Semiparametric regression modeling with mixtures of Berkson and classical error, with application to fallout from the Nevada test site

We construct Bayesian methods for semiparametric modeling of a monotonic regression function when the predictors are measured with classical error. Berkson error, or a mixture of the two. Such methods require a distribution for the unobserved (latent) predictor, a distribution we also model semiparametrically. Such combinations of semiparametric methods for the dose response as well as the latent variable distribution have not been considered in the measurement error literature for any form of measurement error. In addition, our methods represent a new approach to those problems where the measurement error combines Berkson and classical components. While the methods are general, we develop them around a specific application, namely, the study of thyroid disease in relation to radiation fallout from the Nevada test site. We use this data to illustrate our methods, which suggest a point estimate (posterior mean) of relative risk at high doses nearly double that of previous analyses but that also suggest much greater uncertainty in the relative risk.     

Statistical inference for familial disease clusters

In many epidemiologic studies, the first indication of an environmental or genetic contribution to the disease is the way in which the diseased cases cluster within the same family units. The concept of clustering is contrasted with incidence. We assume that all individuals are exchangeable except for their disease status. This assumption is used to provide an exact test of the initial hypothesis of no familial link with the disease, conditional on the number of diseased cases and the distribution of the sizes of the various family units. New parametric generalizations of binomial sampling models are described to provide measures of the effect size of the disease clustering. We consider models and an example that takes covariates into account. Ascertainment bias is described and the appropriate sampling distribution is demonstrated. Four numerical examples with real data illustrate these methods.     

A generalized discriminant rule when training population and test population differ on their descriptive parameters

Standard discriminant analysis methods make the assumption that both the labeled sample used to estimate the discriminant rule and the nonlabeled sample on which this rule is applied arise from the same population. In this work, we consider the case where the two populations are slightly different. In the multinormal context, we establish that both populations are linked through linear mapping. Estimation of the nonlabeled sample discriminant rule is then obtained by estimating parameters of this linear relationship. Several models describing this relationship are proposed and associated estimated parameters are given. An experimental illustration is also provided in which sex of birds that differ morphometrically over their geographical range is to be deterrmined and a comparison with the standard allocation rule is performed. Extension to a partially labeled sample is also discussed.     

The compliance score as a regressor in randomized trials

The compliance score in randomized trials is a measure of the effect of randomization on treatment received. It is in principle a group-level pretreatment variable and so can be used where individual-level measures of treatment received can produce misleading inferences. The interpretation of models with the compliance score as a regressor of interest depends on the link function. Using the identity link can lead to valid inference about the effects of treatment received even in the presence of nonrandom noncompliance; such inference is more problematic for nonlinear links. We illustrate these points with data from two randomized trials.     

Species richness and assemblage structure of Trichoptera in Danish streams

• 1 Species richness and assemblages of Trichoptera from 157 ‘pristine’ Danish lowland stream sites were analyzed, for dependence on geographical position of the sites and simple physical variables, using two way indicator species analysis and detrended correspondence analysis.
• 2 A total of 106 species were recorded, representing ≈ 90% of the species pool known from Danish streams. Only seven species occurred at more than half the sites, whereas an additional 11 species were found at more than a quarter of the sites.
• 3 Although sites showed significant regional differences in environmental variables (stream order, width, slope and presence/absence of riparian forest), species richness and assemblages were primarily correlated with stream order, width and slope. Maximum richness was found at the largest (5th order) stream sites.
• 4 Regional differences in species assemblages were found, with several species being absent from the islands Funen and Bornholm. Species assemblages also differed between forested and non‐forested stream sites.
• 5 We found evidence that stream temperature may be of only minor importance in determining Trichoptera species richness and assemblage composition in Danish streams compared to other size‐related physical factors.

     

Subterranean rodents of the genus Ctenomys (Caviomorpha, Ctenomyidae) follow the converse to Bergmann's rule

