Comparison of properties of tests for assessing tumor clonality

SUMMARY: In a recent article Begg et al. (2007, Biometrics 63, 522-530) proposed a statistical test to determine whether or not a diagnosed second primary tumor is biologically independent of the original primary tumor, by comparing patterns of allelic losses at candidate genetic loci. The proposed concordant mutations test is a conditional test, an adaptation of Fisher's exact test, that requires no knowledge of the marginal mutation probabilities. The test was shown to have generally good properties, but is susceptible to anticonservative bias if there is wide variation in mutation probabilities between loci, or if the individual mutation probabilities of the parental alleles for individual patients differ substantially from each other. In this article, a likelihood ratio test is derived in an effort to address these validity issues. This test requires prespecification of the marginal mutation probabilities at each locus, parameters for which some information will typically be available in the literature. In simulations this test is shown to be valid, but to be considerably less efficient than the concordant mutations test for sample sizes (numbers of informative loci) typical of this problem. Much of the efficiency deficit can be recovered, however, by restricting the allelic imbalance parameter estimate to a prespecified range, assuming that this parameter is in the prespecified range.     

Moderated statistical tests for assessing differences in tag abundance

MOTIVATION: Digital gene expression (DGE) technologies measure gene expression by counting sequence tags. They are sensitive technologies for measuring gene expression on a genomic scale, without the need for prior knowledge of the genome sequence. As the cost of sequencing DNA decreases, the number of DGE datasets is expected to grow dramatically. Various tests of differential expression have been proposed for replicated DGE data using binomial, Poisson, negative binomial or pseudo-likelihood (PL) models for the counts, but none of the these are usable when the number of replicates is very small. RESULTS: We develop tests using the negative binomial distribution to model overdispersion relative to the Poisson, and use conditional weighted likelihood to moderate the level of overdispersion across genes. Not only is our strategy applicable even with the smallest number of libraries, but it also proves to be more powerful than previous strategies when more libraries are available. The methodology is equally applicable to other counting technologies, such as proteomic spectral counts. AVAILABILITY: An R package can be accessed from http://bioinf.wehi.edu.au/resources/     

An anatomical model to determine step height in step testing for estimating aerobic capacity

Physical fitness has been reported to be inversely related to coronary heart disease and other health related problems. One of the most valid means of assessing physical fitness is the test of aerobic capacity. Aerobic capacity is the greatest rate at which the body can consume oxygen and represents the most efficient integration of the various physiological processes which make up the oxygen transport system. However, direct measurement of aerobic capacity requires sophisticated laboratory equipment, and is adversive to subjects. Step tests are widely used to estimate aerobic capacity. Because the biomechanical efficiency and work rate is determined by step height, accommodation of step height to the subject's statute height should provide a better estimation of aerobic capacity. A hip angle of 73.3 degrees, when stepping, was found to give the best relationship of recovery heart rate of a step test to direct measurement of aerobic capacity. Using 73.3 degrees, the following equations were developed for determining the stepping height when using the step test: Hf = 0.189 Ih and Hf = 0.192 Ih for females and males respectively, where hf is the step height and Ih is the statute height of the subject. A correlation coefficient (r) of 0.93 was calculated between various hip angles and calculated foot height of 182 observations of 47 females while a correlation coefficient (r) of 0.96 was calculated from 208 observations of 53 males. Using these equations to determine step height, measurement of 30 females showed a mean hip angle of 73.3 degrees +/- 2.2 and measurement of 30 males showed a mean hip angle of 73.3 degrees +/- 2.1.(ABSTRACT TRUNCATED AT 250 WORDS)     

A questionnaire technique for assessing the stress at work

Subjective perception of the stress at work is a phenomenon reflecting the experience-mediated relationship between the sum of objective conditions of work and the sum of individual's traits available to cope with demands of the work environment. This relationship is mirrored in the function of the whole organism and can be described using the formula S = f (E, D), where S = the state of the organism, E = exposure (i.e. the sum of all stressors the organism is exposed to), and D = disposition (i.e. the sum of traits the organism has available to cope with these stressors). Based on these theoretical considerations, a questionnaire has been developed as a tool for assessing the work stress in different groups of occupations. This "Work Stress Assessment" (WSA) questionnaire was used in a group of 4800 female employees from various branches of the printing industry. Of a total of 160 questionnaire items, 98 items were selected and used to assess the workload in these employees, using a 5-point rating scale of evaluation. The responses were processed statistically, separately for 3531 blue-collar and 1269 white-collar respondents. The use of the factor analysis method revealed that the two groups of jobs had 16 factors in common, 3 factors were specific for blue-collar and 2 factors for white-collar jobs. Judged by factor components, the responses of subjects were well structured and the perceived stress at work turned out to well reflect the reality of conditions of work, which confirms the construct validity of this methodical approach based on the subjective perception of occupational stress. High coefficients of consistency (0.959 for blue-collar and 0.946 for white-collar occupations) point to the reliability of this questionnaire technique. Thus, the WSA questionnaire appears to suitably complement the other methodical approaches aimed at assessing the stress at work in different groups of occupations.     

