Using information criteria to select the correct variance–covariance structure for longitudinal data in ecology

1. Ecological data sets often use clustered measurements or use repeated sampling in a longitudinal design. Choosing the correct covariance structure is an important step in the analysis of such data, as the covariance describes the degree of similarity among the repeated observations. 2. Three methods for choosing the covariance are: the Akaike information criterion (AIC), the quasi-information criterion (QIC), and the deviance information criterion (DIC). We compared the methods using a simulation study and using a data set that explored effects of forest fragmentation on avian species richness over 15 years. 3. The overall success was 80.6% for the AIC, 29.4% for the QIC and 81.6% for the DIC. For the forest fragmentation study the AIC and DIC selected the unstructured covariance, whereas the QIC selected the simpler autoregressive covariance. Graphical diagnostics suggested that the unstructured covariance was probably correct. 4. We recommend using DIC for selecting the correct covariance structure.

HCX : an efficient hybrid clustering approach for XML documents

This paper proposes a novel Hybrid Clustering approach for XML documents (HCX) that first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. The empirical analysis reveals that the proposed method is scalable and accurate.

XCFS - a novel approach for clustering XML documents using both the structure and the content

XML document clustering is essential for many document handling applications such as information storage, retrieval, integration and transformation. An XML clustering algorithm should process both the structural and the content information of XML documents in order to improve the accuracy and meaning of the clustering solution. However, the inclusion of both kinds of information in the clustering process results in a huge overhead for the underlying clustering algorithm because of the high dimensionality of the data. This paper introduces a novel approach that first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. The proposed method reduces the high dimensionality of input data by using only the structure-constrained content. The empirical analysis reveals that the proposed method can effectively cluster even very large XML datasets and outperform other existing methods.

Determining the psychosocial predictors of living, living-related, and posthumous organ donation

The worldwide organ shortage occurs despite people’s positive organ donation attitudes. The discrepancy between attitudes and behaviour is evident in Australia particularly, with widespread public support for organ donation but low donation and communication rates. This problem is compounded further by the paucity of theoretically based research to improve our understanding of people’s organ donation decisions. This program of research contributes to our knowledge of individual decision making processes for three aspects of organ donation: (1) posthumous (upon death) donation, (2) living donation (to a known and unknown recipient), and (3) providing consent for donation by communicating donation wishes on an organ donor consent register (registering) and discussing the donation decision with significant others (discussing). The research program used extended versions of the Theory of Planned Behaviour (TPB) and the Prototype/Willingness Model (PWM), incorporating additional influences (moral norm, self-identity, organ recipient prototypes), to explicate the relationship between people’s positive attitudes and low rates of organ donation behaviours. Adopting the TPB and PWM (and their extensions) as a theoretical basis overcomes several key limitations of the extant organ donation literature including the often atheoretical nature of organ donation research, thefocus on individual difference factors to construct organ donor profiles and the omission of important psychosocial influences (e.g., control perceptions, moral values) that may impact on people’s decision-making in this context. In addition, the use of the TPB and PWM adds further to our understanding of the decision making process for communicating organ donation wishes. Specifically, the extent to which people’s registering and discussing decisions may be explained by a reasoned and/or a reactive decision making pathway is examined (Stage 3) with the novel application of the TPB augmented with the social reaction pathway in the PWM. This program of research was conducted in three discrete stages: a qualitative stage (Stage 1), a quantitative stage with extended models (Stage 2), and a quantitative stage with augmented models (Stage 3). The findings of the research program are reported in nine papers which are presented according to the three aspects of organ donation examined (posthumous donation, living donation, and providing consent for donation by registering or discussing the donation preference). Stage One of the research program comprised qualitative focus groups/interviews with university students and community members (N = 54) (Papers 1 and 2). Drawing broadly on the TPB framework (Paper 1), content analysed responses revealed people’s commonly held beliefs about the advantages and disadvantages (e.g., prolonging/saving life), important people or groups (e.g., family), and barriers and motivators (e.g., a family’s objection to donation), related to living and posthumous organ donation. Guided by a PWM perspective, Paper Two identified people’s commonly held perceptions of organ donors (e.g., altruistic and giving), non-donors (e.g., self-absorbed and unaware), and transplant recipients (e.g., unfortunate, and in some cases responsible/blameworthy for their predicament). Stage Two encompassed quantitative examinations of people’s decision makingfor living (Papers 3 and 4) and posthumous (Paper 5) organ donation, and for registering and discussing donation wishes (Papers 6 to 8) to test extensions to both the TPB and PWM. Comparisons of health students’ (N = 487) motivations and willingness for living related and anonymous donation (Paper 3) revealed that a person’s donor identity, attitude, past blood donation, and knowing a posthumous donor were four common determinants of willingness, with the results highlighting students’ identification as a living donor as an important motive. An extended PWM is presented in Papers Four and Five. University students’ (N = 284) willingness for living related and anonymous donation was tested in Paper Four with attitude, subjective norm, donor prototype similarity, and moral norm (but not donor prototype favourability) predicting students’ willingness to donate organs in both living situations. Students’ and community members’ (N = 471) posthumous organ donation willingness was assessed in Paper Five with attitude, subjective norm, past behaviour, moral norm, self-identity, and prior blood donation all significantly directly predicting posthumous donation willingness, with only an indirect role for organ donor prototype evaluations. The results of two studies examining people’s decisions to register and/or discuss their organ donation wishes are reported in Paper Six. People’s (N = 24) commonly held beliefs about communicating their organ donation wishes were explored initially in a TPB based qualitative elicitation study. The TPB belief determinants of intentions to register and discuss the donation preference were then assessed for people who had not previously communicated their donation wishes (N = 123). Behavioural and normative beliefs were important determinants of registering and discussing intentions; however, control beliefs influenced people’s registering intentions only. Paper Seven represented the first empirical test of the role of organ transplant recipient prototypes (i.e., perceptions of organ transplant recipients) in people’s (N = 465) decisions to register consent for organ donation. Two factors, Substance Use and Responsibility, were identified and Responsibility predicted people’s organ donor registration status. Results demonstrated that unregistered respondents were the most likely to evaluate transplant recipients negatively. Paper Eight established the role of organ donor prototype evaluations, within an extended TPB model, in predicting students’ and community members’ registering (n = 359) and discussing (n = 282) decisions. Results supported the utility of an extended TPB and suggested a role for donor prototype evaluations in predicting people’s discussing intentions only. Strong intentions to discuss donation wishes increased the likelihood that respondents reported discussing their decision 1-month later. Stage Three of the research program comprised an examination of augmented models (Paper 9). A test of the TPB augmented with elements from the social reaction pathway in the PWM, and extensions to these models was conducted to explore whether people’s registering (N = 339) and discussing (N = 315) decisions are explained via a reasoned (intention) and/or social reaction (willingness) pathway. Results suggested that people’s decisions to communicate their organ donation wishes may be better explained via the reasoned pathway, particularly for registering consent; however, discussing also involves reactive elements. Overall, the current research program represents an important step toward clarifying the relationship between people’s positive organ donation attitudes but low rates of organ donation and communication behaviours. Support has been demonstrated for the use of extensions to two complementary theories, the TPB and PWM, which can inform future research aiming to explicate further the organ donation attitude-behaviour relationship. The focus on a range of organ donation behaviours enables the identification of key targets for future interventions encouraging people’s posthumous and living donation decisions, and communication of their organ donation preference.

