Physical Sciences and Mathematics Commons^™

Prognostic And Predictive Value Of Β-Blockers In The Eortc 1325/Keynote-054 Phase Iii Trial Of Pembrolizumab Versus Placebo In Resected High-Risk Stage Iii Melanoma, Oliver J. Kennedy, Michal Kicinski, Sara Valpione, Sara Gandini, Stefan Suciu, Christian U. Blank, Georgina V. Long, Victoria G. Atkinson, Stéphane Dalle, Andrew M. Haydon, Andrey Meshcheryakov, Adnan Khattak, Matteo S. Carlino, Shahneen Sandhu, James Larkin, Susana Puig, Paolo A. Ascierto, Piotr Rutkowski, Dirk Schadendorf, Rutger Koornstra, Leonel Hernandez-Aya, Anna M. Di Giacomo, Alfonsus J.M. Van Den Eertwegh, Jean Jacques Grob, Ralf Gutzmer, Rahima Jamal, Alexander C.J. Van Akkooi, Caroline Robert, Alexander M. M. Eggermont, Paul Lorigan, Mario Mandala

Research outputs 2022 to 2026

Background:

β-adrenergic receptors are upregulated in melanoma cells and contribute to an immunosuppressive, pro-tumorigenic microenvironment. This study investigated the prognostic and predictive value of β-adrenoreceptor blockade by β-blockers in the EORTC1325/KEYNOTE-054 randomised controlled trial.

Methods:

Patients with resected stage IIIA, IIIB or IIIC melanoma and regional lymphadenectomy received 200 mg of adjuvant pembrolizumab (n = 514) or placebo (n = 505) every three weeks for one year or until recurrence or unacceptable toxicity. At a median follow-up of 3 years, pembrolizumab prolonged recurrence-free survival (RFS) compared to placebo (hazard ratio (HR) 0.56, 95% confidence interval (CI) 0.47–0.68). β-blocker use was …

High Definition Tdcs Effect On Postural Control In Healthy Individuals: Entropy Analysis Of A Crossover Clinical Trial, Diandra B. Favoretto, Eduardo Bergonzoni, Diego Carvalho Nascimento, Francisco Louzada, Tenysson W. Lemos, Rosangela A. Batistela, Renato Moraes, João P. Leite, Brunna P. Rimoli, Dylan J. Edwards, Taiza G.S. Edwards

Research outputs 2022 to 2026

Objective: Converging evidence supporting an effect of transcranial direct current stimulation (tDCS) on postural control and human verticality perception highlights this strategy as promising for post-stroke rehabilitation. We have previously demonstrated polarity-dependent effects of high-definition tDCS (HD-tDCS) on weight-bearing asymmetry. However, there is no investigation regarding the time-course of effects on postural control induced by HD-tDCS protocols. Thus, we performed a nonlinear time series analysis focusing on the entropy of the ground reaction force as a secondary investigation of our randomized, double-blind, placebo-controlled, crossover clinical trial. Materials and Methods: Twenty healthy right-handed young adults received the following conditions (random order, …

Adverse Events Reporting Of Clinical Trials In Exercise Oncology Research (Advance): Protocol For A Scoping Review, Hao Luo, Oliver Schumacher, Daniel A. Galvão, Robert U. Newton, Dennis R. Taaffe

Research outputs 2022 to 2026

Introduction: Adequate, transparent, and consistent reporting of adverse events (AEs) in exercise oncology trials is critical to assess the safety of exercise interventions for people following a cancer diagnosis. However, there is little understanding of how AEs are reported in exercise oncology trials. Thus, we propose to conduct a scoping review to summarise and evaluate current practice of reporting of AEs in published exercise oncology trials with further exploration of factors associated with inadequate reporting of AEs. The study findings will serve to inform the need for future research on standardisation of the definition, collection, and reporting of AEs for …

Ecu-Ioft: A Dataset For Analysing Cyber-Attacks On Internet Of Flying Things, Mohiuddin Ahmed, David Cox, Benjamin Simpson, Aseel Aloufi