Aim We analysed body‐size variation in relation to latitude, longitude, elevation and environmental variables in Ctenomys (tuco‐tucos), subterranean rodents in the Ctenomyidae (Caviomorpha). We tested the existence of inter‐ and intraspecific size clines to determine if these rodents follow Bergmann's rule, to compare intra‐ and interspecific size trends and to assess the relevance of the subterranean lifestyle on these trends. Location South America, south of 15° latitude. Methods This paper is based on 719 specimens of tuco‐tucos from 133 localities of Argentina, Bolivia, Chile, Paraguay, Peru and Uruguay, representing 47 named species and 32 undescribed forms. Intraspecific analyses were performed for Ctenomys talarum Thomas, 1898 and the Ctenomys perrensi Thomas, 1896 species complex. Head and body length and weight were used for estimating body size. Geographical independent variables included latitude, longitude and altitude. Environmental independent variables were mean minimal and maximal monthly temperature, mean annual temperature, mean minimal and maximal precipitation, and total annual precipitation. To estimate seasonality, the annual variability of the climatic factors was calculated as their coefficients of variation and the difference between maximum and minimum values. Mean annual actual evapotranspiration (AET), and mean annual, January (summer) and July (winter) potential evapotranspiration (PET) values were also calculated for each locality, as well as annual, summer and winter water balance (WB). Statistical analyses consisted of simple and multiple regression and nonparametric correlation. Results Body size of Ctenomys decreases interspecifically from 15°00′ S to 48°15′ S and from 56°33′ W to 71°46′ W, and is positively correlated with ambient temperature and precipitation. The best predictors of body size according to multiple regression analyses were mean annual temperature, the difference between mean maximum and minimum annual temperatures, annual PET, the difference between summer and winter PET, and annual and winter water balance. These patterns are repeated, but not identically, at a smaller geographical scale within the species C. talarum and the superspecies C. perrensi. Main conclusions Tuco‐tucos follow the converse to Bergmann's rule at the interspecific level. At the intraspecific level some parallel trends were observed, but the smaller scale of these analyses, involving a very reduced variation of environmental factors, necessitates caution in interpreting results. The subterranean lifestyle probably insulates these rodents from the external temperature. The observed latitudinal body‐size gradients are more probably related to seasonality, ambient energy, primary productivity and/or intensity of predation.     

Predicting fine‐scale distributions of peripheral aquatic species in headwater streams

Headwater species and peripheral populations that occupy habitat at the edge of a species range may hold an increased conservation value to managers due to their potential to maximize intraspecies diversity and species' adaptive capabilities in the context of rapid environmental change. The southern Appalachian Mountains are the southern extent of the geographic range of native Salvelinus fontinalis and naturalized Oncorhynchus mykiss and Salmo trutta in eastern North America. We predicted distributions of these peripheral, headwater wild trout populations at a fine scale to serve as a planning and management tool for resource managers to maximize resistance and resilience of these populations in the face of anthropogenic stressors. We developed correlative logistic regression models to predict occurrence of brook trout, rainbow trout, and brown trout for every interconfluence stream reach in the study area. A stream network was generated to capture a more consistent representation of headwater streams. Each of the final models had four significant metrics in common: stream order, fragmentation, precipitation, and land cover. Strahler stream order was found to be the most influential variable in two of the three final models and the second most influential variable in the other model. Greater than 70% presence accuracy was achieved for all three models. The underrepresentation of headwater streams in commonly used hydrography datasets is an important consideration that warrants close examination when forecasting headwater species distributions and range estimates. Additionally, it appears that a relative watershed position metric (e.g., stream order) is an important surrogate variable (even when elevation is included) for biotic interactions across the landscape in areas where headwater species distributions are influenced by topographical gradients.     

Concentration distribution around a growing gas bubble in tissue

This paper presents the concentration distribution around a growing nitrogen gas bubble in the blood and other tissues of divers who surface too quickly, when the ambient pressure through the decompression process is variable and constant. This effort is a modification of Sirinivasan et al. model (1999) [9]. The mathematical model is solved analytically to find the growth rate of a gas bubble in a tissue after decompression in the ambient pressure. Moreover, the concentration distribution around the growing bubble is introduced. The growth process is affected by ascent rate , tissue diffusivity D_T, initial concentration difference ΔC₀, surface tension σ and void fraction ?₀.     

荒漠植物红砂叶绿素和脯氨酸累积与环境因子的相关分析

通过测定中国境内荒漠植物红砂(Reaumuria soongorica)主要分布区内21个自然种群407株叶片的叶绿素和脯氨酸含量,以及不同种群内土壤含水量、可溶性盐分含量、有机质、全氮、全磷含量等土壤理化性状指标,分析了不同自然种群红砂叶绿素和脯氨酸含量的变异特征以及影响其变化的主要环境因子.研究结果表明:红砂种群间叶绿素含量差异显著.土壤因子对叶绿素合成的影响较气象因子大,而土壤含水量和土壤全磷含量是导致不同红砂种群叶绿素含量出现明显差异的主要原因.红砂脯氨酸含量平均值显著高于盐爪爪、骆驼刺、芨芨草等其它荒漠物种,并且与叶片含水量和土壤含水量呈显著负相关,与土壤可溶性盐分含量呈显著正相关.红砂体内脯氨酸的累积是对干旱盐渍环境的适应性反应,与抗旱性和抗盐性之间存在着一定的关系.