Patrick Suppes is a philosopher and scientist whose contributions range over probability and statistics, mathematical and experimental psychology, the foundations of physics, education theory, the philosophy of language, measurement theory, and the philosophy of science. He has also been a pioneer in the area of computer assisted instruction. In each of these areas, Suppes has provided seminal ideas that in some cases led to shaping the direction of research in the field. The papers contained in this collection were commissioned with the mandate of advancing research in their respective fields rather than retrospectively surveying the contributions that Suppes himself has made. The authors form an interesting mixture of researchers in both formal philosophy of science and science itself all of whom have been inspired by his ideas. To maintain the spirit of constructive dialogue that characterizes Suppes's intellectual style, he has written individual responses to each article. In Volume 1: Probability and Probabilistic Causality, nineteen distinguished philosophers and scientists focus their attention on probabilistic issues. In Part I the contributors explore axiomatic representations of probability theory including qualitative and interval valued probabilities as well as traditional point valued probabilities. Belief structures and the dynamics of belief are also treated in detail. In Part II the rapidly growing field of probabilistic causation is assessed from both formal and empirical viewpoints. For probability theorists, statisticians, economists, philosophers of science, psychologists and those interested in the foundations of mathematical social science. In Volume 2: Philosophy of Physics, Theory Structure, and Measurement Theory, fifteen distinguished philosophers and scientists cover a wide variety of topics. Part III covers issues in quantum theory, geometry, classical mechanics, and computational physics. Part IV explores Suppes's well known set-theoretic account of scientific theories which has served him well throughout his career. Suppes's contributions to measurement theory have been widely used in mathematical psychology and elsewhere, and this material is the subject of Part V. For physicists, logicians, workers in mathematical social sicence, and philosophers of science. In Volume 3: Philosophy of Language and Logic, Learning and Action Theory, fourteen distinguished philosophers and scientists explore issues in the philosophy of language, logic, and philosophical psychology. Suppes's suggestions that quantum theory requires a rethinking of classical logic form a particularly sharp account of that controversial thesis, and Part VI deals with this issue together with topics in the philosophy of language and logic, including relational grammars and anaphora. Part VII deals with issues in psychology, action theory, and robotics, while Part VIII concludes with a general survey of Suppes's views in the philosophy of science. A comprehensive chronological and topical bibliography of Suppes's writings is included in this volume. For philosophers of language, theoretical linguists, logicians, workers in mathematical social sciences, and philosophers of science.
Patrick Suppes is a philosopher and scientist whose contributions range over probability and statistics, mathematical and experimental psychology, the foundations of physics, education theory, the philosophy of language, measurement theory, and the philosophy of science. He has also been a pioneer in the area of computer assisted instruction. In each of these areas, Suppes has provided seminal ideas that in some cases led to shaping the direction of research in the field. The papers contained in this collection were commissioned with the mandate of advancing research in their respective fields rather than retrospectively surveying the contributions that Suppes himself has made. The authors form an interesting mixture of researchers in both formal philosophy of science and science itself all of whom have been inspired by his ideas. To maintain the spirit of constructive dialogue that characterizes Suppes's intellectual style, he has written individual responses to each article. In Volume 1: Probability and Probabilistic Causality, nineteen distinguished philosophers and scientists focus their attention on probabilistic issues. In Part I the contributors explore axiomatic representations of probability theory including qualitative and interval valued probabilities as well as traditional point valued probabilities. Belief structures and the dynamics of belief are also treated in detail. In Part II the rapidly growing field of probabilistic causation is assessed from both formal and empirical viewpoints. For probability theorists, statisticians, economists, philosophers of science, psychologists and those interested in the foundations of mathematical social science. In Volume 2: Philosophy of Physics, Theory Structure, and Measurement Theory, fifteen distinguished philosophers and scientists cover a wide variety of topics. Part III covers issues in quantum theory, geometry, classical mechanics, and computational physics. Part IV explores Suppes's well known set-theoretic account of scientific theories which has served him well throughout his career. Suppes's contributions to measurement theory have been widely used in mathematical psychology and elsewhere, and this material is the subject of Part V. For physicists, logicians, workers in mathematical social sicence, and philosophers of science. In Volume 3: Philosophy of Language and Logic, Learning and Action Theory, fourteen distinguished philosophers and scientists explore issues in the philosophy of language, logic, and philosophical psychology. Suppes's suggestions that quantum theory requires a rethinking of classical logic form a particularly sharp account of that controversial thesis, and Part VI deals with this issue together with topics in the philosophy of language and logic, including relational grammars and anaphora. Part VII deals with issues in psychology, action theory, and robotics, while Part VIII concludes with a general survey of Suppes's views in the philosophy of science. A comprehensive chronological and topical bibliography of Suppes's writings is included in this volume. For philosophers of language, theoretical linguists, logicians, workers in mathematical social sciences, and philosophers of science.