Research outputs 2022 to 2026

There has been a significant increase in the adoption of unmanned aerial vehicles (UAV) within science, technology, engineering, and mathematics project-based learning. However, the risks that education providers place their student and staff under is often unknown or undocumented. Low-end consumer drones used within the education sector are vulnerable to state-of-the-art cyberattacks. Therefore, datasets are required to conduct further research to establish cyber defenses for UAVs used within the education sector. This paper showcases the development of the ECU-IoFT dataset, documenting three known cyber-attacks targeting Wi-Fi communications and the lack of security in an affordable off-the-shelf drone. At present, there …

Modeling Digital Camera Monitoring Count Data With Intermittent Zeros For Short-Term Prediction, Eben Afrifa-Yamoah, Ute Mueller

Research outputs 2022 to 2026

Digital camera monitoring has revolutionised survey designs in many fields, as an important source of information. The extended sampling coverage offered by this monitoring scheme makes it preferable compared to other traditional methods of survey. However, data obtained from digital camera monitoring are often highly variable, and characterized by sparse periods of zero counts, interspersed with missing observations due to outages. In practice, missing data of relatively shorter duration are mostly observed and are often imputed using interpolation techniques, ignoring long-term trends leading to inherent estimation biases. In this study, we investigated time series forecasting methods that adequately handle intermittency …

Commodity Futures Returns And Policy Uncertainty, Deepa Bannigidadmath, Paresh Kumar Narayan

Research outputs 2014 to 2021

© 2020 Elsevier Inc. This paper investigates whether economic policy uncertainty is predictable using three sets of commodity futures market variables, namely the equal-weighted average of futures excess returns, the excess returns on a portfolio of going long in backwardated commodities, and the excess returns on a portfolio of going short in contango commodities as predictors. We find significant evidence of both in-sample and out-of-sample predictability. Combination forecasts also reveal strong evidence of predictability. Our findings remain unchanged following several robustness tests.

Financial News And Cds Spreads, Paresh Kumar Narayan, Deepa Bannigidadmath

Research outputs 2014 to 2021

© 2020 Elsevier B.V. This paper examines whether financial news moves CDS spreads for a large number of U.S. stocks sorted into 19 panels consisting of sectors, sizes and credit quality. Using a unique financial news data set, we discover that while both positive and negative news predicts CDS spread changes in most of the panels, annualised mean–variance profits and utility gains are dominated by forecasting models that use positive news as a predictor. At best, risk factors only account for around 31% of observed profits.

Imputation, Modelling And Optimal Sampling Design For Digital Camera Data In Recreational Fisheries Monitoring, Ebenezer Afrifa-Yamoah

Theses: Doctorates and Masters

Digital camera monitoring has evolved as an active application-oriented scheme to help address questions in areas such as fisheries, ecology, computer vision, artificial intelligence, and criminology. In recreational fisheries research, digital camera monitoring has become a viable option for probability-based survey methods, and is also used for corroborative and validation purposes. In comparison to onsite surveys (e.g. boat ramp surveys), digital cameras provide a cost-effective method of monitoring boating activity and fishing effort, including night-time fishing activities. However, there are challenges in the use of digital camera monitoring that need to be resolved. Notably, missing data problems and the cost …

Imputation Of Missing Data From Time-Lapse Cameras Used In Recreational Fishing Surveys, Ebenezer Afrifa-Yamoah, Stephen M. Taylor, Aiden Fisher, Ute Mueller

Research outputs 2014 to 2021

While remote camera surveys have the potential to improve the accuracy of recreational fishing estimates, missing data are common and require robust analytical techniques to impute. Time-lapse cameras are being used in Western Australia to monitor recreational boating activities, but outages have occurred. Generalized linear mixed effect models formulated in a fully conditional specification multiple imputation framework were used to reconstruct missing data, with climatic and some temporal classifications as covariates. Using a complete 12-month camera record of hourly counts of recreational powerboat retrievals, data were simulated based on ten observed camera outage patterns, with a missing proportion of between …

Contemporary Epidemiology Of Rising Atrial Septal Defect Trends Across Usa 1991–2016: A Combined Ecological Geospatiotemporal And Causal Inferential Study, Albert Stuart Reece, Gary Kenneth Hulse

