803 resultados para Probability sample


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There has been recent interest in the use of X-chromosomal loci for forensic and relatedness testing casework, with many authors developing new X-linked short tandem repeat (STR) loci suitable for forensic use. Here we present formulae for two key quantities in paternity testing, the average probability of exclusion and the paternity index, which are suitable for Xchromosomal loci in the presence of population substructure.

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This article assesses the extent to which sampling variation affects findings about Malmquist productivity change derived using data envelopment analysis (DEA), in the first stage by calculating productivity indices and in the second stage by investigating the farm-specific change in productivity. Confidence intervals for Malmquist indices are constructed using Simar and Wilson's (1999) bootstrapping procedure. The main contribution of this article is to account in the second stage for the information in the second stage provided by the first-stage bootstrap. The DEA SEs of the Malmquist indices given by bootstrapping are employed in an innovative heteroscedastic panel regression, using a maximum likelihood procedure. The application is to a sample of 250 Polish farms over the period 1996 to 2000. The confidence intervals' results suggest that the second half of 1990s for Polish farms was characterized not so much by productivity regress but rather by stagnation. As for the determinants of farm productivity change, we find that the integration of the DEA SEs in the second-stage regression is significant in explaining a proportion of the variance in the error term. Although our heteroscedastic regression results differ with those from the standard OLS, in terms of significance and sign, they are consistent with theory and previous research.

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At present, collective action regarding bio-security among UK cattle and sheep farmers is rare. Despite the occurrence of catastrophic livestock diseases such as bovine spongiform encephalopathy (BSE) and foot and mouth disease (FMD), within recent decades, there are few national or local farmer-led animal health schemes. To explore the reasons for this apparent lack of interest, we utilised a socio-psychological approach to disaggregate the cognitive, emotive and contextual factors driving bio-security behaviour among cattle and sheep farmers in the United Kingdom (UK). In total, we interviewed 121 farmers in South-West England and Wales. The main analytical tools included a content, cluster and logistic regression analysis. The results of the content analysis illustrated apparent 'dissonance' between bio-security attitudes and behaviour.(1) Despite the heavy toll animal disease has taken on the agricultural economy, most study participants were dismissive of the many measures associated with bio-security. Justification for this lack of interest was largely framed in relation to the collective attribution or blame for the disease threats themselves. Indeed, epidemic diseases were largely related to external actors and agents. Reasons for outbreaks included inadequate border control, in tandem with ineffective policies and regulations. Conversely, endemic livestock disease was viewed as a problem for 'bad' farmers and not an issue for those individuals who managed their stock well. As such, there was little utility in forming groups to address what was largely perceived as an individual problem. Further, we found that attitudes toward bio-security did not appear to be influenced by any particular source of information per se. While strong negative attitudes were found toward specific sources of bio-security information, e.g. government leaflets, these appear to simply reflect widely held beliefs. In relation to actual bio-security behaviours, the logistic regression analysis revealed no significant difference between in-scheme and out of scheme farmers. We concluded that in order to support collective action with regard to bio-security, messages need to be reframed and delivered from a neutral source. Efforts to support group formation must also recognise and address the issues relating to perceptions of social connectedness among the communities involved. (c) 2008 Elsevier B.V. All rights reserved.

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The steadily accumulating literature on technical efficiency in fisheries attests to the importance of efficiency as an indicator of fleet condition and as an object of management concern. In this paper, we extend previous work by presenting a Bayesian hierarchical approach that yields both efficiency estimates and, as a byproduct of the estimation algorithm, probabilistic rankings of the relative technical efficiencies of fishing boats. The estimation algorithm is based on recent advances in Markov Chain Monte Carlo (MCMC) methods—Gibbs sampling, in particular—which have not been widely used in fisheries economics. We apply the method to a sample of 10,865 boat trips in the US Pacific hake (or whiting) fishery during 1987–2003. We uncover systematic differences between efficiency rankings based on sample mean efficiency estimates and those that exploit the full posterior distributions of boat efficiencies to estimate the probability that a given boat has the highest true mean efficiency.

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This paper presents a case study to illustrate the range of decisions involved in designing a sampling strategy for a complex, longitudinal research study. It is based on experience from the Young Lives project and identifies the approaches used to sample children for longitudinal follow-up in four less developed countries (LDCs). The rationale for decisions made and the resulting benefits, and limitations, of the approaches adopted are discussed. Of particular importance is the choice of sampling approach to yield useful analysis; specific examples are presented of how this informed the design of the Young Lives sampling strategy.