Patrick Suppes is a philosopher and scientist whose contributions range over probability and statistics, mathematical and experimental psychology, the foundations of physics, education theory, the philosophy of language, measurement theory, and the philosophy of science. He has also been a pioneer in the area of computer assisted instruction. In each of these areas, Suppes has provided seminal ideas that in some cases led to shaping the direction of research in the field. The papers contained in this collection were commissioned with the mandate of advancing research in their respective fields rather than retrospectively surveying the contributions that Suppes himself has made. The authors form an interesting mixture of researchers in both formal philosophy of science and science itself all of whom have been inspired by his ideas. To maintain the spirit of constructive dialogue that characterizes Suppes's intellectual style, he has written individual responses to each article. In Volume 1: Probability and Probabilistic Causality, nineteen distinguished philosophers and scientists focus their attention on probabilistic issues. In Part I the contributors explore axiomatic representations of probability theory including qualitative and interval valued probabilities as well as traditional point valued probabilities. Belief structures and the dynamics of belief are also treated in detail. In Part II the rapidly growing field of probabilistic causation is assessed from both formal and empirical viewpoints. For probability theorists, statisticians, economists, philosophers of science, psychologists and those interested in the foundations of mathematical social science. In Volume 2: Philosophy of Physics, Theory Structure, and Measurement Theory, fifteen distinguished philosophers and scientists cover a wide variety of topics. Part III covers issues in quantum theory, geometry, classical mechanics, and computational physics. Part IV explores Suppes's well known set-theoretic account of scientific theories which has served him well throughout his career. Suppes's contributions to measurement theory have been widely used in mathematical psychology and elsewhere, and this material is the subject of Part V. For physicists, logicians, workers in mathematical social sicence, and philosophers of science. In Volume 3: Philosophy of Language and Logic, Learning and Action Theory, fourteen distinguished philosophers and scientists explore issues in the philosophy of language, logic, and philosophical psychology. Suppes's suggestions that quantum theory requires a rethinking of classical logic form a particularly sharp account of that controversial thesis, and Part VI deals with this issue together with topics in the philosophy of language and logic, including relational grammars and anaphora. Part VII deals with issues in psychology, action theory, and robotics, while Part VIII concludes with a general survey of Suppes's views in the philosophy of science. A comprehensive chronological and topical bibliography of Suppes's writings is included in this volume. For philosophers of language, theoretical linguists, logicians, workers in mathematical social sciences, and philosophers of science.
