Preface. 1 Philosophy of science and introduction to epidemiology. Introduction and learning objectives. 1.1 Approaches to scientific research. 1.2 Formulating a research question. 1.3 Rates: incidence and prevalence. 1.4 Concepts of prevention. 1.5 Answers to self-assessment exercises. 2 Routine data sources and descriptive epidemiology. Introduction and learning objectives. 2.1 Routine collection of health information. 2.2 Descriptive epidemiology. 2.3 Information on the environment. 2.4 Displaying, describing and presenting data. 2.5 Summary of routinely available data. 2.6 Descriptive epidemiology in action. 2.7 Overview of epidemiological study designs. 2.8 Answers to self-assessment exercises. 3 Standardisation. Introduction and learning objectives. 3.1 Health inequalities in Merseyside. 3.2 Indirect standardisation: calculation of the standardised mortality ratio (SMR). 3.3 Direct standardisation. 3.4 Standardisation for factors other than age. 3.5 Answers to self-assessment exercises. 4 Surveys. Introduction and learning objectives. 4.1 Purpose and context. 4.2 Sampling methods. 4.3 The sampling frame. 4.4 Sampling error, confidence intervals and sample size. 4.5 Response 4.6 Measurement. 4.7 Data types and presentation. 4.8 Answers to self-assessment exercises. 5 Cohort studies. Introduction and learning objectives. 5.1 Why do a cohort study? 5.2 Obtaining the sample. 5.3 Measurement. 5.4 Follow-up. 5.5 Basic presentation and analysis of results. 5.6 How large should a cohort study be? 5.7 Confounding. 5.8 Simple linear regression. 5.9 Introduction to multiple linear regression. 5.10 Answers to self-assessment exercises. 6 Case-control studies. Introduction and learning objectives. 6.1 Why do a case-control study? 6.2 Key elements of study design. 6.3 Basic unmatched and matched analysis. 6.4 Sample size for a case-control study. 6.5 Confounding and logistic regression. 6.6 Answers to self-assessment exercises. 7 Intervention studies. Introduction and learning objectives. 7.1 Why do an intervention study? 7.2 Key elements of intervention study design. 7.3 The analysis of intervention studies. 7.4 Testing more complex interventions. 7.5 How big should the trial be? 7.6 Further aspects of intervention study design and analysis. 7.7 Answers to self-assessment exercises. 8 Life tables, survival analysis and Cox regression. Introduction and learning objectives. 8.1 Survival analysis. 8.2 Cox regression. 8.3 Current life tables. 8.4 Answers to self-assessment exercises. 9 Systematic reviews and meta-analysis. Introduction and learning objectives. 9.1 The why and how of systematic reviews. 9.2 The methodology of meta-analysis. 9.3 Systematic reviews and meta-analyses of observational studies. 9.4 The Cochrane Collaboration. 9.5 Answers to self-assessment exercises. 10 Prevention strategies and evaluation of screening. Introduction and learning objectives. 10.1 Concepts of risk. 10.2 Strategies of prevention. 10.3 Evaluation of screening programmes. 10.4 Cohort and period effects. 10.5 Answers to self-assessment exercises. 11 Probability distributions, hypothesis testing and Bayesian methods. Introduction and learning objectives. 11.1 Probability distributions. 11.2 Data that do not 'fit' a probability distribution. 11.3 Hypothesis testing. 11.4 Choosing an appropriate hypothesis test. 11.5 Bayesian methods. 11.6 Answers to self-assessment exercises. References. Index.
