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Daniël Lakens


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Daniel Lakens is an Associate Professor in the Human-Technology interaction group at Eindhoven University of Technology (TU/e). His areas of expertise include meta-science, research methods and applied statistics. Daniel’s main lines of empirical research focus on conceptual thought, similarity, and meaning. He also focuses on how to design and interpret studies, applied (meta)-statistics, and reward structures in science.  
3 books on the list
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Introduction to Meta-Analysis
Michael Borenstein - Apr 27, 2009
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This book provides a clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies. Meta-analysis has become a critically important tool in fields as diverse as medicine, pharmacology, epidemiology, education, psychology, business, and ecology. Introduction to Meta-Analysis Outlines the role of...
Daniël Lakens
Dec 16, 2020
@AV_SP As long as you have 2 groups, F = t*t. I would recommend reading Borenstein's book on meta-analysis if you are doing it for the first time and use metafor in R.      source
Theory Building
Robert Dubin - Feb 01, 1978
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Daniël Lakens
Feb 24, 2020
This is a dual appreciation tweet of 1) The book Theory Building by Dubin from 1969, which I highly recommend reading, and 2) the fact I could borrow it for free online from @internetarchive which is amazing (I'll return the book in 10 days if you want it)      source
Understanding Psychology as a Science
An Introduction to Scientific and Statistical Inference
Zoltan Dienes - Feb 14, 2008
Goodreads Rating
An accessible and illuminating exploration of the conceptual basisof scientific and statistical inference and the practical impact this has on conducting psychological research. The book encourages a critical discussion of the different approaches and looks at some of the most important thinkers and their influence....
Daniël Lakens
May 11, 2019
I highly recommend reading Zoltan Dienes' book on Understanding Psychology as a Science (also for non-psych!). One of the best books on philosophy of science, falsification, and different approaches to statistics: Absolutely a must read.      source