Livres sur le sujet « Form Error Evaluation »

The textbook includes topics of modern econometrics, often used in economic research. Some aspects of multiple regression models related to the problem of multicollinearity and models with a discrete dependent variable are considered, including methods for their estimation, analysis, and application. A significant place is given to the analysis of models of one-dimensional and multidimensional time series. Modern ideas about the deterministic and stochastic nature of the trend are considered. Methods of statistical identification of the trend type are studied. Attention is paid to the evaluation, analysis, and practical implementation of Box — Jenkins stationary time series models, as well as multidimensional time series models: vector autoregressive models and vector error correction models. It includes basic econometric models for panel data that have been widely used in recent decades, as well as formal tests for selecting models based on their hierarchical structure. Each section provides examples of evaluating, analyzing, and testing models in the R software environment. Meets the requirements of the Federal state educational standards of higher education of the latest generation. It is addressed to master's students studying in the Field of Economics, the curriculum of which includes the disciplines Econometrics (advanced course)", "Econometric modeling", "Econometric research", and graduate students."

Chapter 41 concerns unilateral mistakes. A unilateral mistake is a transient mental blunder that results from an error in the mechanics of an actor’s mental machinery, such as incorrectly adding a column of figures. Mistakes of these kinds are referred to in this book as mechanical errors. Mechanical errors differ from evaluative mistakes in several critical respects. For one thing, unlike evaluative mistakes the prospect that a counterparty will make a mechanical error normally is not a risk that is bargained for. And unlike evaluative mistakes, relief for mechanical errors would not undermine the very idea of promise: A promisor who seeks relief on the ground of a mechanical error does not assert that all things considered she doesn’t wish to perform. Rather, she asserts that she has a morally acceptable excuse that is well within the systemics of promise.

The total survey error (TSE) approach is a useful schema for organizing the planning and evaluation of surveys. It classifies the several possible types of errors in surveys, including in respondent selection, response accuracy, and survey administration. While the goal is to minimize these errors, the TSE approach emphasizes that this must be done within limitations imposed by several constraints: the cost of minimizing each type of error, the time requirements for the survey, and ethical standards. In addition to survey errors and constraints, there are several survey effects for which there are no error-free solutions; the size of these effects can be studied even though they cannot be eliminated. The total survey quality (TSQ) approach further emphasizes the need for survey organizations to maximize the quality of the product they deliver to their clients, within the context of TSE tradeoffs between survey errors and costs.

From Montaigne’s essay “On Friendship” to popular philosophy of the mid twentieth and early twenty-first centuries (C.S. Lewis’ The Four Loves and Joseph Epstein’s Friendship: An Exposé) to scholarship of the past few decades, this chapter shows how such texts rely to varying degrees upon the binarisms true/false, correct/incorrect, right/wrong in their descriptions and evaluations of Roman friendship. This chapter asks not whether this or that modern text gets ancient Rome wrong, but rather how Rome, evaluated as right or wrong, functions as a vehicle for these texts’ meanings, and also what might be some of the implications for a topic so freighted with larger social, cultural, and political significance over the course of its centuries-long reception. Finally, although its readings of amicitia avoid applying evaluative labels, this chapter asks to what extent its readings of later readings of Roman friendship do (must?) nonetheless appeal to some concept of error.

The CART principles are essential for designing a right-fit impact evaluation. This chapter explains what it means to conduct credible, actionable, responsible, and transportable impact evaluation. To ensure that impact evaluations follow the CART principles, organizations ought to strive for bias-free data collection and analysis. Bias (systematic error that favors one measure over another) may come from the way data are collected (question wording influences responses), or the way they are analyzed (e.g., influence of external factors or how people are selected into programs). In many cases, an randomizied control trial (RCT) helps generate a credible impact evaluation. In the simplest version of an RCT, individuals are randomly assigned to treatment and control groups. However, in special circumstances, other quasi-experimental evaluation methods can be successful. Actionable impact evaluation requires that organizations commit to learn from the undertaking and act on the results, even if they are disappointing. Organizations can make sure an evaluation is responsible by weighing how much it costs relative to its expected benefits. This chapter also addresses common criticisms about RCTs and identifies some strategies for reducing their cost. Finally, the chapter explains that the transportable principle mandates that evaluations produce useful evidence for others.