Preface. 1 Introduction. 1.1 Introduction. 1.2 Some completed trials. 1.3 Choice of design. 1.4 Practical constraints. 1.5 Influencing clinical practice. 1.6 History. 1.7 How trials arise. 1.8 Ethical considerations. 1.9 Regulatory requirements. 1.10 Focus. 1.11 Further reading. 2 Design Features. 2.1 Introduction. 2.2 The research question. 2.3 Patient selection. 2.4 The consent process. 2.5 Choice of interventions. 2.6 Choice of design. 2.7 Assigning the interventions. 2.8 Making the assessments. 2.9 Analysis and reporting. 2.10 Technical details. 2.11 Guidelines. 2.12 Further reading. 3 The Trial Protocol. 3.1 Introduction. 3.2 Protocol abstract. 3.3 Protocol background. 3.4 Protocol research objectives. 3.5 Protocol design. 3.6 Protocol intervention details. 3.7 Protocol eligibility. 3.8 Protocol randomization. 3.9 Protocol assessment and data collection. 3.10 Protocol statistical considerations. 3.11 Protocol ethical issues. 3.12 Protocol organizational structure. 3.13 Protocol publication policy. 3.14 Protocol trial forms. 3.15 Protocol appendices. 3.16 Regulatory requirements. 3.17 Guidelines. 3.18 Protocols. 4 Measurement and Data Capture. 4.1 Introduction. 4.2 Measures and endpoints. 4.3 Making the observations. 4.4 Baseline measures. 4.5 Types of measures. 4.6 Data recording. 4.7 Technical notes. 4.8 Guidelines. 5 Randomization. 5.1 Introduction. 5.2 Rationale. 5.3 Mechanics. 5.4 Application. 5.5 Carrying out randomization. 5.6 Documentation. 5.7 Unacceptable methods. 5.8 Software. 5.9 Guidelines. 6 Trial Initiation. 6.1 Introduction. 6.2 Trial organization. 6.3 Data collection and processing. 6.4 Data monitoring. 6.5 Ethical and regulatory requirements. 6.6 Launching the trial. 6.7 Trial registries. 6.8 Guidelines. 7 Trial Conduct. 7.1 Introduction. 7.2 Regular feedback. 7.3 Publicity. 7.4 Data monitoring committees. 7.5 Protocol modifications. 7.6 Preparing the publication(s). 7.7 The next trial? 7.8 Protocols. 8 Basics of Analysis. 8.1 Introduction. 8.2 Confidence intervals. 8.3 Statistical tests. 8.4 Examples of analysis. 8.5 Other issues. 8.6 Practice. 8.7 Technical details. 9 Trial Size. 9.1 Introduction. 9.2 Significance level and power. 9.3 The fundamental equation. 9.4 Specific situations. 9.5 Practical considerations. 9.6 Further topics. 9.7 Other methods and software. 9.8 Guideline. 10 Reporting. 10.1 Introduction. 10.2 Publication guidelines. 10.3 Responsibilities. 10.4 Background. 10.5 Methods. 10.6 Findings. 10.7 When things go wrong. 10.8 Conclusions. 10.9 Guidelines. 11 Adaptations of the Basic Design. 11.1 Introduction. 11.2 Repeated measures. 11.3 Cluster-randomized trials. 11.4 Non-inferiority trials. 11.5 Guidelines. 12 Paired Designs. 12.1 Cross-over trials. 12.2 Split-mouth designs. 12.3 Paired organs. 13 More Than Two Interventions. 13.1 Introduction. 13.2 Unstructured comparisons. 13.3 Comparisons with placebo (or standard). 13.4 Dose response designs. 13.5 Factorial trials. 14 Further Topics. 14.1 Introduction. 14.2 Adaptive approaches. 14.3 Large simple trials. 14.4 Bayesian methods. 14.5 Zelen randomized-consent designs. 14.6 Systematic overviews. 14.7 Conclusion. Statistical Tables. Glossary. References. Index.