Volume 1: Probability and Probabilistic Causality Volume 2: Philosophy of Physics, Theory Structure and Measurement TheoryVolume 3: Philosophy of Language and Logic, Learning and Action Theory
Volume 1: Probability and Probabilistic Causality Volume 2: Philosophy of Physics, Theory Structure and Measurement TheoryVolume 3: Philosophy of Language and Logic, Learning and Action Theory
Patrick Suppes is a philosopher and scientist whose contributions range over probability and statistics, mathematical and experimental psychology, the foundations of physics, education theory, the philosophy of language, measurement theory, and the philosophy of science. He has also been a pioneer in the area of computer assisted instruction. In each of these areas, Suppes has provided seminal ideas that in some cases led to shaping the direction of research in the field. The papers contained in this collection were commissioned with the mandate of advancing research in their respective fields rather than retrospectively surveying the contributions that Suppes himself has made. The authors form an interesting mixture of researchers in both formal philosophy of science and science itself all of whom have been inspired by his ideas. To maintain the spirit of constructive dialogue that characterizes Suppes's intellectual style, he has written individual responses to each article. In Volume 1: Probability and Probabilistic Causality, nineteen distinguished philosophers and scientists focus their attention on probabilistic issues. In Part I the contributors explore axiomatic representations of probability theory including qualitative and interval valued probabilities as well as traditional point valued probabilities. Belief structures and the dynamics of belief are also treated in detail. In Part II the rapidly growing field of probabilistic causation is assessed from both formal and empirical viewpoints. For probability theorists, statisticians, economists, philosophers of science, psychologists and those interested in the foundations of mathematical social science. In Volume 2: Philosophy of Physics, Theory Structure, and Measurement Theory, fifteen distinguished philosophers and scientists cover a wide variety of topics. Part III covers issues in quantum theory, geometry, classical mechanics, and computational physics. Part IV explores Suppes's well known set-theoretic account of scientific theories which has served him well throughout his career. Suppes's contributions to measurement theory have been widely used in mathematical psychology and elsewhere, and this material is the subject of Part V. For physicists, logicians, workers in mathematical social sicence, and philosophers of science. In Volume 3: Philosophy of Language and Logic, Learning and Action Theory, fourteen distinguished philosophers and scientists explore issues in the philosophy of language, logic, and philosophical psychology. Suppes's suggestions that quantum theory requires a rethinking of classical logic form a particularly sharp account of that controversial thesis, and Part VI deals with this issue together with topics in the philosophy of language and logic, including relational grammars and anaphora. Part VII deals with issues in psychology, action theory, and robotics, while Part VIII concludes with a general survey of Suppes's views in the philosophy of science. A comprehensive chronological and topical bibliography of Suppes's writings is included in this volume. For philosophers of language, theoretical linguists, logicians, workers in mathematical social sciences, and philosophers of science.
Additive and Polynomial Representations deals with major representation theorems in which the qualitative structure is reflected as some polynomial function of one or more numerical functions defined on the basic entities. Examples are additive expressions of a single measure (such as the probability of disjoint events being the sum of their probabilities), and additive expressions of two measures (such as the logarithm of momentum being the sum of log mass and log velocity terms). The book describes the three basic procedures of fundamental measurement as the mathematical pivot, as the utilization of constructive methods, and as a series of isomorphism theorems leading to consistent numerical solutions. The text also explains the counting of units in relation to an empirical relational structure which contains a concatenation operation. The book notes some special variants which arise in connection with relativity and thermodynamics. The text cites examples from physics and psychology for which additive conjoint measurement provides a possible method of fundamental measurement. The book will greatly benefit mathematicians, econometricians, and academicians in advanced mathematics or physics.
All of the sciences―physical, biological, and social―have a need for quantitative measurement. This influential series, Foundations of Measurement, established the formal foundations for measurement, justifying the assignment of numbers to objects in terms of their structural correspondence. Volume I introduces the distinct mathematical results that serve to formulate numerical representations of qualitative structures. Volume II extends the subject in the direction of geometrical, threshold, and probabilistic representations, and Volume III examines representation as expressed in axiomatization and invariance.
Some data-analytic methods excel by their sheer elegance. Their basic principles seem to have a particular attraction, based on a intricate combination of simplicity, deliberation, and power. They usually balance on the verge of two disciplines, data-analysis and foundational measurement, or statistics and psychology. To me, unfolding has always been one of them. The theory and the original methodology were created by Clyde Coombs (1912-1988) to describe and analyze preferential choice data. The fundamental assumptions are truly psy chological; Unfolding is based on the notion of a single peaked preference function over a psychological similarity space, or, in an alternative but equivalent expression, on the assumption of implicit comparisons with an ideal alternative. Unfolding has proved to be a very constructive data-analytic principle, and a source of inspiration for many theories on choice behavior. Yet the number of applications has not lived up to the acclaim the theory has received among mathematical psychologists. One of the reasons is that it requires far more consistency in human choice behavior than can be expected. Several authors have tried to attenuate these requirements by turning the deterministic unfolding theory into a probabilistic one. Since Coombs first put forth a probabilistic version of his theory, a number of competing proposals have been presented in the literature over the past thirty years. This monograph contains a summary and a comparison of unfolding theories for paired comparisons data, and an evaluation strategy designed to assess the validity of these theories in empirical choice tasks.
