Estimation of population attributable fractions from fitted incidence ratios and exposure survey data, with an application to electromagnetic fields and childhood leukemia

Standard presentations of epidemiological results focus on incidence-ratio estimates derived from regression models fit to specialized study data. These data are often highly nonrepresentative of populations for which public-health impacts must be evaluated. Basic methods are provided for interval estimation of attributable fractions from model-based incidence-ratio estimates combined with independent survey estimates of the exposure distribution in the target population of interest. These methods are illustrated in estimation of the potential impact of magnetic-field exposures on childhood leukemia in the United States, based on pooled data from 11 case-control studies and a U.S. sample survey of magnetic-field exposures.     

Estimating the reliability of diet overlap measures

Synopsis Diet overlap measures, commonly used in studies of resource partitioning and competition in fish, are too often treated as fixed values; in fact, they are random variables. Two methods for estimating the variance of some overlap measures using stomach content data are examined here: the jackknife and the bootstrap. Simulation results indicate that the methods work well. In addition, they are valid for either continuous (biomass, percent volume) or discrete (abundance) data. Applications indicate that outliers, such as a stomach much different than others, may have large influence in determing the overlap value.     

Performance of nonparametric species richness estimators in a high diversity plant community

Abstract. The efficiency of four nonparametric species richness estimators — first‐order Jackknife, second‐order Jackknife, Chao2 and Bootstrap — was tested using simulated quadrat sampling of two field data sets (a sandy ‘Dune’ and adjacent ‘Swale’) in high diversity shrublands (kwongan) in south‐western Australia. The data sets each comprised > 100 perennial plant species and > 10 000 individuals, and the explicit (x‐y co‐ordinate) location of every individual. We applied two simulated sampling strategies to these data sets based on sampling quadrats of unit sizes 1/400th and 1/100th of total plot area. For each site and sampling strategy we obtained 250 independent sample curves, of 250 quadrats each, and compared the estimators’ performances by using three indices of bias and precision: MRE (mean relative error), MSRE (mean squared relative error) and OVER (percentage overestimation). The analysis presented here is unique in providing sample estimates derived from a complete, field‐based population census for a high diversity plant community. In general the true reference value was approached faster for a comparable area sampled for the smaller quadrat size and for the swale field data set, which was characterized by smaller plant size and higher plant density. Nevertheless, at least 15–30% of the total area needed to be sampled before reasonable estimates of S_t (total species richness) were obtained. In most field surveys, typically less than 1% of the total study domain is likely to be sampled, and at this sampling intensity underestimation is a problem. Results showed that the second‐order Jackknife approached the actual value of S_t more quickly than the other estimators. All four estimators were better than S_obs (observed number of species). However, the behaviour of the tested estimators was not as good as expected, and even with large sample size (number of quadrats sampled) all of them failed to provide reliable estimates. First‐ and second‐order Jackknives were positively biased whereas Chao2 and Bootstrap were negatively biased. The observed limitations in the estimators’ performance suggests that there is still scope for new tools to be developed by statisticians to assist in the estimation of species richness from sample data, especially in communities with high species richness.     

利用多重抽样估计稀有物种的种类数

利用矩估计和二个稳健估计方法（jackknife估计,bootstrap估计）来处理野外生态学工作者的调查数据,在假定已经发现一些稀有物种的情形下,通过统计推断得到那些未被发现的物种的种类数。利用本文所提出的方法调查水稻水稻田的昆虫群落和林地的在面植被群落的稀有种是十分有效的。     

Comparison of Resubstitution,Data Splitting,the Bootstrap,and the Jackknife as Methods for Estimating Validity Indices of New Marker Tests: A Monte Carlo Study

Estimating the diagnostic efficiency of marker tests on the basis of the training set is an intricate problem of discriminant analysis for which no analytical solution exists. The paper outline the problem, describes various popular estimation procedures and presents the results of computer simulations comparing the estimators with respect to both bias and variance.     

Estimation of contemporaneous mortality factors

We present methods for solving and making statistical inferences about marginal attack rates based on observed death rates for contemporaneous mortality factors. The general method of solution involves solving a system of nonlinear equations which depend in part on competition coefficients that express the outcome when more than one agent attacks the same host individual. For two factors, we present a detailed analysis of the effect of varying this competition coefficient. Statistical inferences are illustrated using standard large sample approximations (the delta method) and the bootstrap, which is a resampling technique. We also extend the results to allow inferences for k-values.