Author: David F. Penson
Publisher: Springer Science & Business Media
ISBN: 1597452300
Category : Medical
Languages : en
Pages : 338
Book Description
With his keen analytical mind and penchant for organization, Charles Darwin would have made an excellent clinical investigator. Unfortunately for surgery, his early exposure at Edinburgh to the brutality of operations in 1825 convinced him to reject his father’s plan for his career and pursue his interest in nature. His subsequent observations of how environmental pressures shaped the development of new species provided the essential mechanism to explain evolution and the disappearance of those species that failed to adapt. Today, surgeons face the same reality as new technology, progressive regulation by government and payers, medico-legal risks, and public demands for proof of performance force changes in behavior that our predecessors never imagined. We know that surgeons have always prided themselves on accurate documentation of their results, including their complications and deaths, but observational studies involving a single surgeon or institution have given way to demands for controlled interventional trials despite the inherent difficulty of studying surgical patients by randomized, blinded techniques. That is why this book is so timely and important. In a logical and comprehensive approach, the authors have assembled a group of experienced clinical scientists who can demonstrate the rich variety of techniques in epidemiology and statistics for reviewing existing publications, structuring a clinical study, and analyzing the resulting data.
Clinical Research Methods for Surgeons
Author: David F. Penson
Publisher: Springer Science & Business Media
ISBN: 1597452300
Category : Medical
Languages : en
Pages : 338
Book Description
With his keen analytical mind and penchant for organization, Charles Darwin would have made an excellent clinical investigator. Unfortunately for surgery, his early exposure at Edinburgh to the brutality of operations in 1825 convinced him to reject his father’s plan for his career and pursue his interest in nature. His subsequent observations of how environmental pressures shaped the development of new species provided the essential mechanism to explain evolution and the disappearance of those species that failed to adapt. Today, surgeons face the same reality as new technology, progressive regulation by government and payers, medico-legal risks, and public demands for proof of performance force changes in behavior that our predecessors never imagined. We know that surgeons have always prided themselves on accurate documentation of their results, including their complications and deaths, but observational studies involving a single surgeon or institution have given way to demands for controlled interventional trials despite the inherent difficulty of studying surgical patients by randomized, blinded techniques. That is why this book is so timely and important. In a logical and comprehensive approach, the authors have assembled a group of experienced clinical scientists who can demonstrate the rich variety of techniques in epidemiology and statistics for reviewing existing publications, structuring a clinical study, and analyzing the resulting data.
Publisher: Springer Science & Business Media
ISBN: 1597452300
Category : Medical
Languages : en
Pages : 338
Book Description
With his keen analytical mind and penchant for organization, Charles Darwin would have made an excellent clinical investigator. Unfortunately for surgery, his early exposure at Edinburgh to the brutality of operations in 1825 convinced him to reject his father’s plan for his career and pursue his interest in nature. His subsequent observations of how environmental pressures shaped the development of new species provided the essential mechanism to explain evolution and the disappearance of those species that failed to adapt. Today, surgeons face the same reality as new technology, progressive regulation by government and payers, medico-legal risks, and public demands for proof of performance force changes in behavior that our predecessors never imagined. We know that surgeons have always prided themselves on accurate documentation of their results, including their complications and deaths, but observational studies involving a single surgeon or institution have given way to demands for controlled interventional trials despite the inherent difficulty of studying surgical patients by randomized, blinded techniques. That is why this book is so timely and important. In a logical and comprehensive approach, the authors have assembled a group of experienced clinical scientists who can demonstrate the rich variety of techniques in epidemiology and statistics for reviewing existing publications, structuring a clinical study, and analyzing the resulting data.
Experimental and Quasi-Experimental Designs for Research
Author: Donald T. Campbell
Publisher: Ravenio Books
ISBN:
Category : Psychology
Languages : en
Pages : 172
Book Description
We shall examine the validity of 16 experimental designs against 12 common threats to valid inference. By experiment we refer to that portion of research in which variables are manipulated and their effects upon other variables observed. It is well to distinguish the particular role of this chapter. It is not a chapter on experimental design in the Fisher (1925, 1935) tradition, in which an experimenter having complete mastery can schedule treatments and measurements for optimal statistical efficiency, with complexity of design emerging only from that goal of efficiency. Insofar as the designs discussed in the present chapter become complex, it is because of the intransigency of the environment: because, that is, of the experimenter’s lack of complete control.