Quantum mechanics has raised in an acute form three problems which go to the heart of man's relationship with nature through experimental science: (r) the public objectivity of science, that is, its value as a universal science for all investigators; (2) the empirical objectivity of scientific objects, that is, man's ability to construct a precise or causal spatio-temporal model of microscopic systems; and finally (3), the formal objectivity of science, that is, its value as an expression of what nature is independently of its being an object of human knowledge. These are three aspects of what is generally called the "crisis of objec tivity" or the "crisis of realism" in modern physics. This crisis is. studied in the light of Werner Heisenberg's work. Heisenberg was one of the architects of quantum mechanics, and we have chosen his writings as the principal source-material for this study. Among physicists of the microscopic domain, no one except perhaps Bohr has expressed himself so abundantly and so profoundly on the philosophy of science as Heisenberg. His writings, both technical and non-technical, show an awareness of the mysterious element in scientific knowledge, far from the facile positivism of Bohr and others of his contemporaries. The mystery of human knowledge and human SUbjectivity is for him an abiding source of wonder.
This book is a major new contribution to decision theory, focusing on the question of when it is rational to accept scientific theories. The author examines both Bayesian decision theory and confirmation theory, refining and elaborating the views of Ramsey and Savage. He argues that the most solid foundation for confirmation theory is to be found in decision theory, and he provides a decision-theoretic derivation of principles for how many probabilities should be revised over time. Professor Maher defines a notion of accepting a hypothesis, and then shows that it is not reducible to probability and that it is needed to deal with some important questions in the philosophy of science. A Bayesian decision-theoretic account of rational acceptance is provided together with a proof of the foundations for this theory. A final chapter shows how this account can be used to cast light on such vexing issues as verisimilitude and scientific realism.
This textbook on Instructional Design for Learning is a must for all education and teaching students and specialists. It provides a comprehensive overview about the theoretical foundations of the various models of Instructional Design and Technology from its very beginning to the most recent approaches. It elaborates Instructional Design (ID) as a science of educational planning. The book expands on this general understanding of ID and presents an up-to-date perspective on the theories and models for the creation of detailed and precise blueprints for effective instruction. It integrates different theoretical aspects and practical approaches, such as conceptual ID models, technology-based ID, and research-based ID. In doing so, this book takes a multi-perspective view on the questions that are central for professional ID: How to analyze the relevant characteristics of the learner and the environment? How to create precise goals and adequate instruments of assessment? How to design classroom and technology-supported learning environments? How to ensure effective teaching and learning by employing formative and summative evaluation? Furthermore, this book presents empirical findings on the processes that enable effective instructional designing. Finally, this book demonstrates two different fields of application by addressing ID for teaching and learning at secondary schools and colleges, as well as for higher education.
On Interpretation challenges a number of entrenched assumptions about being and knowing that have long kept theorists debating at cross purposes. Patrick Colm Hogan first sets forth a theory of meaning and interpretation and then develops it in the context of the practices and goals of law, psychoanalysis, and literary criticism. In his preface, Hogan discusses developments in semantics and related fields that have occurred over the decade since the book first appeared.
Multidimensional scaling (MDS) is a technique for the analysis of similarity or dissimilarity data on a set of objects. Such data may be intercorrelations of test items, ratings of similarity on political candidates, or trade indices for a set of countries. MDS attempts to model such data as distances among points in a geometric space. The main reason for doing this is that one wants a graphical display of the structure of the data, one that is much easier to understand than an array of numbers and, moreover, one that displays the essential information in the data, smoothing out noise. There are numerous varieties of MDS. Some facets for distinguishing among them are the particular type of geometry into which one wants to map the data, the mapping function, the algorithms used to find an optimal data representation, the treatment of statistical error in the models, or the possibility to represent not just one but several similarity matrices at the same time. Other facets relate to the different purposes for which MDS has been used, to various ways of looking at or "interpreting" an MDS representation, or to differences in the data required for the particular models. In this book, we give a fairly comprehensive presentation of MDS. For the reader with applied interests only, the first six chapters of Part I should be sufficient. They explain the basic notions of ordinary MDS, with an emphasis on how MDS can be helpful in answering substantive questions.
