Analysis of Melanoma Onset: Assessing Familial Aggregation by Using Estimating Equations and Fitting Variance Components via Bayesian Random Effects Models

We investigate whether relative contributions of genetic and shared environmental factors are associated with an increased risk in melanoma. Data from the Queensland Familial Melanoma Project comprising 15,907 subjects arising from 1912 families were analyzed to estimate the additive genetic, common and unique environmental contributions to variation in the age at onset of melanoma. Two complementary approaches for analyzing correlated time-to-onset family data were considered: the generalized estimating equations (GEE) method in which one can estimate relationship-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modeled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov Chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the free ware package BUGS. In addition, we also used a Bayesian model to investigate the relative contribution of genetic and environmental effects on the expression of naevi and freckles, which are known risk factors for melanoma.

Estimating the specific heat capacity of starch-water-glycerol systems as a function of temperature and compositions

Increasing interests in the use of starch as biodegradable plastic materials demand, amongst others, accurate information on thermal properties of starch systems particularly in the processing of thermoplastic starch (TPS), where plasticisers (water and glycerol) are added. The specific heat capacity of starch-water-glycerol mixtures was determined within a temperature range of 40-120degreesC. A modulated temperature differential scanning calorimeter (MTDSC) was employed and regression equations were obtained to predict the specific heat capacity as a function of temperature, water and glycerol content for four maize starches of differing amylose content (0 - 85%). Generally, temperature and water content are directly proportional to the specific heat capacity of the systems, but the influence of glycerol content on the thermal property varied according to the starch type.

Estimating physical activity level: The role of domestic activities

Appropriate measures of physical activity are essential for determining the population prevalence of physical activity, for tracking trends over time, and for guiding intervention efforts. Physical activity measurement is characterised by the synthesis of information on the type, frequency, intensity, and duration of activity over a specified period. To date, emphasis in physical activity assessment has been on the measurement of leisure time physical activities. However, some domestic and transport related activities entail energy expenditures equivalent to moderate intensity of 3.0–6.0 METS1 considered to be of sufficient intensity to achieve a health benefit are yet to be included in routine population level physical activity surveillance. This leads to population estimates based only on measures of leisure time physical activities.

Estimating disease likelihood: a case of rubbery figures

In diagnosis and prognosis, we should avoid intuitive “guesstimates” and seek a validated numerical aid

Improving precision and reducing bias in biological surveys: estimating false-negative error rates

The use of presence/absence data in wildlife management and biological surveys is widespread. There is a growing interest in quantifying the sources of error associated with these data. We show that false-negative errors (failure to record a species when in fact it is present) can have a significant impact on statistical estimation of habitat models using simulated data. Then we introduce an extension of logistic modeling, the zero-inflated binomial (ZIB) model that permits the estimation of the rate of false-negative errors and the correction of estimates of the probability of occurrence for false-negative errors by using repeated. visits to the same site. Our simulations show that even relatively low rates of false negatives bias statistical estimates of habitat effects. The method with three repeated visits eliminates the bias, but estimates are relatively imprecise. Six repeated visits improve precision of estimates to levels comparable to that achieved with conventional statistics in the absence of false-negative errors In general, when error rates are less than or equal to50% greater efficiency is gained by adding more sites, whereas when error rates are >50% it is better to increase the number of repeated visits. We highlight the flexibility of the method with three case studies, clearly demonstrating the effect of false-negative errors for a range of commonly used survey methods.

Estimating trends and seasonality in coronary heart disease

We present two methods of estimating the trend, seasonality and noise in time series of coronary heart disease events. In contrast to previous work we use a non-linear trend, allow multiple seasonal components, and carefully examine the residuals from the fitted model. We show the importance of estimating these three aspects of the observed data to aid insight of the underlying process, although our major focus is on the seasonal components. For one method we allow the seasonal effects to vary over time and show how this helps the understanding of the association between coronary heart disease and varying temperature patterns. Copyright (C) 2004 John Wiley Sons, Ltd.