Publisher: Ravenio Books
ISBN:
Category : Psychology
Languages : en
Pages : 172
Book Description
We shall examine the validity of 16 experimental designs against 12 common threats to valid inference. By experiment we refer to that portion of research in which variables are manipulated and their effects upon other variables observed. It is well to distinguish the particular role of this chapter. It is not a chapter on experimental design in the Fisher (1925, 1935) tradition, in which an experimenter having complete mastery can schedule treatments and measurements for optimal statistical efficiency, with complexity of design emerging only from that goal of efficiency. Insofar as the designs discussed in the present chapter become complex, it is because of the intransigency of the environment: because, that is, of the experimenter’s lack of complete control.
Experimental and Quasi-experimental Designs for Generalized Causal Inference
Author: William R. Shadish
Publisher: Cengage Learning
ISBN:
Category : Education
Languages : en
Pages : 664
Book Description
Sections include: experiments and generalised causal inference; statistical conclusion validity and internal validity; construct validity and external validity; quasi-experimental designs that either lack a control group or lack pretest observations on the outcome; quasi-experimental designs that use both control groups and pretests; quasi-experiments: interrupted time-series designs; regresssion discontinuity designs; randomised experiments: rationale, designs, and conditions conducive to doing them; practical problems 1: ethics, participation recruitment and random assignment; practical problems 2: treatment implementation and attrition; generalised causal inference: a grounded theory; generalised causal inference: methods for single studies; generalised causal inference: methods for multiple studies; a critical assessment of our assumptions.
Publisher: Cengage Learning
ISBN:
Category : Education
Languages : en
Pages : 664
Book Description
Sections include: experiments and generalised causal inference; statistical conclusion validity and internal validity; construct validity and external validity; quasi-experimental designs that either lack a control group or lack pretest observations on the outcome; quasi-experimental designs that use both control groups and pretests; quasi-experiments: interrupted time-series designs; regresssion discontinuity designs; randomised experiments: rationale, designs, and conditions conducive to doing them; practical problems 1: ethics, participation recruitment and random assignment; practical problems 2: treatment implementation and attrition; generalised causal inference: a grounded theory; generalised causal inference: methods for single studies; generalised causal inference: methods for multiple studies; a critical assessment of our assumptions.
Best Practices in Quantitative Methods
Author: Jason W. Osborne
Publisher: SAGE
ISBN: 1412940656
Category : Social Science
Languages : en
Pages : 609
Book Description
The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.
Publisher: SAGE
ISBN: 1412940656
Category : Social Science
Languages : en
Pages : 609
Book Description
The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.
Introduction to Educational Research
Author: W. Newton Suter
Publisher: SAGE
ISBN: 1412995736
Category : Education
Languages : en
Pages : 529
Book Description
W. Newton Suter argues that what is important in a changing education landscape is the ability to think clearly about research methods, reason through complex problems and evaluate published research. He explains how to evaluate data and establish its relevance.
Publisher: SAGE
ISBN: 1412995736
Category : Education
Languages : en
Pages : 529
Book Description
W. Newton Suter argues that what is important in a changing education landscape is the ability to think clearly about research methods, reason through complex problems and evaluate published research. He explains how to evaluate data and establish its relevance.
Quasi-Experimentation
Author: Charles S. Reichardt
Publisher: Guilford Publications
ISBN: 1462540201
Category : Business & Economics
Languages : en
Pages : 382
Book Description
Featuring engaging examples from diverse disciplines, this book explains how to use modern approaches to quasi-experimentation to derive credible estimates of treatment effects under the demanding constraints of field settings. Foremost expert Charles S. Reichardt provides an in-depth examination of the design and statistical analysis of pretest-posttest, nonequivalent groups, regression discontinuity, and interrupted time-series designs. He details their relative strengths and weaknesses and offers practical advice about their use. Reichardt compares quasi-experiments to randomized experiments and discusses when and why the former might be a better choice. Modern moethods for elaborating a research design to remove bias from estimates of treatment effects are described, as are tactics for dealing with missing data and noncompliance with treatment assignment. Throughout, mathematical equations are translated into words to enhance accessibility.
