Marketing charitable bequests to lawyers

There is scant literature about the role of the lawyer in influencing the likelihood of a charitable bequest being made in a will. Charities regularly advertise in legal journals and supply bequest materials to lawyers, but the effectiveness of these strategies for influencing lawyers appears not to have been measured in the literature or in practice. Our exploratory research indicates that specialist estate lawyers report that they pay little or no attention to traditional marketing of charitable bequests to them and that lawyers’ specific information needs from charities about bequests are not being satisfied appropriately. Our study reveals that lawyers do seek information from charities in order to write a will’s bequest clause, once a bequest has been considered by the client. Lawyers indicated frustration with obtaining this information from charities, and we recommend some actions for charities to rectify this situation. Recommendations for enhanced bequest solicitation are made together with suggestions for pathways for future bequest research involving lawyers.

Perceptions of data quality dimensions and data roles

Several authors stress the importance of data’s crucial foundation for operational, tactical and strategic decisions (e.g., Redman 1998, Tee et al. 2007). Data provides the basis for decision making as data collection and processing is typically associated with reducing uncertainty in order to make more effective decisions (Daft and Lengel 1986). While the first series of investments of Information Systems/Information Technology (IS/IT) into organizations improved data collection, restricted computational capacity and limited processing power created challenges (Simon 1960). Fifty years on, capacity and processing problems are increasingly less relevant; in fact, the opposite exists. Determining data relevance and usefulness is complicated by increased data capture and storage capacity, as well as continual improvements in information processing capability. As the IT landscape changes, businesses are inundated with ever-increasing volumes of data from both internal and external sources available on both an ad-hoc and real-time basis. More data, however, does not necessarily translate into more effective and efficient organizations, nor does it increase the likelihood of better or timelier decisions. This raises questions about what data managers require to assist their decision making processes.

Gaussian process models for sensor-centric robot localisation

This paper presents an approach to building an observation likelihood function from a set of sparse, noisy training observations taken from known locations by a sensor with no obvious geometric model. The basic approach is to fit an interpolant to the training data, representing the expected observation, and to assume additive sensor noise. This paper takes a Bayesian view of the problem, maintaining a posterior over interpolants rather than simply the maximum-likelihood interpolant, giving a measure of uncertainty in the map at any point. This is done using a Gaussian process framework. To validate the approach experimentally, a model of an environment is built using observations from an omni-directional camera. After a model has been built from the training data, a particle filter is used to localise while traversing this environment

Understanding evaluation of learning support in mathematics and statistics

With rapid and continuing growth of learning support initiatives in mathematics and statistics found in many parts of the world, and with the likelihood that this trend will continue, there is a need to ensure that robust and coherent measures are in place to evaluate the effectiveness of these initiatives. The nature of learning support brings challenges for measurement and analysis of its effects. After briefly reviewing the purpose, rationale for, and extent of current provision, this article provides a framework for those working in learning support to think about how their efforts can be evaluated. It provides references and specific examples of how workers in this field are collecting, analysing and reporting their findings. The framework is used to structure evaluation in terms of usage of facilities, resources and services provided, and also in terms of improvements in performance of the students and staff who engage with them. Very recent developments have started to address the effects of learning support on the development of deeper approaches to learning, the affective domain and the development of communities of practice of both learners and teachers. This article intends to be a stimulus to those who work in mathematics and statistics support to gather even richer, more valuable, forms of data. It provides a 'toolkit' for those interested in evaluation of learning support and closes by referring to an on-line resource being developed to archive the growing body of evidence. © 2011 Taylor & Francis.

Exploring Indigenous social attitudes and priorities in Australia

Given significant government attention to, and expenditure on, Indigenous equity in Australia, this article addresses a core problem: the lack of a sound understanding of Indigenous social attitudes and priorities. An account of cultural theory raises the likelihood of difference in outlook between Indigenous and non-Indigenous people, including those making and implementing policy. Yet, years of scholarly research and official statistical collections have overlooked potentially critical aspects of Indigineity. Suggestions of difference emerge from reference to the 2007 Australian Survey of Social Attitudes (AuSSA). If the attitudes recorded a small sample in this instrument manifest in the Indigenous population at large, policy priorities and directions should be reviewed and possibly revised. Despite inherent methodological difficulties, the article calls for targeted social attitude research among Australia's Indigenous peoples so that future policy can be better oriented and calibrated. The national benefits would outweigh the costs via better directed policy making.