Geriatric Forensic Psychiatry: Principles and Practice is one of the first texts to provide a comprehensive review of important topics in the intersection of geriatric psychiatry, medicine, clinical neuroscience, forensic psychiatry, and law. It will speak to a broad audience among varied fields, including clinical and forensic psychiatry and mental health professionals, geriatricians and internists, attorneys and courts, regulators, and other professionals working with the older population. Topics addressed in this text, applied to the geriatric population, include clinical forensic evaluation, regulations and laws, civil commitment, different forms of capacity, guardianship, patient rights, medical-legal issues related to treatment, long term care and telemedicine, risk management, patient safety and error reduction, elder driving, sociopathy and aggression, offenders and the adjudication process, criminal evaluations, corrections, ethics, culture, cognitive impairment, substance abuse, trauma, older professionals, high risk behavior, and forensic mental health training and research. Understanding the relationship between clinical issues, laws and regulations, and managing risk and improving safety, will help to serve the growing older population.

In a perfect optical system, a point source of light is focused onto a single point on the image plane; in the eye, light is focused on the retina. Optical aberrations are caused by imaging system imperfections which cause deviations in the transmission of light, preventing the convergence of light to a single point of focus. In recent years an increased understanding of higher-order wavefront aberrations has allowed improvements in both the measurement and treatment of refractive error. This chapter discusses refractive surgery. It details refractive error, aberrations, and presbyopia, along with preoperative evaluation for refractive surgery, laser refractive surgery, other corneal refractive procedures, refractive lens surgery, intraocular lenses, phakic intraocular lenses, and presbyopia correction.

Chapter 3 provides a brief overview of null hypothesis significance testing and points out its primary defects. It then outlines the neo-Fisherian account of tests of statistical significance, along with a second option contained in the philosophy of statistics known as the error-statistical philosophy, both of which are defensible. Tests of statistical significance are the most widely used means for evaluating hypotheses and theories in psychology. A massive critical literature has developed in psychology, and the behavioral sciences more generally, regarding the worth of these tests. The chapter provides a list of important lessons learned from the ongoing debates about tests of significance.

Without high-quality data, even the best-designed monitoring and evaluation systems will collapse. Chapter 7 introduces some the basics of collecting high-quality data and discusses how to address challenges that frequently arise. High-quality data must be clearly defined and have an indicator that validly and reliably measures the intended concept. The chapter then explains how to avoid common biases and measurement errors like anchoring, social desirability bias, the experimenter demand effect, unclear wording, long recall periods, and translation context. It then guides organizations on how to find indicators, test data collection instruments, manage surveys, and train staff appropriately for data collection and entry.

A discrepancy between standard economic assumptions and observed behavior centers around individual preferences, which are assumed to be well ordered and consistent, but descriptively shown to be inconsistent and malleable. Not having at their disposal a reliable procedure for assigning values to options, people construct their preferences in the context of decision. As a result, the attractiveness of options depends on, among other things, the nature of other options in the set, the procedure used to express preference, the context of evaluation, and the decision-maker’s self-conception. The varieties of psychological experience underlying preference inconsistency are reviewed, and their implications are discussed. Preference inconsistency, it is proposed, is the outcome not of distracted shortcuts or avoidable errors, but of fundamental aspects of mental life that are central to how people process information. Although people endorse basic consistency criteria, their preferences are inherently inconsistent, with important implications for policy and welfare.

Abstract Qualitative interviewing has today become one of the most common research methods across the human and social sciences, if not the most prevalent approach, but it is an approach that comes in a huge amount of different guises. Qualitative Interviewing will help its readers conduct, write, represent, understand, and critique qualitative interview research in its many forms as currently practiced. This book does not simply tell its reader how to employ a method, but educates by showing and discussing excellent exemplars of qualitative interview research. The book begins with a theoretically informed introduction to qualitative interviewing by presenting a variegated landscape of how conversations have been used for knowledge producing purposes. Particular attention is given to the complementary positions of experience focused interviewing (phenomenological positions) and language-focused interviewing (discourse-oriented positions), which focus on interview talk as reports (of the experiences of interviewees) and accounts (occasioned by the situation of interviewing), respectively. The following chapters address different ways of designing and conducting qualitative interview studies and how to write up the methodological procedures of an interview study and also the research findings. The book finally discusses a number of the most common errors in interview reports and offers a range of solutions and also strategies for evaluating research findings based on qualitative interviews.

