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1.
    
In risk assessment and environmental monitoring studies, concentration measurements frequently fall below detection limits (DL) of measuring instruments, resulting in left-censored data. The principal approaches for handling censored data include the substitution-based method, maximum likelihood estimation, robust regression on order statistics, and Kaplan-Meier. In practice, censored data are substituted with an arbitrary value prior to use of traditional statistical methods. Although some studies have evaluated the substitution performance in estimating population characteristics, they have focused mainly on normally and lognormally distributed data that contain a single DL. We employ Monte Carlo simulations to assess the impact of substitution when estimating population parameters based on censored data containing multiple DLs. We also consider different distributional assumptions including lognormal, Weibull, and gamma. We show that the reliability of the estimates after substitution is highly sensitive to distributional characteristics such as mean, standard deviation, skewness, and also data characteristics such as censoring percentage. The results highlight that although the performance of the substitution-based method improves as the censoring percentage decreases, its performance still depends on the population's distributional characteristics. Practical implications that follow from our findings indicate that caution must be taken in using the substitution method when analyzing censored environmental data.  相似文献   

2.
Kneale  Pauline E.  Howard  Alan 《Hydrobiologia》1997,349(1-3):59-63
Data on cyanobacteria (blue-green algae) are generallycollected on a reactive basis, frequently in responseto bloom events. Such data presents a biased andincomplete snapshot of water quality. This paper looksat two typical data sets for UK waters showing thatwhile statistics may be used to describe the data theyare of limited use in forecasting. Suggestions ofappropriate tests for small and sparse data sets aremade.  相似文献   

3.
    
Sparse geometric information from limited field-of-view medical images is often used to reconstruct the femur in biomechanical models of the hip and knee. However, the full femur geometry is needed to establish boundary conditions such as muscle attachment sites and joint axes which define the orientation of joint loads. Statistical shape models have been used to estimate the geometry of the full femur from varying amounts of sparse geometric information. However, the effect that different amounts of sparse data have on reconstruction accuracy has not been systematically assessed. In this study, we compared shape model and linear scaling reconstruction of the full femur surface from varying proportions of proximal and distal partial femur geometry in combination with morphometric and landmark data. We quantified reconstruction error in terms of surface-to-surface error as well as deviations in the reconstructed femur’s anatomical coordinate system which is important for biomechanical models. Using a partial proximal femur surface, mean shape model-based reconstruction surface error was 1.8 mm with 0.15° or less anatomic axis error, compared to 19.1 mm and 2.7–5.6° for linear scaling. Similar results were found when using a partial distal surface. However, varying amounts of proximal or distal partial surface data had a negligible effect on reconstruction accuracy. Our results show that given an appropriate set of sparse geometric data, a shape model can reconstruct full femur geometry with far greater accuracy than simple scaling.  相似文献   

4.
  总被引:9,自引:2,他引:9  
Because most macroecological and biodiversity data are spatially autocorrelated, special tools for describing spatial structures and dealing with hypothesis testing are usually required. Unfortunately, most of these methods have not been available in a single statistical package. Consequently, using these tools is still a challenge for most ecologists and biogeographers. In this paper, we present sam (Spatial Analysis in Macroecology), a new, easy-to-use, freeware package for spatial analysis in macroecology and biogeography. Through an intuitive, fully graphical interface, this package allows the user to describe spatial patterns in variables and provides an explicit spatial framework for standard techniques of regression and correlation. Moran's I autocorrelation coefficient can be calculated based on a range of matrices describing spatial relationships, for original variables as well as for residuals of regression models, which can also include filtering components (obtained by standard trend surface analysis or by principal coordinates of neighbour matrices). sam also offers tools for correcting the number of degrees of freedom when calculating the significance of correlation coefficients. Explicit spatial modelling using several forms of autoregression and generalized least-squares models are also available. We believe this new tool will provide researchers with the basic statistical tools to resolve autocorrelation problems and, simultaneously, to explore spatial components in macroecological and biogeographical data. Although the program was designed primarily for the applications in macroecology and biogeography, most of sam 's statistical tools will be useful for all kinds of surface pattern spatial analysis. The program is freely available at http://www.ecoevol.ufg.br/sam (permanent URL at http://purl.oclc.org/sam/ ).  相似文献   