Psychology has influence in almost every walk of life. Originally published in 1997, A Century of Psychology is a review of where the discipline came from, where it had reached and where the editors anticipated it may go. Ray Fuller, Patricia Noonan Walsh and Patrick McGinley assembled an internationally recognised team of mainly European experts from the major applications and research areas of psychology. They begin with a critical review of methodology and its limitations and plot the course of gender and developmental psychology. They go on to include discussion of learning, intellectual disability, clinical psychology and the emergence of psychotherapy, educational psychology, organizational psychology, cognitive psychology, neuropsychology and many other topics, in particular community psychology, perception and alternative medicine. Enlightening, reflective and sometimes provocative, A Century of Psychology is required reading for anyone involved in psychology as a practitioner, researcher or teacher. It is also a lively introduction for those new to the discipline.
Drawing on the phenomenological tradition in the philosophy of science and philosophy of nature, Patrick Heelan concludes that perception is a cognitive, world-building act, and is therefore never absolute or finished.
Experimental research by social and cognitive psychologists has established that cooperative groups solve a wide range of problems better than individuals. Cooperative problem solving groups of scientific researchers, auditors, financial analysts, air crash investigators, and forensic art experts are increasingly important in our complex and interdependent society. This comprehensive textbook--the first of its kind in decades--presents important theories and experimental research about group problem solving. The book focuses on tasks that have demonstrably correct solutions within mathematical, logical, scientific, or verbal systems, including algebra problems, analogies, vocabulary, and logical reasoning problems. The book explores basic concepts in group problem solving, social combination models, group memory, group ability and world knowledge tasks, rule induction problems, letters-to-numbers problems, evidence for positive group-to-individual transfer, and social choice theory. The conclusion proposes ten generalizations that are supported by the theory and research on group problem solving. Group Problem Solving is an essential resource for decision-making research in social and cognitive psychology, but also extremely relevant to multidisciplinary and multicultural problem-solving teams in organizational behavior, business administration, management, and behavioral economics.
In The Concept of Justice, Patrick Burke explores and argues for a return to traditional ideas of ordinary justice in opposition to conceptions of 'social justice' that came to dominate political thought in the 20th Century. Arguing that our notions of justice have been made incoherent by the radical incompatibility between instinctive notions of ordinary justice and theoretical conceptions of social justice, the book goes on to explore the historical roots of these ideas of social justice. Finding the roots of these ideas in religious circles in Italy and England in the 19th century, Burke explores the ongoing religious influence in the development of the concept in the works of Marx, Mill and Hobhouse. In opposition to this legacy of liberal thought, the book presents a new theory of ordinary justice drawing on the thought of Immanuel Kant. In this light, Burke finds that all genuine ethical evaluation must presuppose free will and individual responsibility and that all true injustice is fundamentally coercive.
After a detailed discussion of the significance of translation as a critical concept in psychoanalysis, Patrick Mahony proceeds to a comprehensive examination of 'free association', the cornerstone of psychoanalytic method. Next follows the consideration of free association in its relation to scientific rhetorical, expressive and literary discourse. Mahony then begins a detailed study of certain aspects of the text of Freud's Interpretation of Dreams and of issues involved in the oral reporting of dreams. Attention is subsequently turned to the analysis of Freud's own writing in general, and specifically to Totem and Taboo. Finally, the author shows how his ideas can illuminate literary classics (by Villon, Shakespeare, Kafka, and Jonson) and the debate about whether there is anything specific to women's discourse.
