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Literary linguistics: Open Access research in English language

Strathprints makes available Open Access scholarly outputs by English Studies at Strathclyde. Particular research specialisms include literary linguistics, the study of literary texts using techniques drawn from linguistics and cognitive science.

The team also demonstrates research expertise in Renaissance studies, researching Renaissance literature, the history of ideas and language and cultural history. English hosts the Centre for Literature, Culture & Place which explores literature and its relationships with geography, space, landscape, travel, architecture, and the environment.

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Standard survey methods for estimating colony losses and explanatory risk factors in Apis mellifera

van der Zee, Romee and Gray, Alison and Holzmann, Celine and Pisa, Lennard and Brodschneider, Robert and Chlebo, Robert and Coffey, Mary F and Kence, Aykut and Kristiansen, Preben and Mutinelli, Franco and Nguyen, Bach Kim and Noureddine, Adjlane and Peterson, Magnus and Soroker, Victoria and Topolska, Grazyna and Vejsnaes, Flemming and Wilkins, Selwyn (2013) Standard survey methods for estimating colony losses and explanatory risk factors in Apis mellifera. In: Standard Methods for Apis mellifera Pest and Pathogen Research. The COLOSS BEEBOOK. ISBN 0860982750

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This chapter addresses survey methodology and questionnaire design for the collection of data pertaining to estimation of honey bee colony loss rates and identification of risk factors for colony loss. Sources of error in surveys are described. Advantages and disadvantages of different random and non-random sampling strategies and different modes of data collection are presented to enable the researcher to make an informed choice. We discuss survey and questionnaire methodology in some detail, for the purpose of raising awareness of issues to be considered during the survey design stage in order to minimise error and bias in the results. Aspects of survey design are illustrated using surveys in Scotland. Part of a standardized questionnaire is given as a further example, developed by the COLOSS working group for Monitoring and Diagnosis. Approaches to data analysis are described, focussing on estimation of loss rates. Dutch monitoring data from 2012 were used for an example of a statistical analysis with the public domain R software. We demonstrate the estimation of the overall proportion of losses and corresponding confidence interval using a quasi-binomial model to account for extra-binomial variation. We also illustrate generalized linear model fitting when incorporating a single risk factor, and derivation of relevant confidence intervals.