Improving the efficiency of wildlife monitoring by estimating detectability: a case study of foxes (Vulpes vulpes) on the Eyre Peninsula, South Australia

Demonstrating the existence of trends in monitoring data is of increasing practical importance to conservation managers wishing to preserve threatened species or reduce the impact of pest species. However, the ability to do so can be compromised if the species in question has low detectability and the true occupancy level or abundance of the species is thus obscured. Zero-inflated models that explicitly model detectability improve the ability to make sound ecological inference in such situations. In this paper we apply an occupancy model including detectability to data from the initial stages of a fox-monitoring program on the Eyre Peninsula, South Australia. We find that detectability is extremely low (< 18%) and varies according to season and the presence or absence of roadside vegetation. We show that simple methods of using monitoring data to inform management, such as plotting the raw data or performing logistic regression, fail to accurately diagnose either the status of the fox population or its trajectory over time. We use the results of the detectability model to consider how future monitoring could be redesigned to achieve efficiency gains. A wide range of monitoring programs could benefit from similar analyses, as part of an active adaptive approach to improving monitoring and management.

Estimating percolation and lateral water flow on sloping land in rainfed lowland rice ecosystem

Quantifying water losses in paddy fields assists estimation of water availability in rainfed lowland rice ecosystem. Little information is available on water balance in different toposequence positions of sloped rainfed lowland. Therefore, the aim of this work was to quantify percolation and the lateral water flow with special reference to the toposequential variation. Data used for the analysis was collected in Laos and northeast Thailand. Percolation and water tables were measured on a daily basis using a steel cylindrical tube with a lid and perforated PVC tubes, respectively. Percolation rate was determined using linear regression analysis of cumulative percolation. Assuming that the total amount of evaporation and transpiration was equivalent to potential evapotranspiration, the lateral water flow was estimated using the water balance equation. Separate perched water and groundwater tables were observed in paddy fields on coarse-textured soils. The percolation rate varied between 0 and 3 mm/day across locations, and the maximum water loss by lateral movement was more than 20 mm/day. Our results are in agreement with the previously reported findings, and the methodology of estimating water balance components appears reasonably acceptable. With regard to the toposequential variation, the higher the position in the topoesquence, the greater potential for water loss because of higher percolation and lateral flow rates.

Estimating the recreational-use value for hiking in Bellenden Ker National Park, Australia

The recreational-use value of hiking in the Bellenden Ker National Park, Australia has been estimated using a zonal travel cost model. Multiple destination visitors have been accounted for by converting visitors' own ordinal ranking of the various sites visited to numerical weights, using an expected-value approach. The value of hiking and camping in this national park was found to be $AUS 250,825 per year, or $AUS 144,45 per visitor per year, which is similar to findings from other studies valuing recreational benefits. The management of the park can use these estimates when considering the introduction of a system of user pays fees. In addition, they might be important when decisions need to be made about the allocation of resources for maintenance or upgrade of tracks and facilities.

Estimating variable returns to scale production frontiers with alternative stochastic assumptions

Two stochastic production frontier models are formulated within the generalized production function framework popularized by Zellner and Revankar (Rev. Econ. Stud. 36 (1969) 241) and Zellner and Ryu (J. Appl. Econometrics 13 (1998) 101). This framework is convenient for parsimonious modeling of a production function with returns to scale specified as a function of output. Two alternatives for introducing the stochastic inefficiency term and the stochastic error are considered. In the first the errors are added to an equation of the form h(log y, theta) = log f (x, beta) where y denotes output, x is a vector of inputs and (theta, beta) are parameters. In the second the equation h(log y,theta) = log f(x, beta) is solved for log y to yield a solution of the form log y = g[theta, log f(x, beta)] and the errors are added to this equation. The latter alternative is novel, but it is needed to preserve the usual definition of firm efficiency. The two alternative stochastic assumptions are considered in conjunction with two returns to scale functions, making a total of four models that are considered. A Bayesian framework for estimating all four models is described. The techniques are applied to USDA state-level data on agricultural output and four inputs. Posterior distributions for all parameters, for firm efficiencies and for the efficiency rankings of firms are obtained. The sensitivity of the results to the returns to scale specification and to the stochastic specification is examined. (c) 2004 Elsevier B.V. All rights reserved.

