Bioinformatics Club: "Path Analysis: The Algebra of Causality" (03/06/2018 Tuesday)
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Bioinformatics Club at BWH
Mar 4, 2018, 9:40:37 PM3/4/18
to Bioinformatics Club at BWH
Dear all,
This week we will invite Dr. Joseph J Locascio to talk about causality analysis. Dr. Lacascio is a senior biostatistician in Neurology and a well-known collaborating statistician in the BWH/MGH community. Here is the detail for his talk:
Time: March 6th (Tuesday), 1:00 - 2:00 PM
Place: BTM 9004
Summary:
Path Analysis (also referred to as Structural Equation Modeling, SEM, or causal modeling) is a method for systematically studying the possible causal models that may underlie an observed correlation matrix of variables. In path analysis, various explicitly detailed models of causal dynamics are hypothesized. Then the fit of the observed correlation matrix to what would be the correlation matrix predicted by a given hypothetical causal model is assessed. This is done in order to obtain support and greater specification for the proposed model and rule out as statistically improbable alternative models. Path analysis can be viewed as a specific statistical analysis method or as a more general methodological approach to research, i.e., an “algebra of causality”. I will discuss both points of view, but will emphasize more the latter. Path analysis methodology allows for a more fundamental and flexible approach to understanding some statistical techniques currently considered useful and important such as mediation/moderation analysis, factor analysis, latent variable analysis, multiple regression, partial correlation, and analysis of covariance.
Dr. Locascio has had a research appointment as a senior biostatistician for the Alzheimer’s Disease Research Center and Memory/Movement Disorders Units, Department of Neurology at Massachusetts General Hospital since 1992, and is an Assistant Professor of Neurology at Harvard Medical School. He had a dual appointment as a research statistician in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology (MIT) from 1992 to 2009 where he taught formal and informal data analysis courses. He is a Consulting Statistician for the Harvard Catalyst Bio-Statistical Consulting Group of Harvard Medical School and is a member of the Statistical Advisory Board for the journal PLOS One(Public Library of Science). He has also taught statistics at Northwestern University (1982) and worked as a statistician in psychiatric research at the University of Chicago (1983-1985) and Bellevue Hospital/New York University Medical Center (1989-1991).
Dr. Locascio has 90 publications in prestigious medical, scientific, and scholarly journals, magazines, and books.
This week we will invite Dr. Joseph J Locascio to talk about causality analysis. Dr. Lacascio is a senior biostatistician in Neurology and a well-known collaborating statistician in the BWH/MGH community. Here is the detail for his talk:
Time: March 6th (Tuesday), 1:00 - 2:00 PM
Place: BTM 9004
Summary:
Path Analysis (also referred to as Structural Equation Modeling, SEM, or causal modeling) is a method for systematically studying the possible causal models that may underlie an observed correlation matrix of variables. In path analysis, various explicitly detailed models of causal dynamics are hypothesized. Then the fit of the observed correlation matrix to what would be the correlation matrix predicted by a given hypothetical causal model is assessed. This is done in order to obtain support and greater specification for the proposed model and rule out as statistically improbable alternative models. Path analysis can be viewed as a specific statistical analysis method or as a more general methodological approach to research, i.e., an “algebra of causality”. I will discuss both points of view, but will emphasize more the latter. Path analysis methodology allows for a more fundamental and flexible approach to understanding some statistical techniques currently considered useful and important such as mediation/moderation analysis, factor analysis, latent variable analysis, multiple regression, partial correlation, and analysis of covariance.
Dr. Locascio has had a research appointment as a senior biostatistician for the Alzheimer’s Disease Research Center and Memory/Movement Disorders Units, Department of Neurology at Massachusetts General Hospital since 1992, and is an Assistant Professor of Neurology at Harvard Medical School. He had a dual appointment as a research statistician in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology (MIT) from 1992 to 2009 where he taught formal and informal data analysis courses. He is a Consulting Statistician for the Harvard Catalyst Bio-Statistical Consulting Group of Harvard Medical School and is a member of the Statistical Advisory Board for the journal PLOS One(Public Library of Science). He has also taught statistics at Northwestern University (1982) and worked as a statistician in psychiatric research at the University of Chicago (1983-1985) and Bellevue Hospital/New York University Medical Center (1989-1991).
Dr. Locascio has 90 publications in prestigious medical, scientific, and scholarly journals, magazines, and books.
The presentation slide will be available on http://bioinformatics.bwh.harvard.edu/ soon.
See you all,
Xianjun Dong, PhD
See you all,
Xianjun Dong, PhD
Dong, Xianjun
Mar 6, 2018, 11:54:47 AM3/6/18
to Bioinformatics Club at BWH, bwh-c...@researchlist.partners.org
Dear all,
Please remind to come for Dr. Joseph J Locascio’s talk at 1PM TODAY.
Title: Path Analysis: The Algebra of Causality
Time: 1PM, March 6th
Place: BTM 9004 conference room
Link to his presentation slides can be found here:
Thanks,
Xianjun Dong, PhD
----------------------------------------------------
Instructor in Neurology, Harvard Medical School
Director of Computational Neuroscience
Neurogenomics Laboratory and Parkinson Personalized Medicine
Brigham and Women's Hospital
Instructor in Neurology, Harvard Medical School
Building for Transformative Medicine,
60 Fenwood Road, 9002EE
Boston, MA 02115
Tel: +1-857-307-5423
Fax: +1-857-307-5476
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