More Statistical And Methodological Myths And Urban Legends

This book provides an up-to-date review of commonly undertaken methodological and statistical practices that are sustained, in part, upon sound rationale and justification and, in part, upon unfounded lore. Some examples of these "methodological urban legends", as we refer to them in this book, are characterized by manuscript critiques such as: (a) "your self-report measures suffer from common method bias"; (b) "your item-to-subject ratios are too low"; (c) "you can’t generalize these findings to the real world"; or (d) "your effect sizes are too low". Historically, there is a kernel of truth to most of these legends, but in many cases that truth has been long forgotten, ignored or embellished beyond recognition. This book examines several such legends. Each chapter is organized to address: (a) what the legend is that "we (almost) all know to be true"; (b) what the "kernel of truth" is to each legend; (c) what the myths are that have developed around this kernel of truth; and (d) what the state of the practice should be. This book meets an important need for the accumulation and integration of these methodological and statistical practices.

This book provides an up-to-date review of commonly undertaken methodological and statistical practices that are based partially in sound scientific rationale and partially in unfounded lore. Some examples of these “methodological urban legends” are characterized by manuscript critiques such as: (a) “your self-report measures suffer from common method bias”; (b) “your item-to-subject ratios are too low”; (c) “you can’t generalize these findings to the real world”; or (d) “your effect sizes are too low.” What do these critiques mean, and what is their historical basis? More Statistical and Methodological Myths and Urban Legends catalogs several of these quirky practices and outlines proper research techniques. Topics covered include sample size requirements, missing data bias in correlation matrices, negative wording in survey research, and much more.

This book provides an up-to-date review of commonly undertaken methodological and statistical practices that are based partially in sound scientific rationale and partially in unfounded lore. Some examples of these “methodological urban legends” are characterized by manuscript critiques such as: (a) “your self-report measures suffer from common method bias”; (b) “your item-to-subject ratios are too low”; (c) “you can’t generalize these findings to the real world”; or (d) “your effect sizes are too low.” What do these critiques mean, and what is their historical basis? More Statistical and Methodological Myths and Urban Legends catalogs several of these quirky practices and outlines proper research techniques. Topics covered include sample size requirements, missing data bias in correlation matrices, negative wording in survey research, and much more.

Research Methodology remains a vital issue at the heart of all scholarly activity. Without a proper appreciation of Research Methodology and its correct application academic progress is not possible. One of the problems which Research Methodology offers the learner is the very wide range of options which are frequently available with which to answer a research question and this high level of choice can lead to indecision and sometimes confusion. This book is a compilation of a number of important papers on this subject selected by two leaders in this field of study. A wide range of topic have been chosen which lead the reader through some of the more important considerations in the field. The book is designed to help with this type of problem and the the current selection of papers which highlight a variety of research questions, problems and issues and an accompanying range of research methods and methodological discussions. Their authors have stated the research positions they have adopted and respective levels of justification and knowledge forms have been presented. These range from those forms of knowledge that might be found of use to practitioners to those that are more philosophically or academically inclined. A certain level of research impact is either implied or overtly presented in the selected papers. This book is an important text for academics, researchers and students as well as those interested in using research from a commercial point of view.

Strategic management relies on an array of complex methods drawn from various allied disciplines to examine how managers attempt to lead their firms toward success. This book provides a forum for critique, commentary, and discussion about key research methodology issues in the strategic management field.

This research monograph provides a synthesis of a number of statistical tests and measures, which, at first consideration, appear disjoint and unrelated. Numerous comparisons of permutation and classical statistical methods are presented, and the two methods are compared via probability values and, where appropriate, measures of effect size. Permutation statistical methods, compared to classical statistical methods, do not rely on theoretical distributions, avoid the usual assumptions of normality and homogeneity of variance, and depend only on the data at hand. This text takes a unique approach to explaining statistics by integrating a large variety of statistical methods, and establishing the rigor of a topic that to many may seem to be a nascent field in statistics. This topic is new in that it took modern computing power to make permutation methods available to people working in the mainstream of research. lly-informed="" audience,="" and="" can="" also="" easily="" serve="" as="" textbook="" in="" graduate="" course="" departments="" such="" statistics,="" psychology,="" or="" biology.="" particular,="" the="" audience="" for="" book="" is="" teachers="" of="" practicing="" statisticians,="" applied="" quantitative="" students="" fields="" medical="" research,="" epidemiology,="" public="" health,="" biology.

Research in entrepreneurship has been booming, with perspectives from a range of disciplines and numerous developing schools of thought. It can be difficult for young scholars and even long-time researchers to find their way through the lush garden of ideas we see before us. The purpose of this book is to map the research terrain of entrepreneurship, providing the perfect starting point for new and existing researchers looking to explore. Topics covered range from emerging perspective, through issues at the core of the field to innovative methodologies. Starting off with a preface by Bill Gartner, each section of the book brings together a world class set of established leading researchers and rising stars. This considered, comprehensive and conclusive companion integrates the recent debates in entrepreneurship research under one cover, to provide a resource which will be useful across disciplinary boundaries and for a whole range of students and researchers.