Tag based collaborative filtering for recommender systems

Collaborative tagging can help users organize, share and retrieve information in an easy and quick way. For the collaborative tagging information implies user’s important personal preference information, it can be used to recommend personalized items to users. This paper proposes a novel tag-based collaborative filtering approach for recommending personalized items to users of online communities that are equipped with tagging facilities. Based on the distinctive three dimensional relationships among users, tags and items, a new similarity measure method is proposed to generate the neighborhood of users with similar tagging behavior instead of similar implicit ratings. The promising experiment result shows that by using the tagging information the proposed approach outperforms the standard user and item based collaborative filtering approaches.

Collaborative filtering recommender systems using tag information

Recommender Systems is one of the effective tools to deal with information overload issue. Similar with the explicit rating and other implicit rating behaviours such as purchase behaviour, click streams, and browsing history etc., the tagging information implies user’s important personal interests and preferences information, which can be used to recommend personalized items to users. This paper is to explore how to utilize tagging information to do personalized recommendations. Based on the distinctive three dimensional relationships among users, tags and items, a new user profiling and similarity measure method is proposed. The experiments suggest that the proposed approach is better than the traditional collaborative filtering recommender systems using only rating data.

TraSe algorithm : automatic evolutionary morphing of electronic dance music

The TraSe (Transform-Select) algorithm has been developed to investigate the morphing of electronic music through automatically applying a series of deterministic compositional transformations to the source, guided towards a target by similarity metrics. This is in contrast to other morphing techniques such as interpolation or parameters or probabilistic variation. TraSe allows control over stylistic elements of the music through user-defined weighting of numerous compositional transformations. The formal evaluation of TraSe was mostly qualitative and occurred through nine participants completing an online questionnaire. The music generated by TraSe was generally felt to be less coherent than a human composed benchmark but in some cases judged as more creative.