5.
  总被引:7,自引:1,他引:7  
Aim  Spatial autocorrelation (SAC) in data, i.e. the higher similarity of closer samples, is a common phenomenon in ecology. SAC is starting to be considered in the analysis of species distribution data, and over the last 10 years several studies have incorporated SAC into statistical models (here termed 'spatial models'). Here, I address the question of whether incorporating SAC affects estimates of model coefficients and inference from statistical models.
Methods  I review ecological studies that compare spatial and non-spatial models.
Results  In all cases coefficient estimates for environmental correlates of species distributions were affected by SAC, leading to a mis-estimation of on average c . 25%. Model fit was also improved by incorporating SAC.
Main conclusions  These biased estimates and incorrect model specifications have implications for predicting species occurrences under changing environmental conditions. Spatial models are therefore required to estimate correctly the effects of environmental drivers on species present distributions, for a statistically unbiased identification of the drivers of distribution, and hence for more accurate forecasts of future distributions.  相似文献   

6.
    
Pasteuria penetrans is a naturally occurring bacterial parasite of plant parasitic nematodes showing satisfactory results in a biocontrol strategy of root-knot nematodes (Meloidogyne spp.). The endospores attach to the outside nematode body wall (cuticle) of the infective stage second-stage juveniles (J2) of Meloidogyne populations. Optimal attachment level should be around 5–10 endospores per juvenile, as enough endospores will initiate infection without reducing the ability of the nematode to invade roots. Greater than 15 endospores may disable the nematode in its movements, and invasion may not take place. In this research, evidence is provided that P. penetrans spores disturbed the nematode forward movement by disorganising the nematode's head turns. The results based on Markov chain and Cochran probability model show that even a low number of 5–8 spores of P. penetrans attached to the nematode cuticle have a significant impact on that movement, which plays a role in nematode locomotion.  相似文献   

7.
    
In clinical trials one traditionally models the effect of treatment on the mean response. The underlying assumption is that treatment affects the response distribution through a mean location shift on a suitable scale, with other aspects of the distribution (shape/dispersion/variance) remaining the same. This work is motivated by a trial in Parkinson's disease patients in which one of the endpoints is the number of falls during a 10‐week period. Inspection of the data reveals that the Poisson‐inverse Gaussian (PiG) distribution is appropriate, and that the experimental treatment reduces not only the mean, but also the variability, substantially. The conventional analysis assumes a treatment effect on the mean, either adjusted or unadjusted for covariates, and a constant dispersion parameter. On our data, this analysis yields a non‐significant treatment effect. However, if we model a treatment effect on both mean and dispersion parameters, both effects are highly significant. A simulation study shows that if a treatment effect exists on the dispersion and is ignored in the modelling, estimation of the treatment effect on the mean can be severely biased. We show further that if we use an orthogonal parametrization of the PiG distribution, estimates of the mean model are robust to misspecification of the dispersion model. We also discuss inferential aspects that are more difficult than anticipated in this setting. These findings have implications in the planning of statistical analyses for count data in clinical trials.  相似文献   

8.
We consider the problematic relationship between publication success and statistical significance in the light of analyses in which we examine the distribution of published probability (P) values across the statistical 'significance' range, below the 5% probability threshold. P-values are often judged according to whether they lie beneath traditionally accepted thresholds (< 0.05, < 0.01, < 0.001, < 0.0001); we examine how these thresholds influence the distribution of reported absolute P-values in published scientific papers, the majority in biological sciences. We collected published P-values from three leading journals, and summarized their distribution using the frequencies falling across and within these four threshold values between 0.05 and 0. These published frequencies were then fitted to three complementary null models which allowed us to predict the expected proportions of P-values in the top and bottom half of each inter-threshold interval (i.e. those lying below, as opposed to above, each P-value threshold). Statistical comparison of these predicted proportions, against those actually observed, provides the first empirical evidence for a remarkable excess of probability values being cited on, or just below, each threshold relative to the smoothed theoretical distributions. The pattern is consistent across thresholds and journals, and for whichever theoretical approach used to generate our expected proportions. We discuss this novel finding and its implications for solving the problems of publication bias and selective reporting in evolutionary biology.  相似文献   

9.
    
