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Statistical analysis of the relationship among environmental variables, inter-annual variability and smolt trap efficiency of salmonids in the Tucannon River

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FISHERIES RESEARCH 2004年第2-3期70卷 229-238页

作者： Cheng, YW Gallinat, MP Washington Dept Fish & Wildlife Olympia WA 98504 USA

Spring and fall chinook (Oncorhynchus tshawytscha), steelhead (Oncorhynchus mykiss) and hatchery spring chinook in the Tucannon River, Washington, USA are listed as "threatened" under the Endangered Species Act of 1973. Restoration and management of both species can be facilitated by understanding how biotic and abiotic factors affect their smolt trap efficiency. In this paper, we examine the effects of the rate of water flow, water temperature, the level of staff gauge, debris load, and Secchi disk readings on their weekly smolt trap efficiency from 1998 to 2003 using a generalized linear model (GLM) with a binomial response (link function - logit). The nonlinear relationships between the smolt trap efficiency and abiotic variables are also analyzed using a generalized additive model (GAM) with a binomial response (link function - logit). Both GLM and GAM analyses showed that the trap efficiency varied among years for fall chinook, steelhead, and wild spring chinook, but not for hatchery spring chinook, and that the level of staff gauge and the rate of water flow were the most important factors altering trap efficiency. The partial residuals from GAM analyses were used to determine the optimal number of sampled fish with a known efficiency and to detect possibly misleading results from GLM analyses. (C) 2004 Elsevier B.V. All rights reserved.

关键词： smolt trap efficiency generalized linear model generalized additive model

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GLMs, GAMs and GLMMs: an overview of theory for applications in fisheries research

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FISHERIES RESEARCH 2004年第2-3期70卷 319-337页

作者： Venables, WN Dichmont, CM CSIRO Cleveland Qld 4163 Australia

This paper provides an overview of the modelling process using generalized linear models (GLMs), generalized additive models (GAMs) and generalized linear mixed models (GLMMs), especially as they are applied within fisheries research. We describe the essential aspect of model interpretation and construction so as to achieve its correct application. We start with the simplest models and show the progression from GLMs to either GAMs or GLMMs. Although this is not a comprehensive review, we emphasise topics relevant to fisheries science such as transformation options, link functions, adding model flexibility through splines, and using random and fixed effects. We finish by discussing the various aspects of these models and their variants, and provide a view on their relative benefits to fisheries research. (C) 2004 Elsevier B.V. All rights reserved.

关键词： generalized additive model generalized linear model generalized linear mixed model spline regression statistical modelling strategies

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The performance of German firms in the business-related service sector: A dynamic analysis

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JOURNAL OF BUSINESS & ECONOMIC STATISTICS 2004年第3期22卷 274-295页

作者： Van, PN Laisney, F Kaiser, U Univ Strasbourg THEME BETA F-67000 Strasbourg France Ctr European Econ Res ZEW D-68034 Mannheim Germany Odense Univ DK-5230 Odense M Denmark

We analyze the performance of firms from the German business-related service sector for 1994-2000. Performance is measured by ordinal assessment of changes in total sales. We estimate first-order Markov chain models using extensions of the multinormal logit model: a linear index model with alternative specifications of heterogeneity and a semiparametric model. The preferred specification involves heterogeneity connected to the firm and the type of transition. Our findings include that size has a positive effect on performance, young firms outperform older competitors, a single creditor has a stabilizing effect, diversification has a negative impact, and performance is significantly affected by legal status. Measuring performance through profit rather than sales does not alter the qualitative results.

关键词： business survey generalized additive model Markov chain multinomial logit model unobserved heterogeneity

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Analyzing nonlinear population dynamics data

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JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS 2004年第2期9卷 200-215页

作者： Chan, G Chan, KS Stenseth, NC Lingjaerde, OC Univ Iowa Dept Stat & Actuarial Sci Iowa City IA 52242 USA Univ Oslo CEES Dept Biol N-0316 Oslo Norway Univ Oslo Dept Informat N-0316 Oslo Norway

We consider the problem of analyzing long-term experiments with panels of nonlinear time-series data in the framework of generalized additive models. Our approach is developed for testing and estimating the (partial) common dynamic structure across treatment groups. We illustrate our approach with a detailed analysis of an ecotoxicological experiment on the effect of sublethal doses of a toxic substance (cadmium) on the long-run dynamic structure of the greenbottle blowfly (Lucilia sericata). The general model for the blowfly experiment is a generalized additive model which is derived from a stage-structured ecological model. We discuss the relationship between the components of the generalized additive model and those of the underlying stage-structured model. In particular, our proposed approach casts new insights on the effect of toxic diet on the population dynamic structure of the blowfly.