Publisher: Guilford Publications
ISBN: 1462540201
Category : Business & Economics
Languages : en
Pages : 382
Book Description
Featuring engaging examples from diverse disciplines, this book explains how to use modern approaches to quasi-experimentation to derive credible estimates of treatment effects under the demanding constraints of field settings. Foremost expert Charles S. Reichardt provides an in-depth examination of the design and statistical analysis of pretest-posttest, nonequivalent groups, regression discontinuity, and interrupted time-series designs. He details their relative strengths and weaknesses and offers practical advice about their use. Reichardt compares quasi-experiments to randomized experiments and discusses when and why the former might be a better choice. Modern moethods for elaborating a research design to remove bias from estimates of treatment effects are described, as are tactics for dealing with missing data and noncompliance with treatment assignment. Throughout, mathematical equations are translated into words to enhance accessibility.
Quasi-Experimental Research Designs
Author: Bruce A. Thyer
Publisher: Oxford University Press
ISBN: 0195387384
Category : Reference
Languages : en
Pages : 214
Book Description
The role of group research designs to evaluate social work practice -- Pre-experimental group research designs -- Quasi-experimental group research designs -- Time-series research designs -- Evaluating and reporting quasi-experimental studies.
Publisher: Oxford University Press
ISBN: 0195387384
Category : Reference
Languages : en
Pages : 214
Book Description
The role of group research designs to evaluate social work practice -- Pre-experimental group research designs -- Quasi-experimental group research designs -- Time-series research designs -- Evaluating and reporting quasi-experimental studies.
The SAGE Handbook of Quantitative Methods in Psychology
Author: Roger E Millsap
Publisher: SAGE Publications
ISBN: 141293091X
Category : Psychology
Languages : en
Pages : 801
Book Description
`I often... wonder to myself whether the field needs another book, handbook, or encyclopedia on this topic. In this case I think that the answer is truly yes. The handbook is well focused on important issues in the field, and the chapters are written by recognized authorities in their fields. The book should appeal to anyone who wants an understanding of important topics that frequently go uncovered in graduate education in psychology' - David C Howell, Professor Emeritus, University of Vermont Quantitative psychology is arguably one of the oldest disciplines within the field of psychology and nearly all psychologists are exposed to quantitative psychology in some form. While textbooks in statistics, research methods and psychological measurement exist, none offer a unified treatment of quantitative psychology. The SAGE Handbook of Quantitative Methods in Psychology does just that. Each chapter covers a methodological topic with equal attention paid to established theory and the challenges facing methodologists as they address new research questions using that particular methodology. The reader will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area. Drawing on a global scholarship, the Handbook is divided into seven parts: Part One: Design and Inference: addresses issues in the inference of causal relations from experimental and non-experimental research, along with the design of true experiments and quasi-experiments, and the problem of missing data due to various influences such as attrition or non-compliance. Part Two: Measurement Theory: begins with a chapter on classical test theory, followed by the common factor analysis model as a model for psychological measurement. The models for continuous latent variables in item-response theory are covered next, followed by a chapter on discrete latent variable models as represented in latent class analysis. Part Three: Scaling Methods: covers metric and non-metric scaling methods as developed in multidimensional scaling, followed by consideration of the scaling of discrete measures as found in dual scaling and correspondence analysis. Models for preference data such as those found in random utility theory are covered next. Part Four: Data Analysis: includes chapters on regression models, categorical data analysis, multilevel or hierarchical models, resampling methods, robust data analysis, meta-analysis, Bayesian data analysis, and cluster analysis. Part Five: Structural Equation Models: addresses topics in general structural equation modeling, nonlinear structural equation models, mixture models, and multilevel structural equation models. Part Six: Longitudinal Models: covers the analysis of longitudinal data via mixed modeling, time series analysis and event history analysis. Part Seven: Specialized Models: covers specific topics including the analysis of neuro-imaging data and functional data-analysis.