Variational Bayes and the reduced dependence approximation for the autologistic model on an irregular grid with applications

Discrete Markov random field models provide a natural framework for representing images or spatial datasets. They model the spatial association present while providing a convenient Markovian dependency structure and strong edge-preservation properties. However, parameter estimation for discrete Markov random field models is difficult due to the complex form of the associated normalizing constant for the likelihood function. For large lattices, the reduced dependence approximation to the normalizing constant is based on the concept of performing computationally efficient and feasible forward recursions on smaller sublattices which are then suitably combined to estimate the constant for the whole lattice. We present an efficient computational extension of the forward recursion approach for the autologistic model to lattices that have an irregularly shaped boundary and which may contain regions with no data; these lattices are typical in applications. Consequently, we also extend the reduced dependence approximation to these scenarios enabling us to implement a practical and efficient non-simulation based approach for spatial data analysis within the variational Bayesian framework. The methodology is illustrated through application to simulated data and example images. The supplemental materials include our C++ source code for computing the approximate normalizing constant and simulation studies.

A comparison of the psychological, social, and legal factors contributing to speeding and drink driving behaviour

Within Australia, motor vehicle injury is the leading cause of hospital admissions and fatalities. Road crash data reveals that among the factors contributing to crashes in Queensland, speed and alcohol continue to be overrepresented. While alcohol is the number one contributing factor to fatal crashes, speeding also contributes to a high proportion of crashes. Research indicates that risky driving is an important contributor to road crashes. However, it has been debated whether all risky driving behaviours are similar enough to be explained by the same combination of factors. Further, road safety authorities have traditionally relied upon deterrence based countermeasures to reduce the incidence of illegal driving behaviours such as speeding and drink driving. However, more recent research has focussed on social factors to explain illegal driving behaviours. The purpose of this research was to examine and compare the psychological, legal, and social factors contributing to two illegal driving behaviours: exceeding the posted speed limit and driving when over the legal blood alcohol concentration (BAC) for the drivers licence type. Complementary theoretical perspectives were chosen to comprehensively examine these two behaviours including Akers’ social learning theory, Stafford and Warr’s expanded deterrence theory, and personality perspectives encompassing alcohol misuse, sensation seeking, and Type-A behaviour pattern. The program of research consisted of two phases: a preliminary pilot study, and the main quantitative phase. The preliminary pilot study was undertaken to inform the development of the quantitative study and to ensure the clarity of the theoretical constructs operationalised in this research. Semi-structured interviews were conducted with 11 Queensland drivers recruited from Queensland Transport Licensing Centres and Queensland University of Technology (QUT). These interviews demonstrated that the majority of participants had engaged in at least one of the behaviours, or knew of someone who had. It was also found among these drivers that the social environment in which both behaviours operated, including family and friends, and the social rewards and punishments associated with the behaviours, are important in their decision making. The main quantitative phase of the research involved a cross-sectional survey of 547 Queensland licensed drivers. The aim of this study was to determine the relationship between speeding and drink driving and whether there were any similarities or differences in the factors that contribute to a driver’s decision to engage in one or the other. A comparison of the participants self-reported speeding and self-reported drink driving behaviour demonstrated that there was a weak positive association between these two behaviours. Further, participants reported engaging in more frequent speeding at both low (i.e., up to 10 kilometres per hour) and high (i.e., 10 kilometres per hour or more) levels, than engaging in drink driving behaviour. It was noted that those who indicated they drove when they may be over the legal limit for their licence type, more frequently exceeded the posted speed limit by 10 kilometres per hour or more than those who complied with the regulatory limits for drink driving. A series of regression analyses were conducted to investigate the factors that predict self-reported speeding, self-reported drink driving, and the preparedness to engage in both behaviours. In relation to self-reported speeding (n = 465), it was found that among the sociodemographic and person-related factors, younger drivers and those who score high on measures of sensation seeking were more likely to report exceeding the posted speed limit. In addition, among the legal and psychosocial factors it was observed that direct exposure to punishment (i.e., being detected by police), direct punishment avoidance (i.e., engaging in an illegal driving behaviour and not being detected by police), personal definitions (i.e., personal orientation or attitudes toward the behaviour), both the normative and behavioural dimensions of differential association (i.e., refers to both the orientation or attitude of their friends and family, as well as the behaviour of these individuals), and anticipated punishments were significant predictors of self-reported speeding. It was interesting to note that associating with significant others who held unfavourable definitions towards speeding (the normative dimension of differential association) and anticipating punishments from others were both significant predictors of a reduction in self-reported speeding. In relation to self-reported drink driving (n = 462), a logistic regression analysis indicated that there were a number of significant predictors which increased the likelihood of whether participants had driven in the last six months when they thought they may have been over the legal alcohol limit. These included: experiences of direct punishment avoidance; having a family member convicted of drink driving; higher levels of Type-A behaviour pattern; greater alcohol misuse (as measured by the AUDIT); and the normative dimension of differential association (i.e., associating with others who held favourable attitudes to drink driving). A final logistic regression analysis examined the predictors of whether the participants reported engaging in both drink driving and speeding versus those who reported engaging in only speeding (the more common of the two behaviours) (n = 465). It was found that experiences of punishment avoidance for speeding decreased the likelihood of engaging in both speeding and drink driving; whereas in the case of drink driving, direct punishment avoidance increased the likelihood of engaging in both behaviours. It was also noted that holding favourable personal definitions toward speeding and drink driving, as well as higher levels of on Type-A behaviour pattern, and greater alcohol misuse significantly increased the likelihood of engaging in both speeding and drink driving. This research has demonstrated that the compliance with the regulatory limits was much higher for drink driving than it was for speeding. It is acknowledged that while speed limits are a fundamental component of speed management practices in Australia, the countermeasures applied to both speeding and drink driving do not appear to elicit the same level of compliance across the driving population. Further, the findings suggest that while the principles underpinning the current regime of deterrence based countermeasures are sound, current enforcement practices are insufficient to force compliance among the driving population, particularly in the case of speeding. Future research should further examine the degree of overlap between speeding and drink driving behaviour and whether punishment avoidance experiences for a specific illegal driving behaviour serve to undermine the deterrent effect of countermeasures aimed at reducing the incidence of another illegal driving behaviour. Furthermore, future work should seek to understand the factors which predict engaging in speeding and drink driving behaviours at the same time. Speeding has shown itself to be a pervasive and persistent behaviour, hence it would be useful to examine why road safety authorities have been successful in convincing the majority of drivers of the dangers of drink driving, but not those associated with speeding. In conclusion, the challenge for road safety practitioners will be to convince drivers that speeding and drink driving are equally risky behaviours, with the ultimate goal to reduce the prevalence of both behaviours.

