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Data collection systems. --- Frequencies of oscillating systems.

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This book provides a unified framework of web scraping and information extraction from text data with R for the social sciences.

Data mining. --- Automatic data collection systems. --- Social sciences --- R (Computer program language). --- Computers --- Research --- Data processing. --- Database Management --- Data Mining.

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This paper is a practical guide for researchers and practitioners who want to understand spillover effects in program evaluation. The paper defines spillover effects and discusses why it is important to measure them. It explains how to design a field experiment to measure the average effects of the treatment on eligible and ineligible subjects for the program in the presence of spillover effects. In addition, the paper discusses the use of nonexperimental methods for estimating spillover effects when the experimental design is not a viable option. Evaluations that account for spillover effects should be designed such that they explain the cause of these effects and whom they affect. Such an evaluation design is necessary to avoid inappropriate policy recommendations and neglecting important mechanisms through which the program operates.

Data Collection --- Disease Control & Prevention --- Field Experiments --- Impact Evaluation --- Indirect Treatment Effect --- Labor Policies --- Population Policies --- Program Mechanisms --- Science Education --- Scientific Research & Science Parks --- Spillover Effects

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Consumption of food away from home is rapidly growing across the developing world. Surprisingly, the majority of household surveys around the world haven not kept up with its pace and still collect limited information on it. The implications for poverty and inequality measurement are far from clear, and the direction of the impact cannot be established a priori, since consumption of food away from home affects both food consumption and the poverty line. This paper exploits rich data on food away from home collected as part of the National Household Survey in Peru, shedding light to the extent to which welfare measures differ depending on whether they properly account for food away from home. Peru is a relevant context, with the average Peruvian household spending 28 percent of their food budget on food away from home by 2010. The analysis indicates that failure to account for the consumption of food away from home has important implications for poverty and inequality measures as well as the understanding of who the poor are. First, accounting for food away from home results in extreme poverty rates that are 18 percent higher and moderate poverty rates that are 16 percent lower. These results are also consistent, in fact more pronounced, with poverty gap and severity measures. Second, consumption inequality measured by the Gini coefficient decreases by 1.3 points when food away from home is included, a significant reduction. Finally, inclusion of food away from home results in a reclassification of households from poor to non-poor status and vice versa: 20 percent of the poor are different when the analysis includes consumption of food away from home. This effect is large enough that a standard poverty profile analysis results in significant differences between the poverty classification based on whether food away from home is included or not. The differences cover many dimensions, including demographics, education, and labor market characteristics. Taken together, the results indicate that a serious rethinking of how to deal with the consumption of food away from home in measuring well-being is urgently needed to properly estimate and understand poverty around the world.

Data Collection --- Food & Beverage Industry --- Food Consumption --- Industry --- Inequality --- Macroeconomics and Economic Growth --- Poverty --- Poverty Lines --- Poverty Reduction --- Rural Poverty Reduction --- Welfare Measurement

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A patient–reported outcome (PRO) draws on patients’ answers to a series of questions in order to quantify their views on their own health. The purpose of PROs is to get patients′ own assessment of their health and health–related quality of life. The aim of this new title is to provoke and encourage thinking about the wide range of ways in which PRO data, routinely collected in the context of health service delivery, can be used to inform decisions, for example; What opportunities do these data present?What are the limitations of PROs, and what are the possible pitfalls in the use and interpretation of data produced from them?What work needs to be done in order to get the most out of PRO data?What have been the experiences of the English NHS with its PROs programme and what can other health systems learn?Using Patient Reported Outcomes to Improve Health Care provides an overview and explanation of PRO instruments and how PROs data might be used by patients in choosing both where to receive treatment, and also what treatment is best for them.Throughout this book, and drawing on international examples, the Authors consider ways in which the collected data can be used to transform decision–making in healthcare organisations, by those who commission health care and assess value for money, and also how data can be used to benchmark and improve clinical performance. The authors also discuss how clinicians on a more day to day level might use data to guide referral practices, ensuring that the people who receive health care are those that will benefit from it the most.This new title is the only resource to exclusively introduce, explain and show how PROs can be best used to improve healthcare and patient outcomes. Includes real life examples and case studies of PROs in practiceAssesses the growing evidence base for PROs in practiceEditor team from Office of Health Economics (OHE), The King′s Fund and King’s College London with contributions from practising clinicians, GPs and other healthcare professionals

Patient Outcome Assessment --- Delivery of Health Care --- Quality Improvement --- Data Collection --- organization & administration --- Patient outcomes --- W 84.4 Quality of health care (General) --- Data Collection. --- Patient Outcome Assessment. --- Quality Improvement. --- organization & administration. --- Health Care --- Patient Care Management --- Patient Participation --- Physician-Patient Relations --- Professional-Patient Relations