Research outputs 2014 to 2021

© 2020, The Author(s). Background: Cardiovascular anomalies are the largest group of congenital anomalies and the major cause of death in young children, with various data linking rising atrial septal defect incidence (ASDI) with prenatal cannabis exposure. Objectives / Hypotheses. Is cannabis associated with ASDI in USA? Is this relationship causal? Methods: Geospatiotemporal cohort study, 1991–2016. Census populations of adults, babies, congenital anomalies, income and ethnicity. Drug exposure data on cigarettes, alcohol abuse, past month cannabis use, analgesia abuse and cocaine taken from National Survey of Drug Use and Health (78.9% response rate). Cannabinoid concentrations from Drug Enforcement Agency. Inverse …

Netnographic Slog: Creative Elicitation Strategies To Encourage Participation In An Online Community Of Practice For Early Education And Care, Ruth Wallace

Research outputs 2014 to 2021

Active, participatory netnography, in contrast to passive netnography, is essential if researchers are to gain rich rewards from the rigorous collection of qualitative data. However, researchers should be aware of the ‘netnographic slog’; “the blood, sweat and tears” associated with eliciting quality data and encouraging active participation in online communities.

This article examines the – Supporting Nutrition for Australian Childcare (SNAC) – online community of practice, established to support healthy eating practices in early childhood education and care settings. To ensure research rigour, Kozinets’ netnographic steps were employed. Garnering member participation in this online community was a slog; most community …

Compositions, Logratios And Geostatistics: An Application To Iron Ore, Clint Ward

Theses: Doctorates and Masters

Common implementations of geostatistical methods, kriging and simulation, ignore the fact that geochemical data are usually reported in weight percent, sum to a constant, and are thus compositional in nature. The constant sum implies that rescaling has occurred and this can be shown to produce spurious correlations. Compositional geostatistics is an approach developed to ensure that the constant sum constraint is respected in estimation while removing dependencies on the spurious correlations. This study tests the applicability of this method against the commonly implemented ordinary cokriging method. The sample data are production blast cuttings analyses drawn from a producing iron ore …

Hierarchical Graphical Bayesian Models In Psychology, Guillermo Campitelli, Guillermo Macbeth

Research outputs 2014 to 2021

The improvement of graphical methods in psychological research can promote their use and a better comprehension of their expressive power. The application of hierarchical Bayesian graphical models has recently become more frequent in psychological research. The aim of this contribution is to introduce suggestions for the improvement of hierarchical Bayesian graphical models in psychology. This novel set of suggestions stems from the description and comparison between two main approaches concerned with the use of plate notation and distribution pictograms. It is concluded that the combination of relevant aspects of both models might improve the use of powerful hierarchical Bayesian graphical …

Modelling And Analysis On Noisy Financial Time Series, Jinsong Leng

Research outputs 2014 to 2021

Building the prediction model(s) from the historical time series has attracted many researchers in last few decades. For example, the traders of hedge funds and experts in agriculture are demanding the precise models to make the prediction of the possible trends and cycles. Even though many statistical or machine learning (ML) models have been proposed, however, there are no universal solutions available to resolve such particular prob-lem. In this paper, the powerful forward-backward non-linear filter and wavelet-based denoising method are introduced to remove the high level of noise embedded in financial time series. With the filtered time series, the statistical …

Troubleshooting With Surveys, Sandra Pereira

ECU Research Week

This presentation discusses ways to identify and avoid the problems commonly encountered in draft surveys.

Impact Of Higher Education Workplace Relations Requirements On Nteu Membership Density, Tulsi Laxman Panchani

Theses : Honours

The National Tertiary Education Union (NTEU) is the only union working entirely in tertiary education around Australia. The union has over twenty four thousand members comprising of academic and general staff. NTEU maintains membership records at three levels, national, state and branch. The information collected includes gender, age group, employment type and work classification. In late April 2005, Higher Education Workplace Relations Requirements (HEWRRs) legislation was introduced by the Australian government. This legislation imposed restrictions on the interaction between the universities and the union and also curtailed an automatic involvement of the union in the resolution of workplace issues. The …

Comparison And Application Of Three Decorrelation Methods Pca, Maf And Acdc, Jacqueline Ferreira

