1,721,039 research outputs found
Small area estimation using multilevel models
No full textMixed Models have been shown to be useful for improving the efficiency of the small area estimates. Battese Harter and Fuller (1981) have proposed the random intercept model for making small area estimates. Prasad and Rao(1990) have studied model-based properties of some mixed linear small area estimators and provided approximate expression for the Mean Square Error (MSE) of each small area estimate and a corresponding MSE estimator. Model-based simulation studies (Prasad and Rao(1990) ) as well as design-based simulation studies (Ghosh and Rao(1993) ) show the superiority of mixed-models over conventional approaches.The first aim of this thesis is to extend Prasad and Rao's(1990) results obtained for the random intercept model in two ways: (a) allowing all regression coefficients to be random and (b) introducing small area level auxiliary covariates which help to model the between area components of variance. Small area predictors are also provided together with an approximation to the MSE for each small area and an estimator for the MSE.The second aim is to derive design-based precision measurements of the small area predictors and their corresponding estimators.Model-based simulation studies carried out using real data sets show that the extra random components can improve the small area estimates and the MSE approximation is satisfactory. Further numerical results, within the repeated sampling framework demonstrate that underlying model assumptions are important and the use of small area level variables are preferable to explain some of the small area intra-class correlation rather than simply treating them as unexplained sources of variation. (DX184,267)</p
Small area estimation under a two-part random effects model with application to estimation of literacy in developing countries
No full textThis paper considers situations where the target response value is either zero or an observation from a continuous distribution. A typical example analyzed in the paper is the assessment of literacy proficiency with the possible outcome being either zero, indicating illiteracy, or a positive score measuring the level of literacy. Our interest is in how to obtain valid estimates of the average response, or the proportion of positive responses in small areas, for which only small samples or no samples are available. As in other small area estimation problems, the small sample sizes in at least some of the sampled areas and/or the existence of nonsampled areas requires the use of model based methods. Available methods, however, are not suitable for this kind of data because of the mixed distribution of the responses, having a large peak at zero,juxtaposed to a continuous distribution for the rest of the responses. We develop, therefore, a suitable two-part random effects model and show how to fit the model and assess its goodness of fit, and how to compute the small area estimators of interest and measure their precision. The proposed method is illustrated using simulated data and data obtained from a literacy survey conducted in Cambodia
Multi-level Modelling Under Informative Sampling
No full textWe consider a model dependent approach for multi-level modelling that accounts for informative probability sampling, and compare it with the use of probability weighting as proposed by Pfeffermann et al. (1998a). The new modelling approach consists of first extracting the hierarchical model holding for the sample data as a function of the corresponding population model and the first and higher level sample selection probabilities, and then fitting the resulting sample model using Bayesian methods. An important implication of the use of this approach is that the sample selection probabilities feature in the analysis as additional outcome values that strengthen the estimators. A simulation experiment is carried out in order to study and compare the performance of the two approaches. The simulation study indicates that both approaches perform generally equally well in terms of point estimation, but the model dependent approach yields confidence (credibility) intervals with better coverage properties. A robustness simulation study is performed, which allows to assess the impact of misspecification of the models assumed for the sample selection probabilities under informative sampling schemes
Small area estimation under a two part random effects model with application to estimation of literacy in developing countries
No full textThe UNESCO Institute for Statistics has initiated a programme to collect data on the level of literacy of adults in developing countries. This will involve conducting small-scale surveys in a few countries that will consist of giving interviewees aged 15+ a test to measure their literacy score. One of the main objectives of these surveys is to obtain summary measures of literacy levels in small geographical areas for which only very small samples would be available, thus requiring the use of model based small area estimation methods.Available methods are not suitable, however, for this kind of data due to the mixed distribution of the literacy scores in developing countries. This distribution has a large peak at zero, i.e., a large proportion of adults that are illiterate, and juxtaposed to this peak is an approximately bell-shaped distribution of the non-zero scores measured for the rest of the sample.In this paper we develop a two part three-level model that is suitable for this kind of data and show how to obtain the small area measures and their variances, or compute confidence intervals, based on this model. The proposed method is illustrated using simulated data and data obtained from a similar literacy survey conducted in Cambodia. <br/
Small area estimation under varying area boundaries using the synthetic estimator
No full textThis paper investigates the use of hierarchical models for small area estimation with varying area boundaries, employing the synthetic estimator. The paper shows how area estimates and corresponding MSE estimates can be obtained at a variety of nested and intersecting boundary systems by fitting a model at the lowest possible level. The estimates are obtained by aggregating from the lowest level and are therefore internally consistent. The methodology is illustrated by presenting results of a simulation study that uses hierarchical models built at the lowest area level defined by the UK 1991 census
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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