关键词： blowfly density-dependent density-independent ecology ecotoxicology generalized additive model negative binomial nonlinear time series normal poisson

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Predicting the occurrence of rare mollusks in northern California forests

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ECOLOGICAL APPLICATIONS 2004年第3期14卷 713-729页

作者： Dunk, JR Zielinski, WJ Preisler, HK US Forest Serv Pacific SW Res Stn Redwood Sci Lab USDA Arcata CA 95521 USA Humboldt State Univ Dept Environm & Nat Resource Sci Arcata CA 95521 USA US Forest Serv Pacific SW Res Stn USDA Berkeley CA 94701 USA

Terrestrial mollusks are important components of forest ecosystems, yet we know very little about the distribution and habitat of many of these species. We sampled for terrestrial mollusks in northern California with the goal of estimating the geographic ranges and developing predictive habitat models for five species that were assumed to be sensitive to land management activities. The species of interest were Ancotrema voyanum, Helminthoglypta talmadgei, Monadenia churchi, Monadenia fidelis klamathica, and M. f ochromphalus. We randomly selected 308 plots for sampling from a grid of points across a 2.2 million-ha study area. We used generalized additive models to estimate each mollusk's geographic range and to develop predictive habitat models within their ranges. models were developed at one microscale (1 ha), and six mesoscales (ranging from 12.5 to 1250 ha) using vegetation, physical, climatic, and spatial location covariates. Estimated geographic ranges varied from 4770 to 15 795 km(2). Predictive habitat models explained from 40.8% to 94.5% of the deviance in models describing the species' occurrences. models at the 1-ha scale were generally better than models at larger spatial scales. Of the six mesoscales evaluated, the "best" models were often at very large scales. Spatial location and climatic variables contributed significantly to the predictions of occurrence for most species. models for species with small geographic ranges generally appeared to be better than models for species with larger geographic ranges, possibly reflecting more restricted environmental conditions. Cross-validation results, however, showed that models for species with more locations were more stable. A. voyanum was more frequently associated with late-successional forests and M. churchi was found to be a habitat generalist. The remaining three species were not detected enough for us to make strong conclusions about their habitat associations. Our results provide important guidance t

关键词： Ancotrema California forest generalized additive model geographic range habitat association Helminthoglypta mollusk Monadenia Northwest Forest Plan predictive model

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Spatial models for line transect sampling

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JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS 2004年第2期9卷 181-199页

作者： Hedley, SL Buckland, ST Univ St Andrews Ctr Res Ecol & Environm Modelling The Observ St Andrews KY16 9LZ Fife Scotland

This article develops methods for fitting spatial models to line transect data. These allow animal density to be related to topographical, environmental, habitat, and other spatial variables, helping wildlife managers to identify the factors that affect abundance. They also enable estimation of abundance for any subarea of interest within the surveyed region, and potentially yield estimates of abundance from sightings surveys for which the survey design could not be randomized, such as surveys conducted from platforms of opportunity. The methods are illustrated through analyses of data from a shipboard sightings survey of minke whales in the Antarctic.

关键词： distance sampling generalized additive model generalized linear model population size estimation sightings survey spatial distribution

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An investigation of components of variance and tachyphylaxis in a placebo-controlled intravenous tyramine study

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BRITISH JOURNAL OF CLINICAL PHARMACOLOGY 2004年第5期57卷 657-660页

作者： Cantarini, MV Watkins, CL Growcott, J Hughes, AM AstraZeneca Dept Expt Med Macclesfield SK10 4TG Cheshire England

Aims To explore inter- and intra-volunteer variability for the dose of intravenous tyramine eliciting a 20 mmHg increase in systolic blood pressure from baseline (TYR20) and to evaluate potential tachyphylaxis. Methods Twelve healthy volunteers received blinded placebo-controlled ascending and descending sequences of intravenous tyramine injections on two separate occasions. The TYR20 was derived by linear interpolation, using three interventions to deal with missing data. Results Analysis of covariance (ANCOVA) demonstrated no significant difference in TYR20 between sequences, regardless of the missing data methodology applied. inter-volunteer variability was 2.4-3.4 times larger than within-volunteer variability. No evidence of tachyphylaxis was seen using either the sign test or generalized additive models, Conclusions Since inter-volunteer variability was greater than intra-volunteer variability, a crossover study design would be a more efficient study design, and the descending sequence of injections could be omitted since tachyphylaxis was not demonstrated.