A new approach for statistical association signal identification is developed in this paper. We consider a strategy for nonprecise signal identification by extending the well‐known signal detection and signal identification methods applicable to the multiple testing problem. Collection of statistical instruments under the presented approach is much broader than under the traditional signal identification methods, allowing more efficient signal discovery. Further assessments of maximal value and average statistics in signal discovery are improved. While our method does not attempt to detect individual predictors, it instead detects sets of predictors that are jointly associated with the outcome. Therefore, an important application would be in genome wide association study (GWAS), where it can be used to detect genes which influence the phenotype but do not contain any individually significant single nucleotide polymorphism (SNP). We compare power of the signal identification method based on extremes of single p‐values with the signal localization method based on average statistics for logarithms of p‐values. A simulation analysis informs the application of signal localization using the average statistics for wide signals discovery in Gaussian white noise process. We apply average statistics and the localization method to GWAS to discover better gene influences of regulating loci in a Chinese cohort developed for risk of nasopharyngeal carcinoma (NPC).  相似文献   

10.
11.
  总被引:3,自引:3,他引:3  
Statistical phylogeographic studies contribute to our understanding of the factors that influence population divergence and speciation, and that ultimately generate biogeographical patterns. The use of coalescent modelling for analyses of genetic data provides a framework for statistically testing alternative hypotheses about the timing and pattern of divergence. However, the extent to which such approaches contribute to our understanding of biogeography depends on how well the alternative hypotheses chosen capture relevant aspects of species histories. New modelling techniques, which explicitly incorporate spatio-geographic data external to the gene trees themselves, provide a means for generating realistic phylogeographic hypotheses, even for taxa without a detailed fossil record. Here we illustrate how two such techniques – species distribution modelling and its historical extension, palaeodistribution modelling – in conjunction with coalescent simulations can be used to generate and test alternative hypotheses. In doing so, we highlight a few key studies that have creatively integrated both historical geographic and genetic data and argue for the wider incorporation of such explicit integrations in biogeographical studies.  相似文献   

12.
13.
    
Multiple linear regression analyses (also often referred to as generalized linear models – GLMs, or generalized linear mixed models – GLMMs) are widely used in the analysis of data in molecular ecology, often to assess the relative effects of genetic characteristics on individual fitness or traits, or how environmental characteristics influence patterns of genetic differentiation. However, the coefficients resulting from multiple regression analyses are sometimes misinterpreted, which can lead to incorrect interpretations and conclusions within individual studies, and can propagate to wider‐spread errors in the general understanding of a topic. The primary issue revolves around the interpretation of coefficients for independent variables when interaction terms are also included in the analyses. In this scenario, the coefficients associated with each independent variable are often interpreted as the independent effect of each predictor variable on the predicted variable. However, this interpretation is incorrect. The correct interpretation is that these coefficients represent the effect of each predictor variable on the predicted variable when all other predictor variables are zero. This difference may sound subtle, but the ramifications cannot be overstated. Here, my goals are to raise awareness of this issue, to demonstrate and emphasize the problems that can result and to provide alternative approaches for obtaining the desired information.  相似文献   

14.
    
Photoacoustic/Optoacoustic tomography aims to reconstruct maps of the initial pressure rise induced by the absorption of light pulses in tissue. This reconstruction is an ill-conditioned and under-determined problem, when the data acquisition protocol involves limited detection positions. The aim of the work is to develop an inversion method which integrates denoising procedure within the iterative model-based reconstruction to improve quantitative performance of optoacoustic imaging. Among the model-based schemes, total-variation (TV) constrained reconstruction scheme is a popular approach. In this work, a two-step approach was proposed for improving the TV constrained optoacoustic inversion by adding a non-local means based filtering step within each TV iteration. Compared to TV-based reconstruction, inclusion of this non-local means step resulted in signal-to-noise ratio improvement of 2.5 dB in the reconstructed optoacoustic images.  相似文献   

15.
Polynomial boundary treatment for wavelet regression   总被引:3,自引:0,他引:3  
  相似文献   

16.
    
