Jason Roy – författare

Bayesian Nonparametrics for Causal Inference and Missing Data provides an overview of flexible Bayesian nonparametric (BNP) methods for modeling joint or conditional distributions and functional relationships, and their interplay with causal inference and missing data. This book emphasizes the importance of making untestable assumptions to identify estimands of interest, such as missing at random assumption for missing data and unconfoundedness for causal inference in observational studies. Unlike parametric methods, the BNP approach can account for possible violations of assumptions and minimize concerns about model misspecification. The overall strategy is to first specify BNP models for observed data and then to specify additional uncheckable assumptions to identify estimands of interest.The book is divided into three parts. Part I develops the key concepts in causal inference and missing data and reviews relevant concepts in Bayesian inference. Part II introduces the fundamental BNP tools required to address causal inference and missing data problems. Part III shows how the BNP approach can be applied in a variety of case studies. The datasets in the case studies come from electronic health records data, survey data, cohort studies, and randomized clinical trials.Features• Thorough discussion of both BNP and its interplay with causal inference and missing data• How to use BNP and g-computation for causal inference and non-ignorable missingness• How to derive and calibrate sensitivity parameters to assess sensitivity to deviations from uncheckable causal and/or missingness assumptions• Detailed case studies illustrating the application of BNP methods to causal inference and missing data• R code and/or packages to implement BNP in causal inference and missing data problemsThe book is primarily aimed at researchers and graduate students from statistics and biostatistics. It will also serve as a useful practical reference for mathematically sophisticated epidemiologists and medical researchers.

Public opinion polls have become increasingly prominent during elections, but how they affect voting behaviour remains uncertain. In this work, we estimate the effects of poll exposure using an experimental design in which we randomly assign the availability of polls to participants in simulated election campaigns. We draw upon results from ten independent experiments conducted across six countries on four continents (Argentina, Australia, Canada, New Zealand, the United Kingdom, and the United States) to examine how polls affect the amount of information individuals seek and the votes that they cast. We further assess how poll effects differ according to individual-level factors, such as partisanship and political sophistication, and the content included in polls and how it is presented. Our work provides a comprehensive assessment of the power of polls and the implications for poll reporting in contemporary elections.

Biostatistics for the Biological and Health Sciences brings statistical theories and methods to life with real applications, emphasis on real data, and a friendly writing style. It suits a variety of students in their first statistics course and uses minimal algebra. Abundant examples and emphasis on real data help you develop skills in critical thinking, technology and communication. This collaboration from 2 biological sciences experts and the author of the #1 statistics book is an excellent introduction that is also highly readable, understandable and relevant.

The 3rd Edition incorporates the latest methods used by professional statisticians. It offers a wealth of new data sets, examples, and exercises (such as those involving clinical trials, COVID-19, biometrics, and anthropometrics) and includes features that address all recommendations included in the Guidelines for Assessment and Instruction in Statistics Education (GAISE) as recommended by the American Statistical Association.

Biostatistics for the Biological and Health Sciences brings statistical theories and methods to life with real applications, emphasis on real data, and a friendly writing style. It suits a variety of students in their first statistics course and uses minimal algebra. Abundant examples and emphasis on real data help you develop skills in critical thinking, technology and communication. This collaboration from 2 biological sciences experts and the author of the #1 statistics book is an excellent introduction that is also highly readable, understandable and relevant.

The 3rd Edition incorporates the latest methods used by professional statisticians. It offers a wealth of new data sets, examples, and exercises (such as those involving clinical trials, COVID-19, biometrics, and anthropometrics) and includes features that address all recommendations included in the Guidelines for Assessment and Instruction in Statistics Education (GAISE) as recommended by the American Statistical Association.

Biostatistics for the Biological and Health Sciences brings statistical theories and methods to life with real applications, emphasis on real data, and a friendly writing style. It suits a variety of students in their first statistics course and uses minimal algebra. Abundant examples and emphasis on real data help you develop skills in critical thinking, technology and communication. This collaboration from 2 biological sciences experts and the author of the #1 statistics book is an excellent introduction that is also highly readable, understandable and relevant.

