Contrasts are statistical procedures for asking focused questions of data. Compared to diffuse or omnibus questions, focused questions are characterized by greater conceptual clarity and greater statistical power when examining those focused questions. If an effect truly exists, we are more likely to discover it and to believe it to be real when asking focused questions rather than omnibus ones. Researchers, teachers of research methods and graduate students will be familiar with the principles and procedures of contrast analysis, but will also be introduced to a series of newly developed concepts, measures, and indices that permit a wider and more useful application of contrast analysis. This volume takes on this new approach by introducing a family of correlational effect size estimates.
This book is really three-books-in-one, dealing with the topic of artifacts in behavioral research. It is about the problems of experimenter effects which have not been solved. Experimenters still differ in the ways in which they see, interpret, and manipulate their data. Experimenters still obtain different responses from research participants (human or infrahuman) as a function of experimenters' states and traits of biosocial, psychosocial, and situational origins. Experimenters' expectations still serve too often as self-fulfilling prophecies, a problem that biomedical researchers have acknowledged and guarded against better than have behavioral researchers; e.g., many biomedical studies would be considered of unpublishable quality had their experimenters not been blind to experimental condition. Problems of participant or subject effects have also not been solved. Researchers usually still draw research samples from a population of volunteers that differ along many dimensions from those not finding their way into our research. Research participants are still often suspicious of experimenters' intent, try to figure out what experimenters are after, and are concerned about what the experimenter thinks of them. That portion of the complexity of human behavior that can be attributed to the social nature of behavioral research can be conceptualized as a set of artifacts to be isolated, measured, considered, and, sometimes, eliminated. This book examines the methodological and substantive implications of sources of artifacts in behavioral research and strategies for improving this situation.
We describe convenient statistical procedures that will enable research consumers (e.g., professional psychologists, graduate students, and researchers themselves) to reach beyond the published conclusions and make an independent assessment of the reported results. Appropriately conceived contrasts accompanied by effect size estimates often allow researchers to address precise predictions that the authors of the published report may have ignored or abandoned prematurely. We describe the use of t, F, and Z to compute contrasts with different raw ingredients, and we review 3 effect size indices (Cohen's d, Hedges's g, and the Pearson r) and a way of displaying the magnitude of any effect size r. We also describe how to construct confidence limits for the obtained effect as well as its null-counternull interval.Following in the wake of Jacob Cohen's seminal work on the utility of effect sizes and the neglect of statistical power in psychological research (e.g., Cohen, 1962Cohen, , 1965Cohen, , 1969, there has been a surge of interest in these issues (e.g., Judd, McClelland, & Culhane, 1995). Cohen not only provided researchers with an elegant and useful discussion of effect sizes and power analysis (e.g., Cohen, 1969Cohen, , 1988, but he also pioneered in the empirical work showing that significance testing in psychology was conducted with a remarkably high risk of committing Type II
Justification, in the vernacular language of philosophy of science, refers to the evaluation, defense, and confirmation of claims of truth. In this article, we examine some aspects of the rhetoric of justification, which in part draws on statistical data analysis to shore up facts and inductive inferences. There are a number of problems of methodological spirit and substance that in the past have been resistant to attempts to correct them. The major problems are discussed, and readers are reminded of ways to clear away these obstacles to justification.
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