Publisher: SAGE Publications
ISBN: 141293091X
Category : Psychology
Languages : en
Pages : 801
Book Description
`I often... wonder to myself whether the field needs another book, handbook, or encyclopedia on this topic. In this case I think that the answer is truly yes. The handbook is well focused on important issues in the field, and the chapters are written by recognized authorities in their fields. The book should appeal to anyone who wants an understanding of important topics that frequently go uncovered in graduate education in psychology' - David C Howell, Professor Emeritus, University of Vermont Quantitative psychology is arguably one of the oldest disciplines within the field of psychology and nearly all psychologists are exposed to quantitative psychology in some form. While textbooks in statistics, research methods and psychological measurement exist, none offer a unified treatment of quantitative psychology. The SAGE Handbook of Quantitative Methods in Psychology does just that. Each chapter covers a methodological topic with equal attention paid to established theory and the challenges facing methodologists as they address new research questions using that particular methodology. The reader will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area. Drawing on a global scholarship, the Handbook is divided into seven parts: Part One: Design and Inference: addresses issues in the inference of causal relations from experimental and non-experimental research, along with the design of true experiments and quasi-experiments, and the problem of missing data due to various influences such as attrition or non-compliance. Part Two: Measurement Theory: begins with a chapter on classical test theory, followed by the common factor analysis model as a model for psychological measurement. The models for continuous latent variables in item-response theory are covered next, followed by a chapter on discrete latent variable models as represented in latent class analysis. Part Three: Scaling Methods: covers metric and non-metric scaling methods as developed in multidimensional scaling, followed by consideration of the scaling of discrete measures as found in dual scaling and correspondence analysis. Models for preference data such as those found in random utility theory are covered next. Part Four: Data Analysis: includes chapters on regression models, categorical data analysis, multilevel or hierarchical models, resampling methods, robust data analysis, meta-analysis, Bayesian data analysis, and cluster analysis. Part Five: Structural Equation Models: addresses topics in general structural equation modeling, nonlinear structural equation models, mixture models, and multilevel structural equation models. Part Six: Longitudinal Models: covers the analysis of longitudinal data via mixed modeling, time series analysis and event history analysis. Part Seven: Specialized Models: covers specific topics including the analysis of neuro-imaging data and functional data-analysis.
Quasi-experimentation
Author: Thomas D. Cook
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 432
Book Description
This book presents some quasi-experimental designs and design features that can be used in many social research settings. The designs serve to probe causal hypotheses about a wide variety of substantive issues in both basic and applied research. Each design is assessed in terms of four types of validity, with special stress on internal validity. Although general conclusions are drawn about the strengths and limitations of each design, emphasis is also placed on the fact that the relevant threats to valid inference are specific to each research setting. Consequently, a threat that is usually associated with a particular design need not invariably be associated with that design.
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 432
Book Description
This book presents some quasi-experimental designs and design features that can be used in many social research settings. The designs serve to probe causal hypotheses about a wide variety of substantive issues in both basic and applied research. Each design is assessed in terms of four types of validity, with special stress on internal validity. Although general conclusions are drawn about the strengths and limitations of each design, emphasis is also placed on the fact that the relevant threats to valid inference are specific to each research setting. Consequently, a threat that is usually associated with a particular design need not invariably be associated with that design.
Improving Health Research on Small Populations
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309476097
Category : Medical
Languages : en
Pages : 151
Book Description
The increasing diversity of population of the United States presents many challenges to conducting health research that is representative and informative. Dispersion and accessibility issues can increase logistical costs; populations for which it is difficult to obtain adequate sample size are also likely to be expensive to study. Hence, even if it is technically feasible to study a small population, it may not be easy to obtain the funding to do so. In order to address the issues associated with improving health research of small populations, the National Academies of Sciences, Engineering, and Medicine convened a workshop in January 2018. Participants considered ways of addressing the challenges of conducting epidemiological studies or intervention research with small population groups, including alternative study designs, innovative methodologies for data collection, and innovative statistical techniques for analysis.
Publisher: National Academies Press
ISBN: 0309476097
Category : Medical
Languages : en
Pages : 151
Book Description
The increasing diversity of population of the United States presents many challenges to conducting health research that is representative and informative. Dispersion and accessibility issues can increase logistical costs; populations for which it is difficult to obtain adequate sample size are also likely to be expensive to study. Hence, even if it is technically feasible to study a small population, it may not be easy to obtain the funding to do so. In order to address the issues associated with improving health research of small populations, the National Academies of Sciences, Engineering, and Medicine convened a workshop in January 2018. Participants considered ways of addressing the challenges of conducting epidemiological studies or intervention research with small population groups, including alternative study designs, innovative methodologies for data collection, and innovative statistical techniques for analysis.