Observation Oriented Modeling: Analysis of Cause in the Behavioral Sciences (Elsevier Science & Technology Books) - Tapa dura

Grice, James W.

 
9780123851949: Observation Oriented Modeling: Analysis of Cause in the Behavioral Sciences (Elsevier Science & Technology Books)

Sinopsis

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.

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Acerca del autor

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.

De la contraportada

Traditional methods of data analysis in psychology have long been criticized by scientists and philosophers, the American Psychological Association, and the National Institute for Mental Health. However up to now, no reasonable alternative had been presented. Observation Oriented Modeling (OOM) changes that. OOM is not just another statistical or data analysis methodology that relies upon effect sizes, p levels, or r-squares, but rather a straightforward evaluation of the precise consequences specified by a theory or hypothesis. OOM develops integrated models to accurately explain patterns of observation.

Observation Oriented Modeling introduces this new methodology, what it is and does to advance psychology as a science. Numerous examples are presented of how to interpret data using OOM, using free software for the Windows operating system provided to book buyers on an accompanying website. The software offers analysis options to replace t-tests, ANOVA, correlations, multiple regression, mediation analysis chi-square tests, and inter-rater reliability. The output and graphs generated by the software are easy to interpret, and all effect sizes are presented in a common metric: namely the number of observations correctly classified by the algorithm. While flexible and powerful, the software s interface and output are accessible to students at the undergraduate level.

Features:

  • Provides a new accurate means of data analysis
  • Offers integrated modeling
  • Contains numerous case examples of models and analysis
  • Free OOM data analysis software
  • Free user instruction manual

Software available at our companion Web Site: http://booksite.academicpress.com/grice/oom/

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Traditional methods of data analysis in psychology have long been criticized by scientists and philosophers, the American Psychological Association, and the National Institute for Mental Health. However up to now, no reasonable alternative had been presented. Observation Oriented Modeling (OOM) changes that. OOM is not just another statistical or data analysis methodology that relies upon effect sizes, p levels, or r-squares, but rather a straightforward evaluation of the precise consequences specified by a theory or hypothesis. OOM develops integrated models to accurately explain patterns of observation.

Observation Oriented Modeling introduces this new methodology, what it is and does to advance psychology as a science. Numerous examples are presented of how to interpret data using OOM, using free software for the Windows operating system provided to book buyers on an accompanying website. The software offers analysis options to replace t-tests, ANOVA, correlations, multiple regression, mediation analysis chi-square tests, and inter-rater reliability. The output and graphs generated by the software are easy to interpret, and all effect sizes are presented in a common metric: namely the number of observations correctly classified by the algorithm. While flexible and powerful, the software s interface and output are accessible to students at the undergraduate level.

Features:

  • Provides a new accurate means of data analysis

  • Offers integrated modeling

  • Contains numerous case examples of models and analysis

  • Free OOM data analysis software

  • Free user instruction manual

Software available at our companion Web Site: http://booksite.academicpress.com/grice/oom/

"Sobre este título" puede pertenecer a otra edición de este libro.