Inferentialism as a theory of meaning builds on the idea that what a linguistic expression means depends exclusively on the inferential rules that govern its use. Following different strategies and exploring various case studies, the authors of this collection of essays discuss under what circumstances and to what extent the central tenets of inferentialism are tenable. The essays in this volume present the results of a three-year research project “Representation and Inference” which was conducted from the beginning of 2008 to the end 2010. The aim of the project was to assess the research program of inferentialism as it has been pursued recently by Robert Brandom, Mark Lance, and Jaroslav Peregrin. Earlier versions of these texts were presented at the conference “Inference, Consequence, and Meaning” held in Sofia on the 3rd and 4th of December, 2008.

In this study two strands of inferentialism are brought together: the philosophical doctrine of Brandom, according to which meanings are generally inferential roles, and the logical doctrine prioritizing proof-theory over model theory and approaching meaning in logical, especially proof-theoretical terms.

The question of what types of data and evidence can be used is one of the most important topics in linguistics. This book is the first to comprehensively present the methodological problems associated with linguistic data and evidence. Its originality is twofold. First, the authors' approach accounts for a series of unexplained characteristics of linguistic theorising: the uncertainty and diversity of data, the role of evidence in the evaluation of hypotheses, the problem solving strategies as well as the emergence and resolution of inconsistencies. Second, the findings are obtained by the application of a new model of plausible argumentation which is also of relevance from a general argumentation theoretical point of view. All concepts and theses are systematically introduced and illustrated by a number of examples from different linguistic theories, and a detailed case-study section shows how the proposed model can be applied to specific linguistic problems.

How do hearers manage to understand speakers? And how do speakers manage to shape hearers' understanding? Lepore and Stone show that standard views about the workings of semantics and pragmatics are unsatisfactory. They advance an alternative view which better captures what is going on in linguistic communication.

The aim of this book is to correct a common misunderstanding of a technique of mathematical logic.

Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.

Logical consequence is the relation that obtains between premises and conclusion(s) in a valid argument. Orthodoxy has it that valid arguments are necessarily truth-preserving, but this platitude only raises a number of further questions, such as: how does the truth of premises guarantee the truth of a conclusion, and what constraints does validity impose on rational belief? This volume presents thirteen essays by some of the most important scholars in the field of philosophical logic. The essays offer ground-breaking new insights into the nature of logical consequence; the relation between logic and inference; how the semantics and pragmatics of natural language bear on logic; the relativity of logic; and the structural properties of the consequence relation.

Offering a new take on the LSAT logical reasoning section, the Manhattan Prep Logical Reasoning LSAT Strategy Guide is a must-have resource for any student preparing to take the exam. Containing the best of Manhattan Prep’s expert strategies, this book will teach you how to untangle the web of LSAT logical reasoning questions confidently and efficiently. Avoiding an unwieldy and ineffective focus on memorizing sub-categories and steps, the Logical Reasoning LSAT Strategy Guide encourages a streamlined method that engages and improves your natural critical-thinking skills. Beginning with an effective approach to reading arguments and identifying answers, this book trains you to see through the clutter and recognize the core of an argument. It also arms you with the tools needed to pick apart the answer choices, offering in-depth explanations for every single answer – both correct and incorrect – leading to a complex understanding of this subtle section. Each chapter in the Logical Reasoning LSAT Strategy Guide uses real LSAT questions in drills and practice sets, with explanations that take you inside the mind of an LSAT expert as they work their way through the problem. Further practice sets and other additional resources are included online and can be accessed through the Manhattan Prep website. Used by itself or with other Manhattan Prep materials, the Logical Reasoning LSAT Strategy Guide will push you to your top score.

Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.