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Observation Oriented Modeling : Analysis of Cause in the Behavioral Sciences.

Author: James W Grice
Publisher: Burlington : Elsevier Science, 2011.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Grice, James W.
Observation Oriented Modeling : Analysis of Cause in the Behavioral Sciences.
Burlington : Elsevier Science, ©2011
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: James W Grice
ISBN: 9780123851956 0123851955
OCLC Number: 880750039
Description: 1 online resource (257 pages)
Contents: Front Cover; Observation Oriented Modeling; Copyright; Contents; Foreword; Dedication; Acknowledgments; Chapter 1 Introduction; Metaphysical and Methodological Errors; Observation Oriented Modeling and Philosophical Realism; Chapter 2 Data at Its Core; Introduction; Deep Structure; Multiple Observations; Deep Structure Addition and Subtraction; Deep Structure Multiplication and Division; Logical Operations and Deep Structure; Chapter 3 Rotating Deep Structures; Introduction; Procrustes Rotation; Binary Procrustes Rotation; Chapter 4 Modeling with Deep Structures; Introduction. A Simple ExperimentModeling the Experiment; Graphs Both Old and New; A Probability Statistic; Concluding Models and Summary; Chapter 5 Statistics and Null Hypothesis Significance Testing; Introduction; The Force of History; Null Hypothesis Significance Testing; Turning the Tide with Observation Oriented Modeling; Hybridized NHST; Chapter 6 Modeling and Inferential Statistics; Introduction; Modeling in Science; The Bystander Effect Model; Estimating Population Parameters in NHST; Modeling Persons, Testing Aggregates; Observation Oriented Modeling; Chapter 7 Modeling and Effect Sizes. IntroductionAggregate Effects; Differences Between Means; Correlation and Shared Variance; Chapter 8 Measurement and Additive Structures; Introduction; Continuous Quantitative Measurement; Measurement as Knowing Quantity; Observation Oriented Modeling; Additive Models; Measurement Error; Latent Variables; Chapter 9 Cause and Effect; Introduction; Causality and Causation; The Randomized Controlled Experiment; Mediation Models; Person-Centered Mediation Analysis; Logical Hypothesis Testing; Final, Formal, and Efficient Causes; Transition to the Four Causes; Chapter 10 Coda; Introduction. Seven Principles of Observation Oriented ModelingSummary; References; Index.

Abstract:

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.

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