The quality of data collected in official spatial databases is crucial in making strategic decisions as well as in the implementation of planning and design works. Awareness of the level of the quality of these data is also important for individual users of official spatial data. The author presents methods and models of description and evaluation of the quality of spatial data collected in public registers. Data describing the space in the highest degree of detail, which are collected in three databases: land and buildings registry (EGiB), geodetic registry of the land infrastructure network (GESUT) and in database of topographic objects (BDOT500) were analyzed. The results of the research concerned selected aspects of activities in terms of the spatial data quality. These activities include: the assessment of the accuracy of data collected in official spatial databases; determination of the uncertainty of the area of registry parcels, analysis of the risk of damage to the underground infrastructure network due to the quality of spatial data, construction of the quality model of data collected in official databases and visualization of the phenomenon of uncertainty in spatial data. The evaluation of the accuracy of data collected in official, large-scale spatial databases was based on a representative sample of data. The test sample was a set of deviations of coordinates with three variables dX, dY and Dl – deviations from the X and Y coordinates and the length of the point offset vector of the test sample in relation to its position recognized as a faultless. The compatibility of empirical data accuracy distributions with models (theoretical distributions of random variables) was investigated and also the accuracy of the spatial data has been assessed by means of the methods resistant to the outliers. In the process of determination of the accuracy of spatial data collected in public registers, the author’s solution was used – resistant method of the relative frequency. Weight functions, which modify (to varying degree) the sizes of the vectors Dl – the lengths of the points offset vector of the test sample in relation to their position recognized as a faultless were proposed. From the scope of the uncertainty of estimation of the area of registry parcels the impact of the errors of the geodetic network points was determined (points of reference and of the higher class networks) and the effect of the correlation between the coordinates of the same point on the accuracy of the determined plot area. The scope of the correction was determined (in EGiB database) of the plots area, calculated on the basis of re-measurements, performed using equivalent techniques (in terms of accuracy). The analysis of the risk of damage to the underground infrastructure network due to the low quality of spatial data is another research topic presented in the paper. Three main factors have been identified that influence the value of this risk: incompleteness of spatial data sets and insufficient accuracy of determination of the horizontal and vertical position of underground infrastructure. A method for estimation of the project risk has been developed (quantitative and qualitative) and the author’s risk estimation technique, based on the idea of fuzzy logic was proposed. Maps (2D and 3D) of the risk of damage to the underground infrastructure network were developed in the form of large-scale thematic maps, presenting the design risk in qualitative and quantitative form. The data quality model is a set of rules used to describe the quality of these data sets. The model that has been proposed defines a standardized approach for assessing and reporting the quality of EGiB, GESUT and BDOT500 spatial data bases. Quantitative and qualitative rules (automatic, office and field) of data sets control were defined. The minimum sample size and the number of eligible nonconformities in random samples were determined. The data quality elements were described using the following descriptors: range, measure, result, and type and unit of value. Data quality studies were performed according to the users needs. The values of impact weights were determined by the hierarchical analytical process method (AHP). The harmonization of conceptual models of EGiB, GESUT and BDOT500 databases with BDOT10k database was analysed too. It was found that the downloading and supplying of the information in BDOT10k creation and update processes from the analyzed registers are limited. An effective approach to providing spatial data sets users with information concerning data uncertainty are cartographic visualization techniques. Based on the author’s own experience and research works on the quality of official spatial database data examination, the set of methods for visualization of the uncertainty of data bases EGiB, GESUT and BDOT500 was defined. This set includes visualization techniques designed to present three types of uncertainty: location, attribute values and time. Uncertainty of the position was defined (for surface, line, and point objects) using several (three to five) visual variables. Uncertainty of attribute values and time uncertainty, describing (for example) completeness or timeliness of sets, are presented by means of three graphical variables. The research problems presented in the paper are of cognitive and application importance. They indicate on the possibility of effective evaluation of the quality of spatial data collected in public registers and may be an important element of the expert system.