共查询到20条相似文献，搜索用时 0 毫秒
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Ingolf Kühn 《Diversity & distributions》2007,13(1):66-69
Though still often neglected, spatial autocorrelation can be a serious issue in ecology because the presence of spatial autocorrelation may alter the parameter estimates and error probabilities of linear models. Here I re-analysed data from a previous study on the relationship between plant species richness and environmental correlates in Germany. While there was a positive relationship between native plant species richness and an altitudinal gradient when ignoring the presence of spatial autocorrelation, the use of a spatial simultaneous liner error model revealed a negative relationship. This most dramatic effect where the observed pattern was inverted may be explained by the environmental situation in Germany. There the highest altitudes are in the south and the lowlands in the north that result in some locally or regionally inverted patterns of the large-scale environmental gradients from the equator to the north. This study therefore shows the necessity to consider spatial autocorrelation in spatial analyses. 相似文献
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Modeling individual heterogeneity in capture probabilities has been one of the most challenging tasks in capture–recapture studies. Heterogeneity in capture probabilities can be modeled as a function of individual covariates, but correlation structure among capture occasions should be taking into account. A proposed generalized estimating equations (GEE) and generalized linear mixed modeling (GLMM) approaches can be used to estimate capture probabilities and population size for capture–recapture closed population models. An example is used for an illustrative application and for comparison with currently used methodology. A simulation study is also conducted to show the performance of the estimation procedures. Our simulation results show that the proposed quasi‐likelihood based on GEE approach provides lower SE than partial likelihood based on either generalized linear models (GLM) or GLMM approaches for estimating population size in a closed capture–recapture experiment. Estimator performance is good if a large proportion of individuals are captured. For cases where only a small proportion of individuals are captured, the estimates become unstable, but the GEE approach outperforms the other methods. 相似文献
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Carter Allen Yuzhou Chang Brian Neelon Won Chang Hang J. Kim Zihai Li Qin Ma Dongjun Chung 《Biometrics》2023,79(3):1775-1787
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This paper presents Granger mediation analysis, a new framework for causal mediation analysis of multiple time series. This framework is motivated by a functional magnetic resonance imaging (fMRI) experiment where we are interested in estimating the mediation effects between a randomized stimulus time series and brain activity time series from two brain regions. The independent observation assumption is thus unrealistic for this type of time‐series data. To address this challenge, our framework integrates two types of models: causal mediation analysis across the mediation variables, and vector autoregressive (VAR) models across the temporal observations. We use “Granger” to refer to VAR correlations modeled in this paper. We further extend this framework to handle multilevel data, in order to model individual variability and correlated errors between the mediator and the outcome variables. Using Rubin's potential outcome framework, we show that the causal mediation effects are identifiable under our time‐series model. We further develop computationally efficient algorithms to maximize our likelihood‐based estimation criteria. Simulation studies show that our method reduces the estimation bias and improves statistical power, compared with existing approaches. On a real fMRI data set, our approach quantifies the causal effects through a brain pathway, while capturing the dynamic dependence between two brain regions. 相似文献
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Bastien Trächsel Valentin Rousson Jean-Luc Bulliard Isabella Locatelli 《Biometrical journal. Biometrische Zeitschrift》2023,65(7):2200046
This study compares the performance of statistical methods for predicting age-standardized cancer incidence, including Poisson generalized linear models, age-period-cohort (APC) and Bayesian age-period-cohort (BAPC) models, autoregressive integrated moving average (ARIMA) time series, and simple linear models. The methods are evaluated via leave-future-out cross-validation, and performance is assessed using the normalized root mean square error, interval score, and coverage of prediction intervals. Methods were applied to cancer incidence from the three Swiss cancer registries of Geneva, Neuchatel, and Vaud combined, considering the five most frequent cancer sites: breast, colorectal, lung, prostate, and skin melanoma and bringing all other sites together in a final group. Best overall performance was achieved by ARIMA models, followed by linear regression models. Prediction methods based on model selection using the Akaike information criterion resulted in overfitting. The widely used APC and BAPC models were found to be suboptimal for prediction, particularly in the case of a trend reversal in incidence, as it was observed for prostate cancer. In general, we do not recommend predicting cancer incidence for periods far into the future but rather updating predictions regularly. 相似文献
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Summary . Spatial clustering is commonly modeled by a Bayesian method under the framework of generalized linear mixed effect models (GLMMs). Spatial clusters are commonly detected by a frequentist method through hypothesis testing. In this article, we provide a frequentist method for assessing spatial properties of GLMMs. We propose a strategy that detects spatial clusters through parameter estimates of spatial associations, and assesses spatial aspects of model improvement through iterated residuals. Simulations and a case study show that the proposed method is able to consistently and efficiently detect the locations and magnitudes of spatial clusters. 相似文献
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We propose a mixed-effect linear model, as a particular case of the two-level regression model, for analyzing repeated measures made at completely irregular time points. The model allows for subject-level covariates, so as to study the trend and the variability of the individual growth curves. Application of this model is illustrated on a published data set. 相似文献
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Maria João Paúl Dan Rosauer Pedro Tarroso Guillermo Velo-Antón Sílvia B. Carvalho 《Ecology and evolution》2023,13(1):e9666
