Home About us Contact
|
Home About us Contact | ||
|
|
||
Extensive Simulation Study (extensive + simulation_study)
Selected AbstractsOptimization of ordered distance sampling,ENVIRONMETRICS, Issue 2 2004Ryan M. Nielson Abstract Ordered distance sampling is a point-to-object sampling method that can be labor-efficient for demanding field situations. An extensive simulation study was conducted to find the optimum number, g, of population members to be encountered from each random starting point in ordered distance sampling. Monte Carlo simulations covered 64 combinations of four spatial patterns, four densities and four sample sizes. Values of g from 1 to 10 were considered for each case. Relative root mean squared error (RRMSE) and relative bias were calculated for each level of g, with RRMSE used as the primary assessment criterion for finding the optimum level of g. A non-parametric confidence interval was derived for the density estimate, and this was included in the simulations to gauge its performance. Superior estimation properties were found for g > 3, but diminishing returns, relative to the potential for increased effort in the field, were found for g > 5. The simulations showed noticeable diminishing returns for more than 20 sampled points. The non-parametric confidence interval performed well for populations with random, aggregate or double-clumped spatial patterns, but rarely came close to target coverage for populations that were regularly distributed. The non-parametric confidence interval presented here is recommended for general use. Copyright © 2004 John Wiley & Sons, Ltd. [source] Microsatellites versus single-nucleotide polymorphisms in confidence interval estimation of disease lociGENETIC EPIDEMIOLOGY, Issue 1 2006Charalampos Papachristou Abstract With cost-effective high-throughput Single Nucleotide Polymorphism (SNP) arrays now becoming widely available, it is highly anticipated that SNPs will soon become the choice of markers in whole genome screens. This optimism raises a great deal of interest in assessing whether dense SNP maps offer at least as much information as their microsatellite (MS) counterparts. Factors considered to date include information content, strength of linkage signals, and effect of linkage disequilibrium. In the current report, we focus on investigating the relative merits of SNPs vs. MS markers for disease gene localization. For our comparisons, we consider three novel confidence interval estimation procedures based on confidence set inference (CSI) using affected sib-pair data. Two of these procedures are multipoint in nature, enabling them to capitalize on dense SNPs with limited heterozygosity. The other procedure makes use of markers one at a time (two-point), but is much more computationally efficient. In addition to marker type, we also assess the effects of a number of other factors, including map density and marker heterozygosity, on disease gene localization through an extensive simulation study. Our results clearly show that confidence intervals derived based on the CSI multipoint procedures can place the trait locus in much shorter chromosomal segments using densely saturated SNP maps as opposed to using sparse MS maps. Finally, it is interesting (although not surprising) to note that, should one wish to perform a quick preliminary genome screening, then the two-point CSI procedure would be a preferred, computationally cost-effective choice. Genet. Epidemiol. 30:3,17, 2006. © 2005 Wiley-Liss, Inc. [source] Receiver operating characteristic surfaces in the presence of verification biasJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 1 2008Yueh-Yun Chi Summary., In diagnostic medicine, the receiver operating characteristic (ROC) surface is one of the established tools for assessing the accuracy of a diagnostic test in discriminating three disease states, and the volume under the ROC surface has served as a summary index for diagnostic accuracy. In practice, the selection for definitive disease examination may be based on initial test measurements and induces verification bias in the assessment. We propose a non-parametric likelihood-based approach to construct the empirical ROC surface in the presence of differential verification, and to estimate the volume under the ROC surface. Estimators of the standard deviation are derived by both the Fisher information and the jackknife method, and their relative accuracy is evaluated in an extensive simulation study. The methodology is further extended to incorporate discrete baseline covariates in the selection process, and to compare the accuracy of a pair of diagnostic tests. We apply the proposed method to compare the diagnostic accuracy between mini-mental state examination and clinical evaluation of dementia, in discriminating between three disease states of Alzheimer's disease. [source] Goodness-of-fit tests of normality for the innovations in ARMA modelsJOURNAL OF TIME SERIES ANALYSIS, Issue 3 2004Gilles R. Ducharme Abstract., In this paper, we propose a goodness-of-fit test of normality for the innovations of an ARMA(p, q) model with known mean or trend. The test is based on the data driven smooth test approach and is simple to perform. An extensive simulation study is conducted to study the behaviour of the test for moderate sample sizes. It is found that our approach is generally more powerful than existing tests while holding its level throughout most of the parameter space and, thus, can be recommended. This agrees with theoretical results showing the superiority of the data driven smooth test approach in related contexts. [source] Z -scores and the birthweight paradoxPAEDIATRIC & PERINATAL EPIDEMIOLOGY, Issue 5 2009Enrique F. Schisterman Summary Investigators have long puzzled over the observation that low-birthweight babies of smokers tend to fare better than low-birthweight babies of non-smokers. Similar observations have been made with regard to factors other than smoking status, including socio-economic status, race and parity. Use of standardised birthweights, or birthweight z -scores, has been proposed as an approach to resolve the crossing of the curves that is the hallmark of the so-called birthweight paradox. In this paper, we utilise directed acyclic graphs, analytical proofs and an extensive simulation study to consider the use of z -scores of birthweight and their effect on statistical analysis. We illustrate the causal questions implied by inclusion of birthweight in statistical models, and illustrate the utility of models that include birthweight or z -scores to address those questions. Both analytically and through a simulation study we show that neither birthweight nor z -score adjustment may be used for effect decomposition. The z -score approach yields an unbiased estimate of the total effect, even when collider-stratification would adversely impact estimates from birthweight-adjusted models; however, the total effect could have been estimated more directly with an unadjusted model. The use of z -scores does not add additional information beyond the use of unadjusted models. Thus, the ability of z -scores to successfully resolve the paradoxical crossing of mortality curves is due to an alteration in the causal parameter being estimated (total effect), rather than adjustment for confounding or effect decomposition or other factors. [source] A New Method for Constructing Confidence Intervals for the Index CpmQUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 7 2004Michael Perakis Abstract In the statistical literature on the study of the capability of processes through the use of indices, Cpm appears to have been one of the most widely used capability indices and its estimation has attracted much interest. In this article, a new method for constructing approximate confidence intervals or lower confidence limits for this index is suggested. The method is based on an approximation of the non-central chi-square distribution, which was proposed by Pearson. Its coverage appears to be more satisfactory compared with that achieved by any of the two most widely used methods that were proposed by Boyles, in situations where one is interested in assessing a lower confidence limit for Cpm. This is supported by the results of an extensive simulation study. Copyright © 2004 John Wiley & Sons, Ltd. [source] | ||||||||||