Praise forEnvisioning the Survey Interview of the Future "This book is an excellent introduction to some brave new technologies . . . and their possible impacts on the way surveys might be conducted. Anyone interested in the future of survey methodology should read this book." -Norman M. Bradburn, PhD, National Opinion Research Center, University of Chicago "Envisioning the Survey Interview of the Future gathers some of the brightest minds in alternative methods of gathering self-report data, with an eye toward the future self-report sample survey. Conrad and Schober, by assembling a group of talented survey researchers and creative inventors of new software-based tools to gather information from human subjects, have created a volume of importance to all interested in imagining future ways of interviewing." -Robert M. Groves, PhD, Survey Research Center, University of Michigan This collaboration provides extensive insight into the impact of communication technology on survey research As previously unimaginable communication technologies rapidly become commonplace, survey researchers are presented with both opportunities and obstacles when collecting and interpreting data based on human response. Envisioning the Survey Interview of the Future explores the increasing influence of emerging technologies on the data collection process and, in particular, self-report data collection in interviews, providing the key principles for using these new modes of communication. With contributions written by leading researchers in the fields of survey methodology and communication technology, this compilation integrates the use of modern technological developments with established social science theory. The book familiarizes readers with these new modes of communication by discussing the challenges to accuracy, legitimacy, and confidentiality that researchers must anticipate while collecting data, and it also provides tools for adopting new technologies in order to obtain high-quality results with minimal error or bias. Envisioning the Survey Interview of the Future addresses questions that researchers in survey methodology and communication technology must consider, such as: How and when should new communication technology be adopted in the interview process? What are the principles that extend beyond particular technologies? Why do respondents answer questions from a computer differently than questions from a human interviewer? How can systems adapt to respondents' thinking and feeling? What new ethical concerns about privacy and confidentiality are raised from using new communication technologies? With its multidisciplinary approach, extensive discussion of existing and future technologies, and practical guidelines for adopting new technology, Envisioning the Survey Interview of the Future is an essential resource for survey methodologists, questionnaire designers, and communication technologists in any field that conducts survey research. It also serves as an excellent supplement for courses in research methods at the upper-undergraduate or graduate level.
Inquiring about God is the first of two volumes of Nicholas Wolterstorff's collected papers. This volume collects Wolterstorff's essays on the philosophy of religion written over the last thirty-five years. The essays, which span a range of topics including Kant's philosophy of religion, the medieval (or classical) conception of God, and the problem of evil, are unified by the conviction that some of the central claims made by the classical theistic tradition, such as the claims that God is timeless, simple, and impassible, should be rejected. Still, Wolterstorff contends, rejecting the classical conception of God does not imply that theists should accept the Kantian view according to which God cannot be known. Of interest to both philosophers and theologians, Inquiring about God should give the reader a lively sense of the creative and powerful work done in contemporary philosophical theology by one of its foremost practitioners.
This 2007 volume contains survey articles based on the invited lectures given at the Twenty-first British Combinatorial Conference, held in July 2007 at the University of Reading. This biennial conference is a well-established international event and the articles are of the high quality that befits the event. By its nature this volume provides an overview of current research activity in several areas of combinatorics, ranging from graph theory to current applications of combinatorial mathematics, including efficient approximability of NP-hard optimization problems and cryptographic key management. The authors are some of the world's foremost researchers in their fields, and here they summarize existing results, and give a unique preview of work currently being written up. The book provides a valuable survey of the state of knowledge in combinatorics. It will be useful to research workers and advanced graduate students, primarily in mathematics but also in computer science, statistics and engineering.
This volume contains the invited lectures given at the Sixteenth British Combinatorial Conference, held in July 1997 at Queen Mary and Westfield College, University of London. This biennial conference is a well-established international event, with speakers from all over the world. Contained here is a survey of some of the most important work ever in graph theory, with related papers that will be essential background reading to anyone doing research in this field. Also included is an illustration of how recent developments in group theory lead to advances in graph theory, and an exciting new construction of one of the Mathieu groups. Other articles show how to construct a block design, and how to use finite geometries. An account is given of the computational complexity of counting. The book provides a valuable survey of the present state of knowledge in combinatorics. It will be useful to research workers and advanced graduate students, primarily in mathematics but also in computer science, statistics and engineering.
Following on from the successful Women in Management: Current Research Issues, this volume provides an up-to-date and comprehensive overview of current international research findings pertaining to women in management, reflecting recent global changes and issues. Like its predecessor, this volume brings together an international group of eminent academics, who review the major contemporary issues facing women in management, as well as the individual, organizational, and governmental consequences of these changes. Women in Management: Current Issues in Research II will be a vital resource for scholars and students in management, business, occupational psychology, industrial sociology, and gender studies. In addition, related work groups such as Personnel, Occupational Management, Management Consultants, and Trainers, as well as Trade Unionists should find this book essential to read.