The association between objectively measured neighborhood features and walking in middle-aged adults

Purpose: To explore the role of the neighborhood environment in supporting walking Design: Cross sectional study of 10,286 residents of 200 neighborhoods. Participants were selected using a stratified two-stage cluster design. Data were collected by mail survey (68.5% response rate). Setting: The Brisbane City Local Government Area, Australia, 2007. Subjects: Brisbane residents aged 40 to 65 years. Measures Environmental: street connectivity, residential density, hilliness, tree coverage, bikeways, and street lights within a one kilometer circular buffer from each resident’s home; and network distance to nearest river or coast, public transport, shop, and park. Walking: minutes in the previous week categorized as < 30 minutes, ≥ 30 < 90 minutes, ≥ 90 < 150 minutes, ≥ 150 < 300 minutes, and ≥ 300 minutes. Analysis: The association between each neighborhood characteristic and walking was examined using multilevel multinomial logistic regression and the model parameters were estimated using Markov chain Monte Carlo simulation. Results: After adjustment for individual factors, the likelihood of walking for more than 300 minutes (relative to <30 minutes) was highest in areas with the most connectivity (OR=1.93, 99% CI 1.32-2.80), the greatest residential density (OR=1.47, 99% CI 1.02-2.12), the least tree coverage (OR=1.69, 99% CI 1.13-2.51), the most bikeways (OR=1.60, 99% CI 1.16-2.21), and the most street lights (OR=1.50, 99% CI 1.07-2.11). The likelihood of walking for more than 300 minutes was also higher among those who lived closest to a river or the coast (OR=2.06, 99% CI 1.41-3.02). Conclusion: The likelihood of meeting (and exceeding) physical activity recommendations on the basis of walking was higher in neighborhoods with greater street connectivity and residential density, more street lights and bikeways, closer proximity to waterways, and less tree coverage. Interventions targeting these neighborhood characteristics may lead to improved environmental quality as well as lower rates of overweight and obesity and associated chromic disease.

