Observation Oriented Modeling

  • ID: 1768953
  • Book
  • 256 Pages
  • Elsevier Science and Technology
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This book introduces a new data analysis technique that addresses long standing criticisms of the current standard statistics. Observation Oriented Modelling presents the mathematics and techniques underlying the new method, discussing causality, modelling, and logical hypothesis testing. Examples of how to approach and interpret data using OOM are presented throughout the book, including analysis of several classic studies in psychology. These analyses are conducted using comprehensive software for the Windows operating system.

  • Describes the problems that statistics are meant to answer, why popularly used statistics often fail to fully answer the question, and how OOM overcomes these obstacles
  • Chapters include examples of statistical analysis using OOM
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Foreword by Paul Barrett

Acknowledgments

Chapter 1: Introduction

Chapter 2: Data at its core

Chapter 3: Rotating deep structures

Chapter 4: Modeling with deep structures

Chapter 5: Statistics and Null Hypothesis Significance Testing

Chapter 6: Modeling and inferential statistics

Chapter 7: Models and effect sizes

Chapter 8: Measurement and additive structures

Chapter 9: Cause and Effect

Chapter 10: Coda

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Grice, James W.
James W. Grice (B.S., Wright State University; Ph.D., University of new Mexico) is a professor of psychology at Oklahoma State University. his work appears in such journals as Multivariate Behavioral Research, Psychological Methods, and the Journal of Personality. His computer program, Idiogrid, is in circulation in over 30 different countries worldwide.
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