Preface. 1 Philosophy of science and introduction to epidemiology. Introduction and learning objectives. 1.1 Approaches to scientific research. 1.2 Formulating a research question. 1.3 Rates: incidence and prevalence. 1.4 Concepts of prevention. 1.5 Answers to self-assessment exercises. 2 Routine data sources and descriptive epidemiology. Introduction and learning objectives. 2.1 Routine collection of health information. 2.2 Descriptive epidemiology. 2.3 Information on the environment. 2.4 Displaying, describing and presenting data. 2.5 Summary of routinely available data. 2.6 Descriptive epidemiology in action. 2.7 Overview of epidemiological study designs. 2.8 Answers to self-assessment exercises. 3 Standardisation. Introduction and learning objectives. 3.1 Health inequalities in Merseyside. 3.2 Indirect standardisation: calculation of the standardised mortality ratio (SMR). 3.3 Direct standardisation. 3.4 Standardisation for factors other than age. 3.5 Answers to self-assessment exercises. 4 Surveys. Introduction and learning objectives. 4.1 Purpose and context. 4.2 Sampling methods. 4.3 The sampling frame. 4.4 Sampling error, confidence intervals and sample size. 4.5 Response 4.6 Measurement. 4.7 Data types and presentation. 4.8 Answers to self-assessment exercises. 5 Cohort studies. Introduction and learning objectives. 5.1 Why do a cohort study? 5.2 Obtaining the sample. 5.3 Measurement. 5.4 Follow-up. 5.5 Basic presentation and analysis of results. 5.6 How large should a cohort study be? 5.7 Confounding. 5.8 Simple linear regression. 5.9 Introduction to multiple linear regression. 5.10 Answers to self-assessment exercises. 6 Case-control studies. Introduction and learning objectives. 6.1 Why do a case-control study? 6.2 Key elements of study design. 6.3 Basic unmatched and matched analysis. 6.4 Sample size for a case-control study. 6.5 Confounding and logistic regression. 6.6 Answers to self-assessment exercises. 7 Intervention studies. Introduction and learning objectives. 7.1 Why do an intervention study? 7.2 Key elements of intervention study design. 7.3 The analysis of intervention studies. 7.4 Testing more complex interventions. 7.5 How big should the trial be? 7.6 Further aspects of intervention study design and analysis. 7.7 Answers to self-assessment exercises. 8 Life tables, survival analysis and Cox regression. Introduction and learning objectives. 8.1 Survival analysis. 8.2 Cox regression. 8.3 Current life tables. 8.4 Answers to self-assessment exercises. 9 Systematic reviews and meta-analysis. Introduction and learning objectives. 9.1 The why and how of systematic reviews. 9.2 The methodology of meta-analysis. 9.3 Systematic reviews and meta-analyses of observational studies. 9.4 The Cochrane Collaboration. 9.5 Answers to self-assessment exercises. 10 Prevention strategies and evaluation of screening. Introduction and learning objectives. 10.1 Concepts of risk. 10.2 Strategies of prevention. 10.3 Evaluation of screening programmes. 10.4 Cohort and period effects. 10.5 Answers to self-assessment exercises. 11 Probability distributions, hypothesis testing and Bayesian methods. Introduction and learning objectives. 11.1 Probability distributions. 11.2 Data that do not 'fit' a probability distribution. 11.3 Hypothesis testing. 11.4 Choosing an appropriate hypothesis test. 11.5 Bayesian methods. 11.6 Answers to self-assessment exercises. References. Index.
The British Combinatorial Conference is one of the most well known meetings for combinatorialists. This volume collects the invited talks from the 1999 conference held at the University of Kent and together these span a broad range of combinatorial topics. The nine talks are from: S. Ball, J. Dinitz, M. Dyer, K. Metsch, J. Pach, R. Thomas, C. Thomassen, N. Wormald, plus a special contribution from W. T. Tutte. All researchers into combinatorics will find this volume an outstanding and up-to-date resource.
This volume contains nine survey articles based on the invited lectures given at the 24th British Combinatorial Conference, held at Royal Holloway, University of London in July 2013. This biennial conference is a well-established international event, with speakers from around the world. The volume provides an up-to-date overview of current research in several areas of combinatorics, including graph theory, matroid theory and automatic counting, as well as connections to coding theory and Bent functions. Each article is clearly written and assumes little prior knowledge on the part of the reader. The authors are some of the world's foremost researchers in their fields, and here they summarise existing results and give a unique preview of cutting-edge developments. The book provides a valuable survey of the present state of knowledge in combinatorics, and will be useful to researchers and advanced graduate students, primarily in mathematics but also in computer science and statistics.
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