Introduction to abstract interpretation, with examples of applications to the semantics, specification, verification, and static analysis of computer programs. Formal methods are mathematically rigorous techniques for the specification, development, manipulation, and verification of safe, robust, and secure software and hardware systems. Abstract interpretation is a unifying theory of formal methods that proposes a general methodology for proving the correctness of computing systems, based on their semantics. The concepts of abstract interpretation underlie such software tools as compilers, type systems, and security protocol analyzers. This book provides an introduction to the theory and practice of abstract interpretation, offering examples of applications to semantics, specification, verification, and static analysis of programming languages with emphasis on calculational design. The book covers all necessary computer science and mathematical concepts--including most of the logic, order, linear, fixpoint, and discrete mathematics frequently used in computer science--in separate chapters before they are used in the text. Each chapter offers exercises and selected solutions. Chapter topics include syntax, parsing, trace semantics, properties and their abstraction, fixpoints and their abstractions, reachability semantics, abstract domain and abstract interpreter, specification and verification, effective fixpoint approximation, relational static analysis, and symbolic static analysis. The main applications covered include program semantics, program specification and verification, program dynamic and static analysis of numerical properties and of such symbolic properties as dataflow analysis, software model checking, pointer analysis, dependency, and typing (both for forward and backward analysis), and their combinations. Principles of Abstract Interpretation is suitable for classroom use at the graduate level and as a reference for researchers and practitioners.
This book aims to show that fuzzy set theory constitutes a highly expressive framework for modeling preference queries. It presents a study of the algorithmic aspects related to the evaluation of such queries in order to demonstrate that this framework offers a good trade-off between expressivity and efficiency. Numerous examples and proofs are liberally and lucidly demonstrated throughout, and greatly enhance the detailed theoretical aspects explored in the book.
This book steers a middle course between two opposing conceptions that currently dominate the field of semantics, the logical and cognitive approaches. Patrick Duffley brings to light the inadequacies of both of these frameworks, arguing that linguistic semantics must be based on the linguistic sign itself and on the meaning that it conveys across the full range of its uses. The book offers 12 case studies that demonstrate the explanatory power of a sign-based semantics, dealing with topics such as complementation with aspectual and causative verbs, control and raising, wh- words, full-verb inversion, and existential-there constructions. It calls for a radical revision of the semantics/pragmatics interface, proposing that the dividing line be drawn between content that is linguistically encoded and content that is not encoded but still communicated. While traditional linguistic analysis often places meaning at the level of the sentence or construction, this volume argues that meaning belongs at the lower level of linguistic items, where the linguistic sign is stored in a stable, permanent, and direct relation with its meaning outside of any particular context. Building linguistic analysis from the ground up in this way provides it with a more solid foundation and increases its explanatory power.
Originally published in 1979 and with a case-study from Indonesia, this volume examines the question of planning the provision of transport facilities as a special case of the general planning problem. It deals with the modelling (including conceptual short-comings of it), analysis, estimation and control of transport planning and the challenges associated with planning in uncertainty. As well as devoting specific chapters to network planning, the book also provides background material on transport planning, locational theory and economics.
This work analyzes the politics of anthropological knowledge from critical perspective that alters existing understandings of colonialism. At the same time, it produces insights into the history of anthropology. Organized around an historical reconstruction of the great anthropological controversy over doctrines of virgin birth, the book argues that the allegation a great deal about European colonial discourse and little if anything about indigenous beliefs. By means of an Australian example, the book shows not only that the alleged ignorance was an artifact of the anthropological theory that produced it, but also that the anthropology was an artifact of the anthropological theory that produced it, but also that the anthropology concerned has been closely tied into both the historical dispossession and the continuing oppression of native peoples. The author explores the links between metropolitan anthropological theory and local colonial politics from the 19th century up to the present, settler colonialism, and the ideological and sexual regimes that characterize it.
The main purpose of this paper is to contribute to the discussion about the design of computer and communication systems that can aid the management process. 1.1 Historical Overview We propose that Decision Support System can be considered as a design conception conceived within the computer industry to facilitate the use of computer technology in organisations (Keen, 1991). This framework, built during the late 1970s, offers computer and communication technology as support to the decision process which constitutes, in this view, the core of the management process. The DSS framework offers the following capabilities: • Access: ease of use, wide variety of data, analysis and modelling capacity. • Technological: software gel)eration tools. • Development modes: interactive and evolutionary. Within this perspective, computer and communication technologies are seen as an amplification of the human data processing capabilities which limit the decision process. Thus, the human being is understood metaphorically as a data processing machine. Mental processes are associated with the manipulation of symbols aOO human communication to signal transmission.