The strain MWAP71 of Burkholderia caribensis produces a branched charged exopolysaccharide (EPS) that is responsible for soil aggregation. Understanding the conformational properties of the isolated polysaccharide is a prerequisite for proper investigation of the interactions between the polysaccharide and the soil at the atomic level. The aim of this study is first to have an overall view of the flexibility of the backbone and then to ascertain the role played by side groups in the conformational properties of the main chain. Conformational analysis of each oligomeric segment of the polysaccharide has been performed by means of adiabatic mapping of the backbone glycosidic torsion angles using the MM3(92) force field. Substitution by an acetyl group or by a Kdo unit has only a slight effect on the potential energy surfaces of the fragment model compounds. Calculated partition functions, however, indicate that the overall flexibility is slightly larger for the substituted oligomers than for the unsubstituted ones. Prediction of selected average interproton distances from the AB and BC potential energy surfaces allows comparison between modeling results and NMR measurements performed on the ABC fragment. Agreement between the experimental and the predicted data suggests that the established surfaces correctly reflect the observed conformational behavior of such fragments and validate the modeling protocol. The above results have been extended to regular and disordered long polymer chains, differing in Kdo content. It is found that Kdo affects the helical conformations of the polysaccharide. The number of stable helices is considerably larger with Kdo than without Kdo. On the contrary, Kdo has only a moderate effect on unperturbed disordered conformations of the polysaccharide. Predicted persistence length of 70 A suggests that the polymer is semirigid with moderate extension. A further validation of the modeling results is obtained by the good concordance between this predicted value and the experimental one of 95 A, measured from light scattering and viscosity experiments. The results lead to an understanding of the interactions of this polysaccharide with soils.  相似文献   

17.
    
Microarray studies, in order to identify genes associated with an outcome of interest, usually produce noisy measurements for a large number of gene expression features from a small number of subjects. One common approach to analyzing such high-dimensional data is to use linear errors-in-variables (EIV) models; however, current methods for fitting such models are computationally expensive. In this paper, we present two efficient screening procedures, namely, corrected penalized marginal screening (PMSc) and corrected sure independence screening (SISc), to reduce the number of variables for final model building. Both screening procedures are based on fitting corrected marginal regression models relating the outcome to each contaminated covariate separately, which can be computed efficiently even with a large number of features. Under mild conditions, we show that these procedures achieve screening consistency and reduce the number of features substantially, even when the number of covariates grows exponentially with sample size. In addition, if the true covariates are weakly correlated, we show that PMSc can achieve full variable selection consistency. Through a simulation study and an analysis of gene expression data for bone mineral density of Norwegian women, we demonstrate that the two new screening procedures make estimation of linear EIV models computationally scalable in high-dimensional settings, and improve finite sample estimation and selection performance compared with estimators that do not employ a screening stage.  相似文献   

18.
    
Demographic processes directly affect patterns of genetic variation within contemporary populations as well as future generations, allowing for demographic inference from patterns of both present-day and past genetic variation. Advances in laboratory procedures, sequencing and genotyping technologies in the past decades have resulted in massive increases in high-quality genome-wide genetic data from present-day populations and allowed retrieval of genetic data from archaeological material, also known as ancient DNA. This has resulted in an explosion of work exploring past changes in population size, structure, continuity and movement. However, as genetic processes are highly stochastic, patterns of genetic variation only indirectly reflect demographic histories. As a result, past demographic processes need to be reconstructed using an inferential approach. This usually involves comparing observed patterns of variation with model expectations from theoretical population genetics. A large number of approaches have been developed based on different population genetic models that each come with assumptions about the data and underlying demography. In this article I review some of the key models and assumptions underlying the most commonly used approaches for past demographic inference and their consequences for our ability to link the inferred demographic processes to the archaeological and climate records.This article is part of the theme issue ‘Cross-disciplinary approaches to prehistoric demography’.  相似文献   

19.
Abstract

Takotsubo cardiomyopathy (TCM) is characterized by transient myocardial dysfunction, typically at the left ventricular (LV) apex. Its pathophysiology and recovery mechanisms remain unknown. We investigated LV morphology and deformation in n?=?28 TCM patients. Patients with MRI within 5?days from admission (“early TCM”) showed reduced LVEF and higher ventricular volumes, but no differences in ECG, global strains or myocardial oedema. Statistical shape modelling described LV size (Mode 1), apical sphericity (Mode 2) and height (Mode 3). Significant differences in Mode 1 suggest that “early TCM” LV remodeling is mainly influenced by a change in ventricular size rather than apical sphericity.  相似文献   

20.
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