Microbial colonisation of human follicular fluid and adverse in vitro fertilisation outcomes

This study, investigating 263 women undergoing trans-vaginal oocyte retrieval for in vitro fertilisation (IVF) found that microorganisms colonising follicular fluid contributed to adverse IVF (pre-implantation) and pregnancy (post-implantation) outcomes including poor quality embryos, failed pregnancy and early pregnancy loss (< 37 weeks gestation). Some microorganisms also showed in vitro growth patterns in liquid media that appeared to be enhanced by the hormonal stimulation protocol used for oocyte retrieval. Elaborated cytokines within follicular fluid were also associated with adverse IVF outcomes. This study is imperative because infertility affects 16% of the human population and the numbers of couples needing assistance continues to increase. Despite significant improvements in the technical aspects of assisted reproductive technologies (ART), the live birth rate has not increased proportionally. Overt genital tract infection has been associated with both infertility and adverse pregnancy outcomes (including miscarriage and preterm birth) as a direct result of the infection or the host response to it. Importantly, once inflammation had become established, medical treatment often failed to prevent these significant adverse outcomes. Current evaluations of fertility focus on the ovary as a site of steroid hormone production and ovulation. However, infertility as a result of subclinical colonisation of the ovary has not been reported. Furthermore, identification of the microorganisms present in follicular fluid and the local cytokine profile may provide clinicians with an early indication of the prognosis for IVF treatment in infertile couples, thus allowing antimicrobial treatment and/or counselling about possible IVF failure. During an IVF cycle, multiple oocytes undergo maturation in vivo in response to hormonal hyperstimulation. Oocytes for in vitro insemination are collected trans-vaginally. The follicular fluid that bathes the maturing oocyte in vivo, usually is discarded as part of the IVF procedure, but provides a unique opportunity to investigate microbial causes of adverse IVF outcomes. Some previous studies have identified follicular fluid markers that predict IVF pregnancy outcomes. However, there have not been any detailed microbiological studies of follicular fluid. For this current study, paired follicular fluid and vaginal secretion samples were collected from women undergoing IVF cycles to determine whether microorganisms in follicular fluid were associated with adverse IVF outcomes. Microorganisms in follicular fluid were regarded as either "colonisers" or "contaminants"; colonisers, if they were unique to the follicular fluid sample, and contaminants if the same microorganisms were detected in the vaginal and follicular fluid samples indicating that the follicular fluid was merely contaminated during the oocyte retrieval process. Quite unexpectedly, by these criteria, we found that follicular fluid from approximately 30% of all subjects was colonised with bacteria. Fertile and infertile women with colonised follicular fluid had decreased embryo transfer rates and decreased pregnancy rates compared to women with contaminated follicular fluids. The observation that follicular fluid was not always sterile, but contained a diverse range of microorganisms, is novel. Many of the microorganisms we detected in follicular fluid are known opportunistic pathogens that have been detected in upper genital tract infections and are associated with adverse pregnancy outcomes. Bacteria were able to survive for at least 28 weeks in vitro, in cultures of follicular fluid. Within 10 days of establishing these in vitro cultures, several species (Lactobacillus spp., Bifidobacterium spp., Propionibacterium spp., Streptococcus spp. and Salmonella entericus) had formed biofilms. Biofilms play a major role in microbial pathogenicity and persistence. The propensity of microbial species to form biofilms in follicular fluid suggests that successful treatment of these infections with antimicrobials may be difficult. Bifidobacterium spp. grew, in liquid media, only if concentrations of oestradiol and progesterone were similar to those achieved in vivo during an IVF cycle. In contrast, the growth of Streptococcus agalactiae and Escherichia coli was inhibited or abolished by the addition of these hormones to culture medium. These data suggest that the likelihood of microorganisms colonising follicular fluid and the species of bacteria involved is influenced by the stage of the menstrual cycle and, in the