ISSN:0319-5724    

DOI:10.1002/cjs.5550220101

出版商:Wiley‐Blackwell    

年代:1994

数据来源: WILEY

摘要:

AbstractThis paper presents results from a simulation study motivated by a recent study of the relationships between ambient levels of air pollution and human health in the community of Prince George, British Columbia. The simulation study was designed to evaluate the performance of methods based on overdispersed Poisson regression models for the analysis of series of count data. Aspects addressed include estimation of the dispersion parameter, estimation of regression coefficients and their standard errors, and the performance of model selection tests. The effects of varying amounts of overdispersion and differing underlying variance structure on this performance were of particular interest. This study is related to work reported by Breslow (1990) although the context is quite different. Preliminary work led to the conclusion that estimation of the dispersion parameter should be based on Pearson's chi‐square statistic rather than the Poisson deviance. Regression coefficients are well estimated, even in the présence of substantial overdispersion and when the model for the variance function is incorrectly specified. Despite potential greater variability, the empirical estimator of the covariance matrix is preferred because the model‐based estimator is unreliable in general. When the model for the variance function is incorrect, model‐based test statistics may perform poorly, in sharp contrast to empirical test statistics, which performed very well in this

ISSN:0319-5724    

DOI:10.2307/3315402

出版商:Wiley‐Blackwell    

年代:1994

数据来源: WILEY

摘要:

AbstractStatistical methods are proposed to analyze parallel time series of hospital‐based health data and measurements of ambient air pollution. Specifically, associations between the number of daily health events (hospital admissions or emergency‐room visits for respiratory illnesses) and daily levels of ambient air pollutants in the vicinity of several hospitals are examined. A relative‐risk regression model is proposed in which the regression parameters are assumed to vary at random among hospitals. Adjustment for seasonal trends in admissions are also considered. Simple computational methods based on generalized estimating equations are explored as the basis for statistical inference. The proposed methods are illustrated on data obtained from 164 acute‐care hospitals in Ontario over the May‐to‐August period for 1983 to 1988. These admission rates are related to ozone levels obtained from 22 monitoring stations maintained by the Ontario Ministry of the

ISSN:0319-5724    

DOI:10.2307/3315403

出版商:Wiley‐Blackwell    

年代:1994

数据来源: WILEY

摘要:

AbstractIn recent years, considerable attention has been devoted to methods for analyzing longitudinal data. A review of some of the issues surrounding the use of regression analysis is undertaken as they relate to a study of the health effects of air pollution in a group of asthmatics. Daily diary recordings of hours with asthma symptoms are found to be positively related to the daily mean concentration of total reduced sulphur as well as to the daily intake of nonsteroidal drug medication. This finding is corroborated using three different statistical models.

ISSN:0319-5724    

DOI:10.2307/3315404

出版商:Wiley‐Blackwell    

年代:1994

数据来源: WILEY

摘要:

AbstractWhile most of epidemiology is observational, rather than experimental, the culture of epidemiology is still derived from agricultural experiments, rather than other observational fields, such as astronomy or economics. The mismatch is made greater as focus has turned to continue risk factors, multifactorial outcomes, and outcomes with large variation unexplainable by available risk factors. The analysis of such data is often viewed as hypothesis testing with statistical control replacing randomization. However, such approaches often test restricted forms of the hypothesis being investigated, such as the hypothesis of a linear association, when there is no prior empirical or theoretical reason to believe that if an association exists, it is linear. In combination with the large nonstochastic sources of error in such observational studies, this suggests the more flexible alternative of exploring the association. Conclusions on the possible causal nature of any discovered association will rest on the coherence and consistency of multiple studies. Nonparametric smoothing in general, and generalized additive models in particular, represent an attractive approach to such problems. This is illustrated using data examining the relationship between particulate air pollution and daily mortality in Birmingham, Alabama; between particulate air pollution, ozone, and SO2and daily hospital admissions for respiratory illness in Philadelphia; and between ozone and particulate air pollution and coughing episodes in children in six eastern U.S. cities. The results indicate that airborne particles and ozone are associated with adverse health outcomes at very low concentrations, and that there are likely no thresholds for these relationships.

ISSN:0319-5724    

DOI:10.2307/3315405

出版商:Wiley‐Blackwell    

年代:1994

数据来源: WILEY

摘要:

AbstractWe develop and apply an approach to the spatial interpolation of a vector‐valued random response field. The Bayesian approach we adopt enables uncertainty about the underlying models to be représentés in expressing the accuracy of the resulting interpolants. The methodology is particularly relevant in environmetrics, where vector‐valued responses are only observed at designated sites at successive time points. The theory allows space‐time modelling at the second level of the hierarchical prior model so that uncertainty about the model parameters has been fully expressed at the first level. In this way, we avoid unduly optimistic estimates of inferential accuracy. Moreover, the prior model can be upgraded with any available new data, while past data can be used in a systematic way to fit model parameters. The theory is based on the multivariate normal and related joint distributions. Our hierarchical prior models lead to posterior distributions which are robust with respect to the choice of the prior (hyperparameters). We illustrate our theory with an example involving monitoring stations in southern Ontario, where monthly average levels of ozone, sulphate, and nitrate are available and between‐station response triplets are interpolated. In this example we use a recently developed method for interpolating spatial correlati

ISSN:0319-5724    

DOI:10.2307/3315406

出版商:Wiley‐Blackwell    

年代:1994

数据来源: WILEY

摘要:

AbstractA model involving autocorrelated random effects and sampling errors is proposed for small‐area estimation, using both time‐series and cross‐sectional data. The sampling errors are assumed to have a known block‐diagonal covariance matrix. This model is an extension of a well‐known model, due to Fay and Herriot (1979), for cross‐sectional data. A two‐stage estimator of a small‐area mean for the current period is obtained under the proposed model with known autocorrelation, by first deriving the best linear unbiased prediction estimator assuming known variance components, and then replacing them with their consistent estimators. Extending the approach of Prasad and Rao (1986, 1990) for the Fay‐Herriot model, an estimator of mean squared error (MSE) of the two‐stage estimator, correct to a second‐order approximation for a small or moderate number of time points,T, and a large number of small areas,m, is obtained. The case of unknown autocorrelation is also considered. Limited simulation results on the efficiency of two‐stage estimators and the accuracy of the proposed estimat

ISSN:0319-5724    

DOI:10.2307/3315407

出版商:Wiley‐Blackwell    

年代:1994

数据来源: WILEY

摘要:

AbstractThe extent to which cancer will be a burden on the Canadian health‐care system will be determined by future cancer rates and future population levels in the high‐risk age groups. Parametric models of incidence and mortality rates for various cancers may be used to obtain medium‐term forecasts of rates, which then can be used in conjunction with population projections to obtain forecasts of total incidence and mortality. Age‐period‐cohort cancer data often exhibit marked heteroscedasticity, which complicates the modeling of the data. Methods to allow for the effects of this heteroscedasticity on residual processes are developed and discussed in the context of modeling Canadian female breast‐cancer inc

ISSN:0319-5724    

DOI:10.2307/3315408

出版商:Wiley‐Blackwell    

年代:1994

数据来源: WILEY