Theses : Honours

Geostatistics is a branch of applied mathematics that deals with spatially correlated data. Analysing and modelling spatially correlated data can be difficult and time consuming, especially for a multivariate data set. One of the techniques used to make analysis and modelling easier involves decorrelation, whereby a linear transformation on the sample variables is used to associate the spatially correlated variables with a set of decorrelated factors which are statistically and spatially independent. PCA was one of the first multivariate techniques and is mostly used as a data reduction technique. A popular alternative decorrelation technique often used in the mining industry …

A Semiparametric Approach To A Nonlinear Acd Model, Pipat Wongsaart, Jiti Gao, David E. Allen

Research outputs pre 2011

We introduce in this paper a new semiparametric approach to a nonlinear ACD model, namely the Semiparametric ACD (SEMI-ACD) model. This new model is more flexible in the sense that the data are allowed to speak for themselves, without a hypothetical assumption being imposed arbitrarily on its key component. Moreover, it enables a much more thorough examination of the intertemporal importance of the conditional duration on the ACD process. Our experimental analysis suggests that the new model possesses a sound asymptotic character, while its performance is also robust across data generating processes and assumptions about the conditional distribution of the …

Fitting Weibull Acd Models To High Frequency Transactions Data : A Semi-Parametric Approach Based On Estimating Functions, Kok Haur Ng, David E. Allen, Shelton Peiris

Research outputs pre 2011

Autoregressive conditional duration (ACD) models play an important role in financial modeling. This paper considers the estimation of the Weibull ACD model using a semiparametric approach based on the theory of estimating functions (EF). We apply the EF and the maximum likelihood (ML) methods to a data set given in Tsay (2003, p203) to compare these two methods. It is shown that the EF approach is easier to apply in practice and gives better estimates than the MLE. Results show that the EF approach is compatible with the ML method in parameter estimation. Furthermore, the computation speed for the EF …

Using Decision Analytic Modelling To Simulate Pregnancy, Jeffrey Cannon

Theses : Honours

Decision analytic modelling enables decision makers to assess the cost-effectiveness associated with a proposed change in a cunent system without physically implementing the changes. This can be achieved by formulating a mathematical model that represents all the major events occuning in the system through fmmulas and algorithms, and estimating the likely outcomes along with their costs. This type of modelling has been identified by the State Health Research Advisory Council (SHRAC) of the Western Australian Depmiment of Health as an asset for the plmming of health care investments in the future. One such area in which the Western Australian Department …

Realized Volatility Uncertainty, David E. Allen, Michael Mcaleer, Marcel Scharth

Research outputs pre 2011

The presence of high and time-varying volatility of volatility and leverage effects bring additional uncertainty in the tails of the distribution of asset returns, even though returns standardized by (ex-post) quadratic variation measures are nearly gaussian. We argue that in this setting modeling shocks to volatility is more relevant for applications than extracting more precise predictions of the variable, as point forecasts differences are swamped by the size of the volatility of volatility and rendered less informative by the nongaussianity in the ex-ante distribution of returns. Using S&P 500 data, we document that this volatility of volatility is subject to …

The Third Generation Acd Model : A Semiparametric Approach, Pipat Wongsaart, Jiti Gao, David E. Allen

Research outputs pre 2011

Having concluded that thus far the question about the most appropriate type of nonlinear ACD model has not been satisfactorily answered, we intend to develop a novel ACD modelling methodology based on an iterative estimation algorithm and a semiparametric autoregressive process that not only allows the data to speak for itself, but also is robust across datasets without relying on some computational factors, such as the hypothesis about the probability density function of the standardised durations. We propose in this paper the Semiparametric ACD (SP-ACD) model, which can be considered a starting point of such a development. To address the …

The Extent Of Interaction Between The Scallop And Prawn Fleets In The Shark Bay Scallop Managed Fishery, John Dickson

Theses : Honours

The Shark Bay Managed Scallop Fishery is Western Australia's most important scallop fishery with an annual value of between $2 and $58 million. In addition to this the fishery is an important source of regional employment with approximately 160 skippers and crew employed during the 2005 season. Two separate fleets are permitted to fish for scallops in this fishery, the first consisting of dedicated scallop fishing vessels (Class A licences) and the second of prawn fishing vessels (Class B licences) that are allowed to take scallops under a catch sharing arrangement. Concerns exist over the interactions between these two fleets …

Analysis And Applications Of Autoregressive Moving Average Models With Stochastic Variance, Shelton Peiris, Ramprasad Bhar, David E. Allen

Research outputs pre 2011

It is known that volatility plays a central role in financial modelling problems. This paper studies, in detail, a class of discrete time stochastic volatility (SV) models driven by ARMA models with innovations having a stochastic variances. The auto- correlation function of this class of models is derived and methods of identification of such processes are described. An example is added to illustrate the development of the theory over the standard methods.