An effective technique for data analysis in the social sciences The recent explosion in longitudinal data in the social sciences highlights the need for this timely publication. Latent Curve Models: A Structural Equation Perspective provides an effective technique to analyze latent curve models (LCMs). This type of data features random intercepts and slopes that permit each case in a sample to have a different trajectory over time. Furthermore, researchers can include variables to predict the parameters governing these trajectories. The authors synthesize a vast amount of research and findings and, at the same time, provide original results. The book analyzes LCMs from the perspective of structural equation models (SEMs) with latent variables. While the authors discuss simple regression-based procedures that are useful in the early stages of LCMs, most of the presentation uses SEMs as a driving tool. This cutting-edge work includes some of the authors' recent work on the autoregressive latent trajectory model, suggests new models for method factors in multiple indicators, discusses repeated latent variable models, and establishes the identification of a variety of LCMs. This text has been thoroughly class-tested and makes extensive use of pedagogical tools to aid readers in mastering and applying LCMs quickly and easily to their own data sets. Key features include: Chapter introductions and summaries that provide a quick overview of highlights Empirical examples provided throughout that allow readers to test their newly found knowledge and discover practical applications Conclusions at the end of each chapter that stress the essential points that readers need to understand for advancement to more sophisticated topics Extensive footnoting that points the way to the primary literature for more information on particular topics With its emphasis on modeling and the use of numerous examples, this is an excellent book for graduate courses in latent trajectory models as well as a supplemental text for courses in structural modeling. This book is an excellent aid and reference for researchers in quantitative social and behavioral sciences who need to analyze longitudinal data.
Cost-effectiveness analysis allows researchers and evaluators to determine if a particular program or policy has attained maximum effectiveness for a given budget. This book introduces cost-effectiveness analysis and gives readers step-by-step methods to plan and implement a cost-analysis study. It explains and illustrates the four major techniques : cost-effectiveness, cost-benefit, cost-utility, and cost-feasibility. It discusses choice of analysis, implementation, the nature of costs (including how to identify, measure, and distribute costs); measuring effectiveness, utility, and benefits; and, lastly the difficulties of including cost evaluations in the decision making process. Each chapter ends with exercises that enable readers to sharpen their ability to evaluate policy options and program effectiveness.
This textbook describes the broadening methodology spectrum of psychological measurement in order to meet the statistical needs of a modern psychologist. The way statistics is used, and maybe even perceived, in psychology has drastically changed over the last few years; computationally as well as methodologically. R has taken the field of psychology by storm, to the point that it can now safely be considered the lingua franca for statistical data analysis in psychology. The goal of this book is to give the reader a starting point when analyzing data using a particular method, including advanced versions, and to hopefully motivate him or her to delve deeper into additional literature on the method. Beginning with one of the oldest psychometric model formulations, the true score model, Mair devotes the early chapters to exploring confirmatory factor analysis, modern test theory, and a sequence of multivariate exploratory method. Subsequent chapters present special techniques useful for modern psychological applications including correlation networks, sophisticated parametric clustering techniques, longitudinal measurements on a single participant, and functional magnetic resonance imaging (fMRI) data. In addition to using real-life data sets to demonstrate each method, the book also reports each method in three parts-- first describing when and why to apply it, then how to compute the method in R, and finally how to present, visualize, and interpret the results. Requiring a basic knowledge of statistical methods and R software, but written in a casual tone, this text is ideal for graduate students in psychology. Relevant courses include methods of scaling, latent variable modeling, psychometrics for graduate students in Psychology, and multivariate methods in the social sciences.
Robot technology will find wide-scale use only when a robotic device can be given commands and taught new tasks in a natural language. How could a robot understand instructions expressed in English? How could a robot learn from instructions? Crangle and Suppes begin to answer these questions through a theoretical approach to language and learning for robots, and by experimental work with robots. The authors develop the notion of an instructable robot - one which derives its intelligence in part from interaction with humans. Since verbal interaction with a robot requires a natural language semantics, the authors propose a natural-model semantics which they then apply to the interpretation of robot commands. Two experimental projects are described which provide natural-language interfaces to robotic aids for the physically disabled.
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