Minimum time required for assessing step variability during running at submaximal velocities

This study aimed to determine the minimum time required for assessing spatiotemporal variability during continuous running at different submaximal velocities and, thereby, the number of steps required. Nineteen trained endurance runners performed an incremental running protocol, with a 3-min recording period at 10, 12, 14 and 16 km/h. Spatiotemporal parameters (contact and flight times, step length and step frequency) were measured using the OptoGait system and step variability was considered for each parameter, in terms of within-participants standard deviation (SD) and coefficient of variation (CV%). Step variability was considered over six different durations at every velocity tested: 0–10 s, 0–20 s, 0–30 s, 0–60 s, 0–120 s and 0–180 s. The repeated measures ANOVA revealed no significant differences in the magnitude of the four spatiotemporal parameters between the recording intervals at each running velocity tested (p ≥ 0.05, ICC > 0.90). The post-hoc analysis confirmed no significant differences in step variability (SD and CV% of each spatiotemporal parameter at any velocity tested) between measurements. The Bland-Altman limits of agreement method showed that longer recording intervals yield smaller systematic bias, random errors, and narrower limits of agreement, regardless of running velocity. The results suggest that the duration of the recording period required to estimate spatiotemporal variability plays an important role in the accuracy of the measurement, regardless of running velocity (10–16 km/h).     

Latent likelihood ratio tests for assessing spatial kernels in epidemic models

One of the most important issues in the critical assessment of spatio-temporal stochastic models for epidemics is the selection of the transmission kernel used to represent the relationship between infectious challenge and spatial separation of infected and susceptible hosts. As the design of control strategies is often based on an assessment of the distance over which transmission can realistically occur and estimation of this distance is very sensitive to the choice of kernel function, it is important that models used to inform control strategies can be scrutinised in the light of observation in order to elicit possible evidence against the selected kernel function. While a range of approaches to model criticism is in existence, the field remains one in which the need for further research is recognised. In this paper, building on earlier contributions by the authors, we introduce a new approach to assessing the validity of spatial kernels—the latent likelihood ratio tests—which use likelihood-based discrepancy variables that can be used to compare the fit of competing models, and compare the capacity of this approach to detect model mis-specification with that of tests based on the use of infection-link residuals. We demonstrate that the new approach can be used to formulate tests with greater power than infection-link residuals to detect kernel mis-specification particularly when the degree of mis-specification is modest. This new tests avoid the use of a fully Bayesian approach which may introduce undesirable complications related to computational complexity and prior sensitivity.

     

A method for assessing work productivity and flexibility in livestock farms

Changes affecting livestock farming systems have made farm work a central concern for both the sector and for farmers themselves. Increased pressure on farms to be competitive and productive together with farmers' demand for greater autonomy, holidays or time to spend on private activities and the family converge to underline the two key dimensions of work - productivity and flexibility - required for the assessment of work organization. This paper proposes a method called the QuaeWork (QUAlification and Evaluation of Work in livestock farms) to assess work productivity and flexibility on a farm, and its use to identify how livestock management can contribute to work organization on dairy farms. The QuaeWork method was set up through an iterative process combining surveys conducted with farmers in two regions of France, discussions with different experts and literature review. The QuaeWork was applied on a sample of seven dairy farms in the southern Massif Central in France to identify patterns of how livestock management contributes to work organization. The QuaeWork was used to analyse work organization over the year through a systemic approach to the farm, integrating interactions between herd and land management, workforce composition, equipment facilities and combinations of activities through a characterization of 'who does what, when and for how long'. The criteria for assessing work productivity were work duration (routine work, seasonal work) and work efficiency (per livestock unit or hectare of utilized agricultural area). The criteria for assessing work flexibility were room for manoeuvre and adjustments to internal and external events. The three main patterns of livestock management practices to work organization were identified. In pattern-1, farmers used indoor stable feeding practices with delegated work, with moderate room for manoeuvre and efficiency. In pattern-3, farmers used simplified milking, reproduction and breeding practices to seasonalize work and make it efficient with consistent room for manoeuvre. The method suggests social sustainability criteria to assess work productivity and flexibility, which are important for making reasoned decisions on livestock farm changes, especially innovations. Researchers could usefully exploit the QuaeWork to integrate work objectives (productivity, flexibility) into technical and economic goals.     

Clustering-neural network models for freeway work zone capacity estimation

Two neural network models, called clustering-RBFNN and clustering-BPNN models, are created for estimating the work zone capacity in a freeway work zone as a function of seventeen different factors through judicious integration of the subtractive clustering approach with the radial basis function (RBF) and the backpropagation (BP) neural network models. The clustering-RBFNN model has the attractive characteristics of training stability, accuracy, and quick convergence. The results of validation indicate that the work zone capacity can be estimated by clustering-neural network models in general with an error of less than 10%, even with limited data available to train the models. The clustering-RBFNN model is used to study several main factors affecting work zone capacity. The results of such parametric studies can assist work zone engineers and highway agencies to create effective traffic management plans (TMP) for work zones quantitatively and objectively.     

Nutritional status and physical work capacity

The functional consequences of nutritional intake and resulting nutritional status are reviewed in terms of maximal oxygen consumption, physical work capacity, heart rate response to exercise, work productivity, and endurance at submaximal work loads. The results of both acute “laboratory” and chronic “naturally occurring” malnutrition are considered as well as the effects of dietary supplementation and recovery from previously existing undernutrition. Obesity and anemia are also treated as separate but related nutritional entities.     

Sleep disorders and medical work capacity

Excessive daily sleepiness attribute to sleep disturbances can be a problem for occupational physician concerning the work ability to security works, night shift work and vehicle driving. It's difficult to detect those pathologies because the workers don't identify their symptoms as serious diseases or because they mask these symptoms for fear of the loose of their job. We've studied one case of SAS (sleep apnea syndrome) and one case of narcolepsy to demonstrate: 1) the criterions of the occupational forecast; 2) the sometimes serious social and occupational consequences of a medical inaptitude sanction. We insist on the necessity of a good collaboration between general practitioner and occupational physician.