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111.
Diane Hope Weixing Zhu Corinna Gries Jacob Oleson Jason Kaye Nancy B. Grimm Lawrence A. Baker 《Urban Ecosystems》2005,8(3-4):251-273
We explored variations in inorganic soil nitrogen (N) concentrations across metropolitan Phoenix, Arizona, and the surrounding
desert using a probability-based synoptic survey. Data were examined using spatial statistics on the entire region, as well
as for the desert and urban sites separately. Concentrations of both NO3-N and NH4-N were markedly higher and more heterogeneous amongst urban compared to desert soils. Regional variation in soil NO3-N concentration was best explained by latitude, land use history, population density, along with percent cover of impervious
surfaces and lawn, whereas soil NH4-N concentrations were related to only latitude and population density. Within the urban area, patterns in both soil NO3-N and NH4-N were best predicted by elevation, population density and type of irrigation in the surrounding neighborhood. Spatial autocorrelation
of soil NO3-N concentrations explained 49% of variation among desert sites but was absent between urban sites. We suggest that inorganic
soil N concentrations are controlled by a number of ‘local’ or ‘neighborhood’ human-related drivers in the city, rather than
factors related to an urban-rural gradient. 相似文献
112.
Michael V. Tidwell 《Nonprofit management & leadership》2005,15(4):449-467
This study draws on social identity theory, while developing and testing the Social Identification Model of Prosocial Behavior among voluntary participants in nonprofit organizations. This model posits relationships between organization identification, commitment, satisfaction, and prosocial behavior among nonprofit volunteers. Path analysis results indicate successful identification of the model. Specifically, when volunteers identified with their nonprofit, they had higher levels of prosocial behaviors, commitment, and satisfaction. This study provides several important extensions to social identity theory and nonprofit literatures while highlighting the need for further research examining motivations behind prosocial behaviors within nonprofits. 相似文献
113.
Jonathan H. Wright 《Econometric Reviews》2002,21(4):397-417
Many recent papers have used semiparametric methods, especially the log-periodogram regression, to detect and estimate long memory in the volatility of asset returns. In these papers, the volatility is proxied by measures such as squared, log-squared, and absolute returns. While the evidence for the existence of long memory is strong using any of these measures, the actual long memory parameter estimates can be sensitive to which measure is used. In Monte-Carlo simulations, I find that if the data is conditionally leptokurtic, the log-periodogram regression estimator using squared returns has a large downward bias, which is avoided by using other volatility measures. In United States stock return data, I find that squared returns give much lower estimates of the long memory parameter than the alternative volatility measures, which is consistent with the simulation results. I conclude that researchers should avoid using the squared returns in the semiparametric estimation of long memory volatility dependencies. 相似文献
114.
Carmen Fernández Eduardo Ley Mark F. J. Steel 《Journal of the Royal Statistical Society. Series C, Applied statistics》2002,51(3):257-280
Summary. We model daily catches of fishing boats in the Grand Bank fishing grounds. We use data on catches per species for a number of vessels collected by the European Union in the context of the Northwest Atlantic Fisheries Organization. Many variables can be thought to influence the amount caught: a number of ship characteristics (such as the size of the ship, the fishing technique used and the mesh size of the nets) are obvious candidates, but one can also consider the season or the actual location of the catch. Our database leads to 28 possible regressors (arising from six continuous variables and four categorical variables, whose 22 levels are treated separately), resulting in a set of 177 million possible linear regression models for the log-catch. Zero observations are modelled separately through a probit model. Inference is based on Bayesian model averaging, using a Markov chain Monte Carlo approach. Particular attention is paid to the prediction of catches for single and aggregated ships. 相似文献
115.
116.
If a population contains many zero values and the sample size is not very large, the traditional normal approximation‐based confidence intervals for the population mean may have poor coverage probabilities. This problem is substantially reduced by constructing parametric likelihood ratio intervals when an appropriate mixture model can be found. In the context of survey sampling, however, there is a general preference for making minimal assumptions about the population under study. The authors have therefore investigated the coverage properties of nonparametric empirical likelihood confidence intervals for the population mean. They show that under a variety of hypothetical populations, these intervals often outperformed parametric likelihood intervals by having more balanced coverage rates and larger lower bounds. The authors illustrate their methodology using data from the Canadian Labour Force Survey for the year 2000. 相似文献
117.
118.
A sample size justification should be given for all clinical investigations. However, sometimes the objective of a trial is to estimate an effect with a view to planning a later definitive study. This paper describes the calculations for designing studies where one wishes to adopt an estimation approach through using confidence intervals around the overall response. Calculations are given for data anticipated to take a Normal form. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
119.
A finite mixture model using the multivariate t distribution has been shown as a robust extension of normal mixtures. In this paper, we present a Bayesian approach for inference about parameters of t-mixture models. The specifications of prior distributions are weakly informative to avoid causing nonintegrable posterior distributions. We present two efficient EM-type algorithms for computing the joint posterior mode with the observed data and an incomplete future vector as the sample. Markov chain Monte Carlo sampling schemes are also developed to obtain the target posterior distribution of parameters. The advantages of Bayesian approach over the maximum likelihood method are demonstrated via a set of real data. 相似文献
120.
Craig H. Mallinckrodt Christopher J. Kaiser John G. Watkin Michael J. Detke Geert Molenberghs Raymond J. Carroll 《Pharmaceutical statistics》2004,3(3):171-186
The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SEΔ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SEΔ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SEΔ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献