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<h1>Getting started with the "New" Statistics</h1> <p>This is the OSF page for a workshop on getting started with the "New Statistics" that will be given 12:30pm Pacific Time on June 22, 2020 during the SIPS 2020 virtual meeting. </p> <p>The workshop is organized by Bob Calin-Jageman with assistance from moderators TJ Krafnick, Persis Driver, and Geoff Cumming.</p> <p>Here you will find:</p> <ul> <li><a href="https://osf.io/at8kg/download" rel="nofollow">The slides from the workshop</a> </li> <li><a href="https://osf.io/wdq8m/" rel="nofollow">The sample data for the workshop</a></li> <li><a href="https://osf.io/d89xg/wiki/tools:%20esci%20for%20jamovi/" rel="nofollow">Instructions on how obtain esci for jamovi</a>, the main tool we'll use for estimating parameters for different research designs</li> <li><a href="https://osf.io/d89xg/wiki/tools:%20esci%20for%20R/" rel="nofollow">Instructions on how to obtain and use the esci package for R</a>, a still-in-development package for obtaining estimates for different research designs</li> <li><a href="https://osf.io/d89xg/wiki/data:%20data%20from%20multi-lab%20psych%20studies%20for%20teaching%20statistics/" rel="nofollow">Links to sample data that you can use to teach the estimation approach</a></li> <li>(eventually) A video of the workshop.</li> </ul> <h2>Resources for going forward</h2> <h3>Teaching the New Stats</h3> <ul> <li>Videos to use with a flipped classroom: <a href="https://www.youtube.com/user/geoffdcumming" rel="nofollow">https://www.youtube.com/user/geoffdcumming</a></li> <li>Datasets from multi-lab psych studies: <a href="https://github.com/rcalinjageman/MultiLab_Datasets_For_Teaching" rel="nofollow">https://github.com/rcalinjageman/MultiLab_Datasets_For_Teaching</a></li> <li>Touch base with Bob for a complete set of instructor materials</li> <li>Share materials back to the community via this OSF page: <a href="https://osf.io/muy6u/" rel="nofollow">https://osf.io/muy6u/</a> </li> </ul> <h3>Some Suggested Readings</h3> <ul> <li>Frequentist Estimation: Cumming, G., & Calin-Jageman, R. J. (2017). Introduction to the new statistics: Estimation, open science, and beyond. New York: Routledge. Request a free desk copy here: <a href="https://www.routledge.com/textbooks/evaluation/9781138825529" rel="nofollow">https://www.routledge.com/textbooks/evaluation/9781138825529</a> </li> <li>Bootstrap Estimation: Hesterberg, T. C. (2015). What Teachers Should Know About the Bootstrap: Resampling in the Undergraduate Statistics Curriculum. American Statistician, 69(4), 371–386. <a href="https://doi.org/10.1080/00031305.2015.1089789" rel="nofollow">https://doi.org/10.1080/00031305.2015.1089789</a></li> <li>Bayesian Estimation - Kruschke, J. K., & Liddell, T. M. (2018). The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective. Psychonomic Bulletin & Review, 25(1), 178–206. <a href="https://doi.org/10.3758/s13423-016-1221-4" rel="nofollow">https://doi.org/10.3758/s13423-016-1221-4</a></li> <li>When testing, do better with inference by interval - Lakens, D. (2017). Equivalence Tests: A Practical Primer for t Tests, Correlations, and Meta-Analyses. Social Psychological and Personality Science, 8(4), 355–362. <a href="https://doi.org/10.1177/1948550617697177" rel="nofollow">https://doi.org/10.1177/1948550617697177</a></li> <li>Planning for Precision - Rothman, K. J., & Greenland, S. (2018). Planning Study Size Based on Precision Rather Than Power. Epidemiology, 29(5), 599–603. <a href="https://doi.org/10.1097/EDE.0000000000000876" rel="nofollow">https://doi.org/10.1097/EDE.0000000000000876</a></li> <li>Planning for evidence - Schönbrodt, F. D., & Wagenmakers, E.-J. (2017). Bayes factor design analysis: Planning for compelling evidence. Psychonomic Bulletin & Review, 1–16. <a href="https://doi.org/10.3758/s13423-017-1230-y" rel="nofollow">https://doi.org/10.3758/s13423-017-1230-y</a></li> </ul> <h3>Software</h3> <p>Frequentists estimation (confidence intervals) <em> esci module for jamovi - <a href="https://osf.io/d89xg/wiki/tools:%20esci%20for%20jamovi/" rel="nofollow">https://osf.io/d89xg/wiki/tools:%20esci%20for%20jamovi/</a> </em> Guide to esci package for R - <a href="https://osf.io/d89xg/wiki/tools:%20esci%20for%20R/" rel="nofollow">https://osf.io/d89xg/wiki/tools:%20esci%20for%20R/</a> * Esci for jamovi… still in progress</p> <p>Boostrapped intervals * DABEST for R, python, and web-interface - <a href="http://www.estimationstats.com/" rel="nofollow">http://www.estimationstats.com/</a> </p> <p>Bayesian Estimation (credible intervals) <em> JASP - <a href="https://jasp-stats.org/" rel="nofollow">https://jasp-stats.org/</a> </em> BEST package for R - <a href="https://cran.r-project.org/web/packages/BEST/" rel="nofollow">https://cran.r-project.org/web/packages/BEST/</a> </p>
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