Estimating state-contingent production frontiers

Chambers and Quiggin (2000) use state-contingent representations of risky production technologies to establish important theoretical results concerning producer behavior under uncertainty. Unfortunately, perceived problems in the estimation of state-contingent models have limited the usefulness of the approach in policy formulation. We show that fixed and random effects state-contingent production frontiers can be conveniently estimated in a finite mixtures framework. An empirical example is provided. Compared to conventional estimation approaches, we find that estimating production frontiers in a state-contingent framework produces significantly different estimates of elasticities, firm technical efficiencies, and other quantities of economic interest.

Simple approach to estimating the van der Waals interaction between carbon nanotubes

The van der Waals (vdW) interactions between carbon nanotubes (CNTs) were studied based on the continuum Lennard-Jones model. It was found that all the vdW potentials between two arbitrary CNTs fall on the same curve when plotted in terms of certain reduced parameters, the well depth, and the equilibrium vdW gap. Based on this observation, an approximate approach is developed to obtain the vdW potential between two CNTs without time-consuming computations. The vdW potential estimated by this approach is close to that obtained from complex integrations. Therefore, the developed approach can greatly simplify the calculation of vdW interactions between CNTs.

Comparison of the particulate organic carbon and permanganate oxidation methods for estimating labile soil organic carbon

Forty-four soils from under native vegetation and a range of management practices following clearing were analysed for ‘labile’ organic carbon (OC) using both the particulate organic carbon (POC) and the 333 mm KmnO4 (MnoxC) methods. Although there was some correlation between the 2 methods, the POC method was more sensitive by about a factor of 2 to rapid loss in OC as a result of management or land-use change. Unlike the POC method, the MnoxC method was insensitive to rapid gains in TOC following establishment of pasture on degraded soil. The MnoxC method was shown to be particularly sensitive to the presence of lignin or lignin-like compounds and therefore is likely to be very sensitive to the nature of the vegetation present at or near the time of sampling and explains the insensitivity of this method to OC gain under pasture. The presence of charcoal is an issue with both techniques, but whereas the charcoal contribution to the POC fraction can be assessed, the MnoxC method cannot distinguish between charcoal and most biomolecules found in soil. Because of these limitations, the MnoxC method should not be applied indiscriminately across different soil types and management practices.

Estimating nutrient intake in comparative studies of animals: an example using dietary carotenoid content in birds

Many different methods of reporting animal diets have been used in ecological research. These vary greatly in level of accuracy and precision and therefore complicate attempts to measure and compare diets, and quantitites of nutrients in those diets, across a wide range of taxa. For most birds, the carotenoid content of the diet has not been directly measured. Here, therefore, I use an avian example to show how different methods of measuring the quantities of various foods in the diet affect the relative rankings of higher taxa (families, subfamilies, and tribes), and species within these taxa, with regard to the carotenoid contents of their diets. This is a timely example, as much recent avian literature has focused on the way dietary carotenoids may be traded off among aspects of survival, fitness and signalling. I assessed the mean dietary carotenoid contents of representatives of thirty higher taxa of birds using four different carotenoid intake indices varying in precision, including trophic levels, a coarse-scale and a fine-scale categorical index, and quantitative estimates of dietary carotenoids. This last method was used as the benchmark. For comparisons among taxa, all but the trophic level index were significantly correlated with each other. However, for comparisons of species within taxa, the fine-scale index outperformed the coarse-scale index, which in turn outperformed the trophic level index. In addition, each method has advantages and disadvantages, as well as underlying assumptions that must be considered. Examination and comparison of several possible methods of diet assessment appears to highlight these so that the best possible index is used given available data, and it is recommended that such a step be taken prior to the inclusion of estimated nutrient intake in any statistical analysis. Although applied to avian carotenoids here, this method could readily be applied to other taxa and types of nutrients.