The 3rd Edition incorporates the latest methods used by professional statisticians. It offers a wealth of new data sets, examples, and exercises (such as those involving clinical trials, COVID-19, biometrics, and anthropometrics) and includes features that address all recommendations included in the Guidelines for Assessment and Instruction in Statistics Education (GAISE) as recommended by the American Statistical Association.

Biostatistics for the Biological and Health Sciences brings statistical theories and methods to life with real applications, emphasis on real data, and a friendly writing style. It suits a variety of students in their first statistics course and uses minimal algebra. Abundant examples and emphasis on real data help you develop skills in critical thinking, technology and communication. This collaboration from 2 biological sciences experts and the author of the #1 statistics book is an excellent introduction that is also highly readable, understandable and relevant.

The 3rd Edition incorporates the latest methods used by professional statisticians. It offers a wealth of new data sets, examples, and exercises (such as those involving clinical trials, COVID-19, biometrics, and anthropometrics) and includes features that address all recommendations included in the Guidelines for Assessment and Instruction in Statistics Education (GAISE) as recommended by the American Statistical Association.

Biostatistics for the Biological and Health Sciences brings statistical theories and methods to life with real applications, emphasis on real data, and a friendly writing style. It suits a variety of students in their first statistics course and uses minimal algebra. Abundant examples and emphasis on real data help you develop skills in critical thinking, technology and communication. This collaboration from 2 biological sciences experts and the author of the #1 statistics book is an excellent introduction that is also highly readable, understandable and relevant.

The 3rd Edition incorporates the latest methods used by professional statisticians. It offers a wealth of new data sets, examples, and exercises (such as those involving clinical trials, COVID-19, biometrics, and anthropometrics) and includes features that address all recommendations included in the Guidelines for Assessment and Instruction in Statistics Education (GAISE) as recommended by the American Statistical Association.

Biostatistics for the Biological and Health Sciences brings statistical theories and methods to life with real applications, emphasis on real data, and a friendly writing style. It suits a variety of students in their first statistics course and uses minimal algebra. Abundant examples and emphasis on real data help you develop skills in critical thinking, technology and communication. This collaboration from 2 biological sciences experts and the author of the #1 statistics book is an excellent introduction that is also highly readable, understandable and relevant.

The 3rd Edition incorporates the latest methods used by professional statisticians. It offers a wealth of new data sets, examples, and exercises (such as those involving clinical trials, COVID-19, biometrics, and anthropometrics) and includes features that address all recommendations included in the Guidelines for Assessment and Instruction in Statistics Education (GAISE) as recommended by the American Statistical Association.

Do negative campaigns win elections? Do voters abandon candidates accused of scandalous behaviour? Do government apologies affect prospects for re-election? While many people assume the answer to each of these questions is yes, there is limited empirical evidence to support these assumptions. In this book, Jason Roy and Christopher Alcantara use a series of experiments to test these and other commonly held beliefs. Each chapter draws upon contemporary events and literature to frame the issues and strategies. The findings suggest that not all of the assumptions that people have about the best strategies for winning and keeping political power hold up to empirical scrutiny. In fact, some work in ways that many readers may find surprising. Original and innovative in its use of experimental methods, Winning and Keeping Power in Canadian Politics is a persuasive analysis of some of our most prominent and long-standing political myths. It will be a "go to" resource for journalists, strategists, scholars, and general readers alike.

Do negative campaigns win elections? Do voters abandon candidates accused of scandalous behaviour? Do government apologies affect prospects for re-election? While many people assume the answer to each of these questions is yes, there is limited empirical evidence to support these assumptions. In this book, Jason Roy and Christopher Alcantara use a series of experiments to test these and other commonly held beliefs. Each chapter draws upon contemporary events and literature to frame the issues and strategies. The findings suggest that not all of the assumptions that people have about the best strategies for winning and keeping political power hold up to empirical scrutiny. In fact, some work in ways that many readers may find surprising. Original and innovative in its use of experimental methods, Winning and Keeping Power in Canadian Politics is a persuasive analysis of some of our most prominent and long-standing political myths. It will be a "go to" resource for journalists, strategists, scholars, and general readers alike.