case of IVF, the nature and dose of steroid hormones administered for the maturation of multiple oocytes in vivo. Our findings indicate that the elevated levels of steroid hormones during an IVF cycle may influence the microbial growth within follicular fluid, suggesting that the treatment itself will impact on the microflora present in the female upper genital tract during pre-conception and early post-conception phases of the cycle. The effect of the host immune response on colonising bacteria and on the outcomes of IVF also was investigated. White blood cells reportedly compose between 5% and 15% of the cell population in follicular fluid. The follicular membrane is semi-permeable and cells are actively recruited as part of the normal menstrual cycle and in response to microorganisms. A previous study investigated follicular fluid cytokines from infertile women and fertile oocyte donors undergoing IVF, and concluded that there were no significant differences in the cytokine concentrations between the two groups. However, other studies have reported differences in the follicular fluid cytokine levels associated with infertile women with endometriosis or polycystic ovary syndrome. In this study, elevated levels of interleukin (IL)-1 á, IL-1 â and vascular endothelial growth factor (VEGF) in vaginal fluid were associated with successful fertilisation, which may be useful marker for successful fertilisation outcomes for women trying to conceive naturally or prior to oocyte retrieval for IVF. Elevated levels of IL-6, IL-12p40, granulocyte colony stimulating factor (GCSF) and interferon-gamma (IFN ã) in follicular fluid were associated with successful embryo transfer. Elevated levels of pro-inflammatory IL-18 and decreased levels of anti-inflammatory IL-10 were identified in follicular fluid from women with idiopathic infertility. Successful fertilisation and implantation is dependent on a controlled pro-inflammatory environment, involving active recruitment of pro-inflammatory mediators to the genital tract as part of the menstrual cycle and early pregnancy. However, ongoing pregnancy requires an enhanced anti-inflammatory environment to ensure that the maternal immune system does not reject the semi-allergenic foetus. The pro-inflammatory skew in the follicular fluid of women with idiopathic infertility, correlates with normal rates of fertilisation, embryo discard and embryo transfer, observed for this cohort, which were similar to the outcomes observed for fertile women. However, their pregnancy rate was reduced compared to fertile women. An altered local immune response in follicular fluid may provide a means of explaining infertility in this cohort, previously defined as 'idiopathic'. This study has found that microorganisms colonising follicular fluid may have contributed to adverse IVF and pregnancy outcomes. Follicular fluid bathes the cumulus oocyte complex during the in vivo maturation process, and microorganisms in the fluid, their metabolic products or the local immune response to these microorganisms may result in damage to the oocytes, degradation of the cumulus or contamination of the IVF culture system. Previous studies that have discounted bacterial contamination of follicular fluid as a cause of adverse IVF outcomes failed to distinguish between bacteria that were introduced into the follicular fluid at the time of trans-vaginal oocyte retrieval and those that colonised the follicular fluid. Those bacteria that had colonised the fluid may have had time to form biofilms and to elicit a local immune response. Failure to draw this distinction has previously prevented consideration of bacterial colonisation of follicular fluid as a cause of adverse IVF outcomes. Several observations arising from this study are of significance to IVF programs. Follicular fluid is not always sterile and colonisation of follicular fluid is a cause of adverse IVF and pregnancy outcomes. Hormonal stimulation associated with IVF may influence whether follicular fluid is colonised and enhance the growth of specific species of bacteria within follicular fluid. Bacteria in follicular fluid may form biofilms and literature has reported that this may influence their susceptibility to antibiotics. Monitoring the levels of selected cytokines within vaginal secretions may inform fertilisation outcomes. This study has identified novel factors contributing to adverse IVF outcomes and that are most likely to affect also natural conception outcomes. Early intervention, possibly using antimicrobial or immunological therapies may reduce the need for ART and improve reproductive health outcomes for all women.

