Effect of the exposure to Fasciola hepatica (Trematoda: Digenea) on life history traits of Lymnaea cousini and Lymnaea columella (Gastropoda: Lymnaeidae)

The snails Lymnaea columella and Lymnaea cousini have both been reported as intermediate hosts of Fasciola hepatica in Colombia. The effect of the exposure to the parasite on survival, fecundity and size of these snails was evaluated by means of experimental infections and the life history traits of control and exposed groups were compared. Infection rates were 82.2 and 34% for L. columella and L. cousini, respectively. A reduction in fitness was observed in both species when exposed to the parasite: fecundity alone was reduced in L. columella whereas in L. cousini there was also a decline in survival rate. Unlike other studies, increased size was not observed in either species. On the contrary, a reduction in growth rate was observed in L. columella.     

Test-based exact confidence intervals for the difference of two binomial proportions

Confidence intervals are often provided to estimate a treatment difference. When the sample size is small, as is typical in early phases of clinical trials, confidence intervals based on large sample approximations may not be reliable. In this report, we propose test-based methods of constructing exact confidence intervals for the difference in two binomial proportions. These exact confidence intervals are obtained from the unconditional distribution of two binomial responses, and they guarantee the level of coverage. We compare the performance of these confidence intervals to ones based on the observed difference alone. We show that a large improvement can be achieved by using the standardized Z test with a constrained maximum likelihood estimate of the variance.     

Environmental Impacts of Products:Policy Relevant Information and Data Challenges

The research and analysis presented in this special issue shows that the same limited number of consumption categories are consistently revealed to be responsible for the largest share of environmental impact: mobility (automobile and air transport), food (meat, poultry, fish, and dairy followed by plant‐based food), and residential energy use in the house (heating, cooling, electrical appliances, and lighting). It appears that differences in impact per euro between the product groupings are relatively limited, so it is essential to reduce the life‐cycle impacts of products as such, rather than to shift expenditures to less impact‐intensive product groupings. Furthermore, the effectiveness of expenditure on material products to improve quality of life leaves much room for improvement. Environmentally extended input‐output (EEIO) tables probably form, in this field, the most appropriate information support tool for priority setting, prospective assessment of options, scenario analysis, and monitoring. A clear benefit would result from integrating the input–output (IO) tables in the report to Eurostat of the 25 individual countries that make up the European Union (EU), with other officially available information on emissions and resources use, into a 60‐sector EEIO table for the EU. This, obviously, would be the first step toward more detailed tables. Three strategies are suggested to realize the additional, desirable detail of 150 sectors or more, each achievable at an increasing time horizon and with increasing effort: (1) developing further the current CEDA EU25 table; (2) building a truly European detailed input–output table accepting the restrictions of existing data gathering procedures; and (3) as (2), but developing new, dedicated data gathering and classification procedures. In all cases, a key issue is harmonizing classification systems for industry sectors, consumer expenditure categories, and product classifications (as in import/export statistics) in such a way that data sets may adequately be linked to input–output tables.     

Correcting for heterogeneity and non-comparability bias in multicenter clinical trials with a rescaled random-effect excess hazard model

In the presence of competing causes of event occurrence (e.g., death), the interest might not only be in the overall survival but also in the so-called net survival, that is, the hypothetical survival that would be observed if the disease under study were the only possible cause of death. Net survival estimation is commonly based on the excess hazard approach in which the hazard rate of individuals is assumed to be the sum of a disease-specific and expected hazard rate, supposed to be correctly approximated by the mortality rates obtained from general population life tables. However, this assumption might not be realistic if the study participants are not comparable with the general population. Also, the hierarchical structure of the data can induces a correlation between the outcomes of individuals coming from the same clusters (e.g., hospital, registry). We proposed an excess hazard model that corrects simultaneously for these two sources of bias, instead of dealing with them independently as before. We assessed the performance of this new model and compared it with three similar models, using extensive simulation study, as well as an application to breast cancer data from a multicenter clinical trial. The new model performed better than the others in terms of bias, root mean square error, and empirical coverage rate. The proposed approach might be useful to account simultaneously for the hierarchical structure of the data and the non-comparability bias in studies such as long-term multicenter clinical trials, when there is interest in the estimation of net survival.     

A quantitative method for ranking the water quality tolerances of benthic species

This method compares relative tolerances of benthic organisms to levels of water pollutants using contingency table analyses. Ratings of the pollution tolerance of benthic species may thus be more accurately assigned, improving the previously proposed biotic indices. Preliminary application of this method utilizes six species of tubificid worms of the genera Limnodrilus and Tubifex, among which several trends in water tolerance seemed to have become apparent.Based on paper presented May 12, 1978 at the Twenty-sixth Annual Meeting of the North American Benthological Society, Winnipeg, Manitoba     

An Evaluation of Different Methods in Epidemiologic Studies of Radiation Risks

The probability of detecting possible late effects of ionizing radiation in human populations depends on the size of exposure in the study population and on the epidemiologic evaluation method used. This is not only due to the mathematical or statistical properties of the method, but also to the choice of the control population, which may be either external (usually large) or internal (usually not so large). Moreover, the use of a large external control population often results in an increasing influence of selection factors expressing themselves e.g. through the ‘healthy worker’ effect. In this paper three different methods usually employed in follow-up studies are reviewed: the calculation of Standardized Mortality Ratios (SMR), a contingency table analysis based on Person-Years (PY) and the comparison of Cumulative Mean Doses (CMD) within different subcohorts. The methods are illustrated with a simple radiation risk model; nevertheless, most of the conclusions apply to non-radiation risk studies as well. The CMD-method is shown to be heavily selection sensitive.     

Association,Symmetry and Diagonal Models for Occupational Mobility and Other Similar Square Contingency Tables Having Ordered Categorical Variables

This paper examines various association, symmetry and “diagonal band” class models for both the British and Danish social mobility data. Composite models are also fitted to these data and the variety of models considered ensures that for most square tables, parsimonious models within the class of models examined in this study can always be found that will adequately describe such tables. The models considered in this study, which have been described in various forms by Goodman (1984), Upton (1985) and Tomizawa (1986) can suit most square tables having ordered classificatory variables. A model selection procedure is also examined.