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Verena Puchner evaluates and compares statistical matching and selected SAE methods. Due to the fact that poverty estimation at regional level based on EU-SILC samples is not of adequate accuracy, the quality of the estimations should be improved by additionally incorporating micro census data. The aim is to find the best method for the estimation of poverty in terms of small bias and small variance with the aid of a simulated artificial "close-to-reality" population. Variables of interest are imputed into the micro census data sets with the help of the EU-SILC samples through regression models including selected unit-level small area methods and statistical matching methods. Poverty indicators are then estimated. The author evaluates and compares the bias and variance for the direct estimator and the various methods. The variance is desired to be reduced by the larger sample size of the micro census.
The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.
RealWorld Evaluation: Working Under Budget, Time, Data, and Political Constraints addresses the challenges of conducting program evaluations in real-world contexts where evaluators and their clients face budget and time constraints. The book is organized around the authors’ seven-step model that has been tested in workshops and practice environments to help the evaluation implementers and managers make the best choices when faced with real world constraints. The Third Edition includes a new chapter on gender equality and women’s empowerment and discussion of digital technology and data science.
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A practical `cut to the chase′ handbook that quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision-making in a wide variety of disciplines. In this one-stop reference, the authors provide succinct guidelines for performing an analysis, avoiding pitfalls, interpreting results and reporting outcomes.
Includes subject section, name section, and 1968-1970, technical reports.
"Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases."--Publisher's description.