduated scale of speeding penalties and fixed penalties might also help to address the issue of uncertainty about penalties and related perceptions of unfairness. Such advancements would be in keeping with the principles of best practice for speed management as identified by the World Health Organisation. Another practical implication relating to legal penalties, and applicable to both cultural contexts, relates to the issues of detection and punishment avoidance. These two concepts appeared to strongly influence speeding in the current samples. In Australia, detection avoidance strategies reported by participants generally involved activities that are not illegal (e.g., site learning and remaining watchful for police vehicles). The results from China were similar, although a greater range of strategies were reported. The most common strategy reported in both countries for avoiding detection when speeding was site learning, or familiarisation with speed camera locations. However, a range of illegal practices were also described by Chinese drivers (e.g., tampering with or removing vehicle registration plates so as to render the vehicle unidentifiable on camera and use of in-vehicle radar detectors). With regard to avoiding punishment when apprehended, a range of strategies were reported by drivers from both countries, although a greater range of strategies were reported by Chinese drivers. As the results of the current research indicated that detection avoidance was strongly associated with greater self-reported speeding in both samples, efforts to reduce avoidance opportunities are strongly recommended. The practice of randomly scheduling speed camera locations, as is current practice in Queensland, offers one way to minimise site learning. The findings of this research indicated that this practice should continue. However, they also indicated that additional strategies are needed to reduce opportunities to evade detection. The use of point-to-point speed detection (also known as sectio

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Since the 1960s, the value relevance of accounting information has been an important topic in accounting research. The value relevance research provides evidence as to whether accounting numbers relate to corporate value in a predicted manner (Beaver, 2002). Such research is not only important for investors but also provides useful insights into accounting reporting effectiveness for standard setters and other users. Both the quality of accounting standards used and the effectiveness associated with implementing these standards are fundamental prerequisites for high value relevance (Hellstrom, 2006). However, while the literature comprehensively documents the value relevance of accounting information in developed markets, little attention has been given to emerging markets where the quality of accounting standards and their enforcement are questionable. Moreover, there is currently no known research that explores the association between level of compliance with International Financial Reporting Standards (IFRS) and the value relevance of accounting information. Motivated by the lack of research on the value relevance of accounting information in emerging markets and the unique institutional setting in Kuwait, this study has three objectives. First, it investigates the extent of compliance with IFRS with respect to firms listed on the Kuwait Stock Exchange (KSE). Second, it examines the value relevance of accounting information produced by KSE-listed firms over the 1995 to 2006 period. The third objective links the first two and explores the association between the level of compliance with IFRS and the value relevance of accounting information to market participants. Since it is among the first countries to adopt IFRS, Kuwait provides an ideal setting in which to explore these objectives. In addition, the Kuwaiti accounting environment provides an interesting regulatory context in which each KSE-listed firm is required to appoint at least two external auditors from separate auditing firms. Based on the research objectives, five research questions (RQs) are addressed. RQ1 and RQ2 aim to determine the extent to which KSE-listed firms comply with IFRS and factors contributing to variations in compliance levels. These factors include firm attributes (firm age, leverage, size, profitability, liquidity), the number of brand name (Big-4) auditing firms auditing a firm’s financial statements, and industry categorization. RQ3 and RQ4 address the value relevance of IFRS-based financial statements to investors. RQ5 addresses whether the level of compliance with IFRS contributes to the value relevance of accounting information provided to investors. Based on the potential improvement in value relevance from adopting and complying with IFRS, it is predicted that the higher the level of compliance with IFRS, the greater the value relevance of book values and earnings. The research design of the study consists of two parts. First, in accordance with prior disclosure research, the level of compliance with mandatory IFRS is examined using a disclosure index. Second, the value relevance of financial statement information, specifically, earnings and book value, is examined empirically using two valuation models: price and returns models. The combined empirical evidence that results from the application of both models provides comprehensive insights into value relevance of accounting information in an emerging market setting. Consistent with expectations, the results show the average level of compliance with IFRS mandatory disclosures for all KSE-listed firms in 2006 was 72.6 percent; thus, indicating KSE-listed firms generally did not fully comply with all requirements. Significant variations in the extent of compliance are observed among firms and across accounting standards. As predicted, older, highly leveraged, larger, and profitable KSE-listed firms are more likely to comply with IFRS required disclosures. Interestingly, significant differences in the level of compliance are observed across the three possible auditor combinations of two Big-4, two non-Big 4, and mixed audit firm types. The results for the price and returns models provide evidence that earnings and book values are significant factors in the valuation of KSE-listed firms during the 1995 to 2006 period. However, the results show that the value relevance of earnings and book values decreased significantly during that period, suggesting that investors rely less on financial statements, possibly due to the increase in the available non-financial statement sources. Notwithstanding this decline, a significant association is observed between the level of compliance with IFRS and the value relevance of earnings and book value to KSE investors. The findings make several important contributions. First, they raise concerns about the effectiveness of the regulatory body that oversees compliance with IFRS in Kuwait. Second, they challenge the effectiveness of the two-auditor requirement in promoting compliance with regulations as well as the associated cost-benefit of this requirement for firms. Third, they provide the first known empirical evidence linking the level of IFRS compliance with the value relevance of financial statement information. Finally, the findings are relevant for standard setters and for their current review of KSE regulations. In particular, they highlight the importance of establishing and maintaining adequate monitoring and enforcement mechanisms to ensure compliance with accounting standards. In addition, the finding that stricter compliance with IFRS improves the value relevance of accounting information highlights the importance of full compliance with IFRS and not just mere adoption.

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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.