Understanding the ecological and evolutionary processes driving biodiversity patterns and allowing their persistence is of utmost importance. Many hypotheses have been proposed to explain spatial diversity patterns, including water-energy availability, habitat heterogeneity, and historical climatic refugia. The main goal of this study is to identify if general spatial drivers of species diversity patterns of phylogenetic diversity (PD) and phylogenetic endemism (PE) at the global scale are also predictive of PD and PE at regional scales, using Iberian amphibians as a case study. Our main hypothesis assumes that topography along with contemporary and historical climate are drivers of phylogenetic diversity and endemism, but that the strength of these predictors may be weaker at the regional scale than it tends to be at the global scale. We mapped spatial patterns of Iberian amphibians' phylogenetic diversity and endemism, using previously published phylogenetic and distribution data. Furthermore, we compiled spatial data on topographic and climatic variables related to the water-energy availability, topography, and historical climatic instability hypotheses. To test our hypotheses, we used Spatial Autoregressive Models and selected the best model to explain diversity patterns based on Akaike Information Criterion. Our results show that, out of the variables tested in our study, water-energy availability and historical climate instability are the most important drivers of amphibian diversity in Iberia. However, as predicted, the strength of these predictors in our case study is weaker than it tends to be at global scales. Thus, additional drivers should also be investigated and we suggest caution when interpreting these predictors as surrogates for different components of diversity. 相似文献
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Hans‐Peter Piepho 《Biometrical journal. Biometrische Zeitschrift》2019,61(4):860-872
Extensions of linear models are very commonly used in the analysis of biological data. Whereas goodness of fit measures such as the coefficient of determination (R2) or the adjusted R2 are well established for linear models, it is not obvious how such measures should be defined for generalized linear and mixed models. There are by now several proposals but no consensus has yet emerged as to the best unified approach in these settings. In particular, it is an open question how to best account for heteroscedasticity and for covariance among observations present in residual error or induced by random effects. This paper proposes a new approach that addresses this issue and is universally applicable for arbitrary variance‐covariance structures including spatial models and repeated measures. It is exemplified using three biological examples. 相似文献
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Summary . Motivated by an analysis of a real data set in ecology, we consider a class of partially nonlinear models where both a nonparametric component and a parametric component are present. We develop two new estimation procedures to estimate the parameters in the parametric component. Consistency and asymptotic normality of the resulting estimators are established. We further propose an estimation procedure and a generalized F -test procedure for the nonparametric component in the partially nonlinear models. Asymptotic properties of the newly proposed estimation procedure and the test statistic are derived. Finite sample performance of the proposed inference procedures are assessed by Monte Carlo simulation studies. An application in ecology is used to illustrate the proposed methods. 相似文献
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This article presents a statistical method, vector autoregressive moving average time series analysis, which makes no initial assumptions about the controlling interactions between variables in the data beyond those of linear systems, and has been designed to be statistically valid without requiring several repetitions of data sets. It is therefore very useful for studying physiological and behavioral phenomena.This new methodology is applied to a kinematic analysis of antennal scanning movements in two species of millipede. The analysis demonstrates features of the generation of the antennal and head movements, the direction of information flow within the central nervous system and consequent asymmetric control relationships between bilaterally homologous body parts. 相似文献
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The extent to which climate change might diminish the efficacy of protected areas is one of the most pressing conservation questions. Many projections suggest that climate‐driven species distribution shifts will leave protected areas impoverished and species inadequately protected while other evidence suggests that intact ecosystems within protected areas will be resilient to change. Here, we tackle this problem empirically. We show how recent changes in distribution of 139 Tanzanian savannah bird species are linked to climate change, protected area status and land degradation. We provide the first evidence of climate‐driven range shifts for an African bird community. Our results suggest that the continued maintenance of existing protected areas is an appropriate conservation response to the challenge of climate and environmental change. 相似文献
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Over the years, there have been claims that evolution proceeds according to systematically different processes over different timescales and that protein evolution behaves in a non-Markovian manner. On the other hand, Markov models are fundamental to many applications in evolutionary studies. Apparent non-Markovian or time-dependent behavior has been attributed to influence of the genetic code at short timescales and dominance of physicochemical properties of the amino acids at long timescales. However, any long time period is simply the accumulation of many short time periods, and it remains unclear why evolution should appear to act systematically differently across the range of timescales studied. We show that the observed time-dependent behavior can be explained qualitatively by modeling protein sequence evolution as an aggregated Markov process (AMP): a time-homogeneous Markovian substitution model observed only at the level of the amino acids encoded by the protein-coding DNA sequence. The study of AMPs sheds new light on the relationship between amino acid-level and codon-level models of sequence evolution, and our results suggest that protein evolution should be modeled at the codon level rather than using amino acid substitution models. 相似文献
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Heterogeneity among individuals in fitness components is what selection acts upon. Evolutionary theories predict that selection in constant environments acts against such heterogeneity. But observations reveal substantial non-genetic and also non-environmental variability in phenotypes. Here, we examine whether there is a relationship between selection pressure and phenotypic variability by analysing structured population models based on data from a large and diverse set of species. Our findings suggest that non-genetic, non-environmental variation is in general neither truly neutral, selected for, nor selected against. We find much variations among species and populations within species, with mean patterns suggesting nearly neutral evolution of life-course variability. Populations that show greater diversity of life courses do not show, in general, increased or decreased population growth rates. Our analysis suggests we are only at the beginning of understanding the evolution and maintenance of non-genetic non-environmental variation. 相似文献
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Josep L. Carrasco 《Biometrics》2010,66(3):897-904
Summary The classical concordance correlation coefficient (CCC) to measure agreement among a set of observers assumes data to be distributed as normal and a linear relationship between the mean and the subject and observer effects. Here, the CCC is generalized to afford any distribution from the exponential family by means of the generalized linear mixed models (GLMMs) theory and applied to the case of overdispersed count data. An example of CD34+ cell count data is provided to show the applicability of the procedure. In the latter case, different CCCs are defined and applied to the data by changing the GLMM that fits the data. A simulation study is carried out to explore the behavior of the procedure with a small and moderate sample size. 相似文献