Analyzing web multimedia query reformulation behavior

Current multimedia Web search engines still use keywords as the primary means to search. Due to the richness in multimedia contents, general users constantly experience some difficulties in formulating textual queries that are representative enough for their needs. As a result, query reformulation becomes part of an inevitable process in most multimedia searches. Previous Web query formulation studies did not investigate the modification sequences and thus can only report limited findings on the reformulation behavior. In this study, we propose an automatic approach to examine multimedia query reformulation using large-scale transaction logs. The key findings show that search term replacement is the most dominant type of modifications in visual searches but less important in audio searches. Image search users prefer the specified search strategy more than video and audio users. There is also a clear tendency to replace terms with synonyms or associated terms in visual queries. The analysis of the search strategies in different types of multimedia searching provides some insights into user’s searching behavior, which can contribute to the design of future query formulation assistance for keyword-based Web multimedia retrieval systems.

A study and comparison of multimedia Web searching : 1997-2006

Searching for multimedia is an important activity for users of Web search engines. Studying user's interactions with Web search engine multimedia buttons, including image, audio, and video, is important for the development of multimedia Web search systems. This article provides results from a Weblog analysis study of multimedia Web searching by Dogpile users in 2006. The study analyzes the (a) duration, size, and structure of Web search queries and sessions; (b) user demographics; (c) most popular multimedia Web searching terms; and (d) use of advanced Web search techniques including Boolean and natural language. The current study findings are compared with results from previous multimedia Web searching studies. The key findings are: (a) Since 1997, image search consistently is the dominant media type searched followed by audio and video; (b) multimedia search duration is still short (>50% of searching episodes are <1 min), using few search terms; (c) many multimedia searches are for information about people, especially in audio search; and (d) multimedia search has begun to shift from entertainment to other categories such as medical, sports, and technology (based on the most repeated terms). Implications for design of Web multimedia search engines are discussed.

Identification of factors predicting clickthrough in Web searching using neural network analysis

In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

On importer trust and commitment : a comparative study of two developing countries

Purpose: Relationship trust and commitment are two key dimensions of international exchanges. Both have been extensively investigated from an exporter (as opposed to importer) perspective in developed country (as opposed to developing country) contexts. To address these gaps, this study aims to develop a model of antecedents and outcomes of importer trust and commitment in two developing countries.---------- Design/methodology: The authors test the proposed model using data from Chile and Bangladesh. Hypotheses were tested using structural equation modeling (SEM).---------- Findings: SEM analysis revealed that most of the hypotheses were supported in both the Bangladeshi and Chilean context. The findings of this study also suggest that the effects of importer transaction-specific investments on importer commitment are distinct in the Bangladeshi context. Practical implications: Practically, these results show that trust and commitment are essential for enhancing importer relationship performance in developing countries. Importer trust in a foreign supplier is effective when suppliers are competent and provide relatively superior facilities, as opposed to opportunistic proclivity. Importer commitment to a foreign supplier is stronger when importers perceive that the foreign supplier is not opportunistic, but is knowledgeable and experienced with the importer market, and they perceive that it is an advantage importing from that supplier. Cultural similarity between importers and foreign suppliers improves importer trust in both countries. However, importer commitment in Chile increases with importer transaction-specific investment, but this is not found to be the case in Bangladesh.---------- Originality/value: This study contributes to the importer-exporter exchange relationship literature by testing a model of antecedents and outcomes of importer trust and commitment. The tested model is one of few that considers developing country contexts and incorporates two novel antecedents of trust and commitment: importer knowledge and experience, and supplier resource competency.

Are organ donation communication decisions reasoned or reactive? A test of the utility of an augmented Theory of Planned Behaviour with the Prototype/Willingness Model

Objectives: To explore whether people's organ donation consent decisions occur via a reasoned and/or social reaction pathway. --------- Design: We examined prospectively students' and community members' decisions to register consent on a donor register and discuss organ donation wishes with family. --------- Method: Participants completed items assessing theory of planned behaviour (TPB; attitude, subjective norm, perceived behavioural control (PBC)), prototype/willingness model (PWM; donor prototype favourability/similarity, past behaviour), and proposed additional influences (moral norm, self-identity, recipient prototypes) for registering (N=339) and discussing (N=315) intentions/willingness. Participants self-reported their registering (N=177) and discussing (N=166) behaviour 1 month later. The utility of the (1) TPB, (2) PWM, (3) augmented TPB with PWM, and (4) augmented TPB with PWM and extensions was tested using structural equation modelling for registering and discussing intentions/willingness, and logistic regression for behaviour. --------- Results: While the TPB proved a more parsimonious model, fit indices suggested that the other proposed models offered viable options, explaining greater variance in communication intentions/willingness. The TPB, augmented TPB with PWM, and extended augmented TPB with PWM best explained registering and discussing decisions. The proposed and revised PWM also proved an adequate fit for discussing decisions. Respondents with stronger intentions (and PBC for registering) had a higher likelihood of registering and discussing. --------- Conclusions: People's decisions to communicate donation wishes may be better explained via a reasoned pathway (especially for registering); however, discussing involves more reactive elements. The role of moral norm, self-identity, and prototypes as influences predicting communication decisions were highlighted also.