关键词： generalized additive model intravenous tyramine pressor response tachyphylaxis

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Improved semiparametric time series models of air pollution and mortality

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JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION 2004年第468期99卷 938-948页

作者： Dominici, F McDermott, A Hastie, TJ Johns Hopkins Univ Dept Biostat Baltimore MD 21205 USA Stanford Univ Dept Stat Stanford CA 94305 USA

In 2002, methodological issues around time series analyses of air pollution and health attracted the attention of the scientific community, policy makers, the press, and the diverse stakeholders concerned with air pollution. As the U.S. Environmental Protection Agency (EPA) was finalizing its most recent review of epidemiologic evidence on particulate matter air pollution (PM), statisticians and epidemiologists found that the S-PLUS implementation of generalized additive models (GAMs) can overestimate effects of air pollution and understate statistical uncertainty in time series studies of air pollution and health. This discovery delayed completion of the PM Criteria Document prepared as part of the review of the U.S. National Ambient Air Quality Standard, because the time series findings represented a critical component of the evidence. In addition, it raised concerns about the adequacy of current model formulations and their software implementations. In this article we provide improvements in semiparametric regression directly relevant to risk estimation in time series studies of air pollution. First, we introduce a closed-form estimate of the asymptotically exact covariance matrix of the linear component of a GAM. To ease the implementation of these calculations, we develop the S package ***, an extended version of gain. Use of *** allows a more robust assessment of the statistical uncertainty of the estimated pollution coefficients. Second, we develop a bandwidth selection method to reduce confounding bias in the pollution-mortality relationship due to unmeasured time-varying factors, such as season and influenza epidemics. Third, we introduce a conceptual framework to fully explore the sensitivity of the air pollution risk estimates to model choice. We apply our methods to data of the National Mortality Morbidity Air Pollution Study, which includes time series data from the 90 largest U.S. cities for the period 1987-1994.

关键词： bandwidth selection generalized additive model generalized linear model mean squared error particulate matter semiparametric regression time series

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Disease cases and their medical costs attributable to smoking: an analysis of the national medical expenditure survey

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JOURNAL OF ECONOMETRICS 2003年第1期112卷 135-151页

作者： Johnson, E Dominici, F Griswold, M Zeger, SL Johns Hopkins Univ Sch Publ Hlth Dept Biostat Baltimore MD 21205 USA

We estimate the fraction of disease cases, and the fraction of their total medical expenditures, attributable to smoking for two disease groups: (LC) lung and laryngeal cancer and chronic obstructive pulmonary disease, (CHD) cardiovascular disease, stroke and other smoking-caused cancers. We use a generalized additive model to predict the probability of disease;and a semi-parametric, two-part cost model to estimate the average difference in medical expenditures for persons with and without disease. We estimate that 53% and 13% of the medical expenditures for persons with LC or CHD are attributable to smoking. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： smoking-attributable fraction smoking-attributable expenditure generalized additive model two-part model

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generalized models vs. classification tree analysis:: Predicting spatial distributions of plant species at different scales

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JOURNAL OF VEGETATION SCIENCE 2003年第5期14卷 669-680页

作者： Thuiller, W Araújo, MB Lavorel, S CNRS Ctr Ecol Fonct & Evolut F-34293 Montpellier 5 France

Statistical models of the realized niche of species are increasingly used, but systematic comparisons of alternative methods are still limited. In particular, only few studies have explored the effect of scale in model outputs. In this paper. we investigate the predictive ability of three statistical methods (generalized linear models, generalized additive models and classification tree analysis) using species distribution data at three scales: fine (Catalonia), intermediate (Portugal) and coarse (Europe). Four Mediterranean tree species were modelled for comparison. Variables selected by models were relatively consistent across scales and the predictive accuracy of models varied only slightly. However, there were slight differences in the performance of methods. Classification tree analysis had a lower accuracy than the generalized methods, especially at finer scales. The performance of generalized linear models also increased with scale. At the fine scale GLM with linear terms showed better accuracy than GLM with quadratic and polynomial terms. This is probably because distributions at finer scales represent a linear sub-sample of entire realized niches of species. In contrast to GLM, the performance of GAM was constant across scales being more data-oriented. The predictive accuracy of GAM was always at least equal to other techniques, suggesting that this modelling approach is more robust to variations of scale because it can deal with any response shape.

关键词： accuracy assessment climate variable generalized additive model generalized linear model Mediterranean tree species receiver operating characteristics curve

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