Methods For The Estimation Of Missing Values In Time Series, David S. Fung

Theses: Doctorates and Masters

Time Series is a sequential set of data measured over time. Examples of time series arise in a variety of areas, ranging from engineering to economics. The analysis of time series data constitutes an important area of statistics. Since, the data are records taken through time, missing observations in time series data are very common. This occurs because an observation may not be made at a particular time owing to faulty equipment, lost records, or a mistake, which cannot be rectified until later. When one or more observations are missing it may be necessary to estimate the model and also …

Forecasting The Equity Premium In The Australian Market, David E. Allen, Lurion Demello

Research outputs pre 2011

This paper provides a forecasting methodology for estimating the market risk premium in Australia. We employ an in-sample and out-of-sample forecast estimate using various dividend yield measures. The lagged dividend yield model is used to predict future equity premia on a data series that includes the top 85 percent of the Australian stock market. An important concern in this paper is the accuracy of dividend yield in forecasting the equity premium in the Australian market. We find that the level of predictability in the later part of the series is very weak compared to in-sample prediction during the 70s and …

Applications Of Recursive Estimation Methods In Statistical Process Control, Shelton Peiris, Aerambamoorthy Thavaneswaran, David E. Allen, R. Mellor

Research outputs pre 2011

In recent years there has been a growing interest in recursive estimation techniques as applied to statistical process control (SPC). In cases where prior information about the processes are available, it is shown that procedures based on the “optimal” smoothing can be superior to the classical procedures like Shewhart’s CUSUM control charts (see, for instance, Thavaneswaran, McPherson and Abraham (1998)). This paper reviews the recursive algorithms based on EWMA (exponentially weighted moving average), DLM (dynamic linear modeling), KF (Kalman filtering) and OS (optimal smoothing) in statistical process control with correlated data. We also discuss various relationships among the asymptotic mean …

Some Evidence On The Information Content Of Undisclosed Limit Orders On The Asx, M. Aitken, David E. Allen, Wenling J. Yang

Research outputs pre 2011

This paper is concerned with investigating the information content of undisclosed limit orders, and identifying factors that affect their size, plus the examination of the brokers’ behaviour in using undisclosed orders. We adopt a sample of liquid stocks listed on the ASX, and our estimation results indicate that the size of undisclosed orders are affected by a number of factors. Given the ‘stealth trading’ pattern of behaviour observed in large disclosed orders, this paper provides evidence to support a similar pattern of behaviour in the case of undisclosed orders. Our model also provides an appropriate measure for estimating the size …

Effects Of Bank Funds Management Activities On The Disintermediation Of Bank Deposits, David E. Allen, Jerry T. Parwada

Research outputs pre 2011

This study investigates the alleged disintermediation of banks’ traditional deposit-taking in favour of investment management activities. Using data on Australian bank-affiliated funds and a nine-year record of the parent banks’ liability balances, this study finds that managed funds do not displace bank liabilities. Prudential capital adequacy requirements dissuade banks from using in-house managed investments as indirect conduits for raising funds in the same manner as deposit-taking.

Generalized Moving Average Models And Applications In High Frequency Data, Shelton Peiris, David E. Allen, Aerambamoorthy Thavaneswaran

Research outputs pre 2011

This paper considers a new class of first order moving average type time series model with index δ (> 0) to describe some hidden features of a time series. It is shown that this class of models provides a valid, simple solution to a new direction of time series modelling. In particular, for suitably chosen parameters (coefficient β and index δ) this type of models could be used to describe data with low or high frequency components. Various new results associated with this class are given in a general form. A simulation study is carried out to justify the theory. …