Assessing financial reporting comparability across institutional settings : the case of pension accounting

The drive for comparability of financial information is to enable users to distinguish similarities and differences in economic activities for an entity over time and between entities so that their resource allocation decisions are facilitated. With the increased globalisation of economic activities, the enhanced international comparability of financial statements is often used as an argument to advance the convergence of local accounting standards to international financial reporting standards (IFRS). Differences in the underlying economic substance of transactions between jurisdictions plus accounting standards allowing alternative treatments may render this expectation of increased comparability unrealistic. Motivated by observations that, as a construct, comparability is under-researched and not well understood, we develop a comparability framework that distinguishes between four types of comparability. In applying this comparability framework to pension accounting in the Australian and USA contexts, we highlight a dilemma: while regulators seek to increase the likelihood that similar events are accounted for similarly, an unintended consequence may be that preparers are forced to apply similar accounting treatment to events that are, in substance, different.

Vulnerable road user groups : a review of younger drivers, motorcyclists and older drivers

Scientific efforts to understand and reduce the occurrence of road crashes continue to expand, particularly in the areas of vulnerable road user groups. Three groups that are receiving increasing attention within the literature are younger drivers, motorcyclists and older drivers. These three groups are at an elevated risk of being in a crash or seriously injured, and research continues to focus on the origins of this risk as well as the development of appropriate countermeasures to improve driving outcomes for these cohorts. However, it currently remains unclear what factors produce the largest contribution to crash risk or what countermeasures are likely to produce the greatest long term positive effects on road safety. This paper reviews research that has focused on the personal and environmental factors that increase crash risk for these groups as well as considers direction for future research in the respective areas. A major theme to emerge from this review is that while there is a plethora of individual and situational factors that influence the likelihood of crashes, these factors often combine in an additive manner to exacerbate the risk of both injury and fatality. Additionally, there are a number of risk factors that are pertinent for all three road user groups, particularly age and the level of driving experience. As a result, targeted interventions that address these factors are likely to maximise the flow-on benefits to a wider range of road users. Finally, there is a need for further research that aims to bridge the research-to-practice gap, in order to develop appropriate pathways to ensure that evidenced-based research is directly transferred to effective policies that improve safety outcomes.

CAT-SLAM : probabilistic localisation and mapping using a continuous appearance-based trajectory

This paper describes a new system, dubbed Continuous Appearance-based Trajectory Simultaneous Localisation and Mapping (CAT-SLAM), which augments sequential appearance-based place recognition with local metric pose filtering to improve the frequency and reliability of appearance-based loop closure. As in other approaches to appearance-based mapping, loop closure is performed without calculating global feature geometry or performing 3D map construction. Loop-closure filtering uses a probabilistic distribution of possible loop closures along the robot’s previous trajectory, which is represented by a linked list of previously visited locations linked by odometric information. Sequential appearance-based place recognition and local metric pose filtering are evaluated simultaneously using a Rao–Blackwellised particle filter, which weights particles based on appearance matching over sequential frames and the similarity of robot motion along the trajectory. The particle filter explicitly models both the likelihood of revisiting previous locations and exploring new locations. A modified resampling scheme counters particle deprivation and allows loop-closure updates to be performed in constant time for a given environment. We compare the performance of CAT-SLAM with FAB-MAP (a state-of-the-art appearance-only SLAM algorithm) using multiple real-world datasets, demonstrating an increase in the number of correct loop closures detected by CAT-SLAM.

Controlling Minimally-Actuated Vehicles for Applications in Ocean Observation

Establishing a persistent presence in the ocean with an AUV to observe temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we propose a strategy that utilizes ocean model predictions to increase the autonomy and control of Lagrangian or profiling floats for precisely this purpose. An A* planner is applied to a local controllability map generated from predictions of ocean currents to compute a path between prescribed waypoints that has the highest likelihood of successful execution. The control to follow the planned path is computed by use of a model predictive controller. This controller is designed to select the best depth for the vehicle to exploit ambient currents to reach the goal waypoint. Mission constraints are employed to simulate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, and show surprising results in the ability of a Lagrangian float to reach a desired location.

Using approximate Bayesian computation to estimate transmission rates of nosocomial pathogens

In this paper, we apply a simulation based approach for estimating transmission rates of nosocomial pathogens. In particular, the objective is to infer the transmission rate between colonised health-care practitioners and uncolonised patients (and vice versa) solely from routinely collected incidence data. The method, using approximate Bayesian computation, is substantially less computer intensive and easier to implement than likelihood-based approaches we refer to here. We find through replacing the likelihood with a comparison of an efficient summary statistic between observed and simulated data that little is lost in the precision of estimated transmission rates. Furthermore, we investigate the impact of incorporating uncertainty in previously fixed parameters on the precision of the estimated transmission rates.

A Bias in ML Estimates of Branch Lengths in the Presence of Multiple Signals

Sequence data often have competing signals that are detected by network programs or Lento plots. Such data can be formed by generating sequences on more than one tree, and combining the results, a mixture model. We report that with such mixture models, the estimates of edge (branch) lengths from maximum likelihood (ML) methods that assume a single tree are biased. Based on the observed number of competing signals in real data, such a bias of ML is expected to occur frequently. Because network methods can recover competing signals more accurately, there is a need for ML methods allowing a network. A fundamental problem is that mixture models can have more parameters than can be recovered from the data, so that some mixtures are not, in principle, identifiable. We recommend that network programs be incorporated into best practice analysis, along with ML and Bayesian trees.