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Observation Oriented Modeling : Analysis of Cause in the Behavioral Sciences - James W. Grice

Observation Oriented Modeling

Analysis of Cause in the Behavioral Sciences


Published: 17th May 2011
Format: ePUB
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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 that has been written to accompany the book and will be provided free to book buyers on an accompanying website.

The software has a user-friendly interface, similar to SPSS and SAS , which are the two most commonly used software analysis packages, and the analysis options are flexible enough to replace numerous traditional techniques such as t-tests, ANOVA, correlation, multiple regression, mediation analysis, chi-square tests, factor analysis, and inter-rater reliability. The output and graphs generated by the software are also easy to interpret, and all effect sizes are presented in a common metric; namely, the number of observations correctly classified by the algorithm. The software is designed so that undergraduate students in psychology will have no difficulty learning how to use the software and interpreting the results of the analyses.

* 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 * Software for OOM comes free with the book * Accompanying website include svideo instruction on OOM use

Foreword by Paul Barrett


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

ISBN: 9780123851956
ISBN-10: 0123851955
Format: ePUB
Language: English
Number Of Pages: 256
Published: 17th May 2011
Publisher: Elsevier Science