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Small area estimation under informative sampling
No full textIn this article we show how to predict small area means and compute valid MSE estimators in situations where the areas represented in the sample are sampled with unequal probabilities that are possibly related to the true (unknown) area means, and the sampling of units within the selected areas is with probabilities that are possibly related to the outcome values. We illustrate the proposed procedures by means of a simulation study
Prediction of finite population totals based on the sample distribution
No full textThis article studies the use of the sample distribution for the prediction of finite population totals under single-stage sampling. The proposed predictors employ the sample values of the target study variable, the sampling weights of the sample units and possibly known population values of auxiliary variables. The prediction problem is solved by estimating the expectation of the study values for units outside the sample as a function of the corresponding expectation under the sample distribution and the sampling weights. The prediction mean square error is estimated by a combination of an inverse sampling procedure and a re-sampling method. An interesting outcome of the present analysis is that several familiar estimators in common use are shown to be special cases of the proposed approach, thus providing them a new interpretation. The performance of the new and some old predictors in common use is evaluated and compared by a Monte Carlo simulation study using a real data set
Small Area Estimation Under Informative Sampling
No full textThis article proposes two approaches for small area estimation under informative sampling. The semi-parametric approach makes no assumptions regarding the relationship between the area selection probabilities and the true area means. The proposed predictors under this approach are approximately unbiased for both the sampled and nonsampled areas but the prediction RMSEs can be large particularly for nonsampled areas. The parametric approach models the relationship between the area selection probabilities and the area means and incorporates this relationship into the model for the study variable. As illustrated by a simulation study, the use of this approach can reduce the RMSEs quite significantly
Small area estimation under informative probability sampling of areas and within the selected areas
No full textIn this article we show how to predict small area means and obtain valid MSE estimators and confidence intervals when the areas represented in the sample are sampled with unequal probabilities that are possibly related to the true (unknown) area means, and the sampling of units within the selected areas is with probabilities that are possibly related to the outcome values. Ignoring the effects of the sampling process on the distribution of the observed outcomes in such cases may bias the inference very severely. Classical design based inference that uses the randomization distribution of probability weighted estimators cannot be applied for predicting the means of nonsampled areas. We propose simple test statistics for testing the informativeness of the selection of the areas and the sampling of units within the selected areas. The proposed procedures are illustrated by a simulation study and a real application of estimating mean body mass index in counties of the U.S.A, using data from the NHANES III survey
Estimation of mean squared error of X-11-ARIMA and other estimators of time series components
No full textThis article considers the familiar but very important problem of how to estimate the mean squared error (MSE) of seasonally adjusted and trend estimators produced by X-11-ARIMA or other decomposition methods. The MSE estimators are obtained by defining the unknown target components such as the trend and seasonal effects to be the hypothetical X-11 estimates of them that would be obtained if there were no sampling errors and the series were sufficiently long to allow the use of the symmetric filters embedded in the programme, which are time invariant. This definition of the component series conforms to the classical definition of the target parameters in design-based survey sampling theory, so that users should find it comfortable to adjust to this definition. The performance of the MSE estimators is assessed by a simulation study and by application to real series obtained from an establishment survey carried out by the Bureau of Labor Statistics in the U.S.A
Small area estimation under informative sampling and not missing at random nonresponse
No full textPfeffermann and Sverchkov considered small area estimation for the case where the selection of the sampled areas is informative in the sense that the area sampling probabilities are related to the true (unknown) area means, and the sampling of units within the selected areas is likewise informative with probabilities that are related to the values of the study variable, in both cases after conditioning on the model covariates. We extend this approach to the practical situation of incomplete response at the unit level, and where the response is not missing at random.The proposed extension consists of first identifying the model holding for the observed responses and using the model for estimating the response probabilities, and then applying the approach of Pfeffermann and Sverchkov to the observed data with the unit sampling probabilities replaced by the products of the sampling probabilities and the estimated response probabilities. A bootstrap procedure for estimating the mean-squared error of the proposed predictors is developed. We illustrate our approach by a simulation study and by application to a real dataset. The simulations also illustrate the consequences of not accounting for informative samplingand/or non-response
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
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