Open Science Teaching and Training Resources
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Link to resourceAuthorTitle / citationType (video, blog, paper, etc.)Level (beginner, intermediate, etc.)CommentkeywordsYearLength / Time needed to view or absorbmeta keyword
2 GallistelBayes for Beginners: Probability and Liklihood beginner
3 BohannonI Fooled Millions Into Thinking Chocolate Helps Weight Loss. Here's How.ArticleBeginner2015
4 O'HaganArticlesbeginnerBayes Factors
5, Bayes
6 & McCulloughArticlesintermediatePETPEESE application, ego depletion
7, BenBad Science blog on the Guardian webpagesblogintermediate2011
8, BenBad Science log, post-Guardianblogintermediate2015
9 InzlichtA tale of two papersBlogfile drawer
10 VazireWhy p=.048 should be rareBlogp-values
11 LakensAlways use Welch t-testBlogintermediatet-test
12 LakensData peeking without p-hackingBlogintermediatesequential testing
13 LakensWhat is a p-value?Blogbeginnerp-values
14 GervaisBlogClass Projectp-curveassessing evidence
15 GervaisBlogp-curveassessing evidence
16 HughesBlogp-curve, R indexassessing evidence
17 applicationassessing evidence
18 evidence
19 SchimmackBlogTIVA
20 EtzBlogintermediatelikelihood
21 EtzBlogintermediateBayes Factorsstatistical inference
22 FunderBlogbeginnerBayes statistical inference
23 inference
24 SchimmackBlogintermediatecriticismBayes Factors
25 software
26 SimonsohnBlogadvancedBayes Factors
27 RouderBlogadvancedresponse to Uri SimonsohnBayes Factors
28 MoreyBlogintermediateR package tutorial
29 MagnussonUnderstanding Statistical Power and Significance Testing: an interactive visualizationblogbeginngervisualization
30 MagnussonBayesian inferenceblogvisualization
31 MagnussonP-curve visualization updated with log x-axisblogvisualization
32 MagnussonThe t-distritbution and its normal approximationblogvisualization
33 MagnussonUsing R and lme/lmer to fit different two- and three- level longitudinal modelsblog
34 MagnussonDistribution of p-values when comparing two groupsblogvisualization
35 MagnussonInterpreting confidence intervalsblogvisualization
36 MagnussonInterpreting correlationsblogvisualization
37 MagnussonExpected overestiationg of Cohen's d under publication biasblogvisualization
38 MagnussonInterpreting cohen's d effect sizeblogvisualization
39 MagnussonCalculating the overlap of two normal distributions using monte carlo intergrationblog
40 MagnussonVisualizing a one-way ANOVAblogvisualization
41 MagnussonHow to tell when error bars correspond to a significant p-valueblog
42 MagnussonEffect of sample size on teh accuracy of Cohen's d estimatesblog
43 MagnussonShort R script to plot effect sizes (Cohen's d) and share overlapping areblog
44, JohnTutorial/R code for creating scree/parallel analysis plotsBlogIntermediateR; data-visualization; factor analysis
45, JohnTutorial/R code for creating funnel/forest plotsBlogIntermediateR; data-visualization; meta-analysis
46, JohnTutorial/R code for creating plots for 2-way interactionsBlogIntermediateR; data-visualization; interactions
47 BishopThe Amazing Significo: why researchers need to understand pokerBlogBeginnerp-hacking
48 SrivastavaThe Hardest ScienceBlogvarious
49 psyborgs lab, PettitReplication in Psychology: a historical perspectiveblogbeginningreproducibility2015
50 Gelmanblogvariousstatistical analysis, research methods, repoducibility
51, AndrewStatistical Modeling, Causal Inference, and Social ScienceBlogIntermediatestatistical inference
52 Watch: Michael LaCour archivesBlogIntermediateCollection of articles about the faking of data, discovery through replication attempt
53 DotschDegrees of Freedom Tutorialblogbeginnerexplanation about degrees of freedom for ANOVA2015statistics
54 GrantBlog advancedBayes, frequentiststatistical inference
55 EtzBlog (I think it is now also a paper?)Bayes, replication projectstatistical inference
56 Incidental EconomistPre-registration of clinical trials is associated with fewer positive findingsBlog postBeginner
57 StapelFaking Science: A True Story of Academic FraudBookintro, intermediate2014
58, G. (2012). Understanding the new statistics: Effect sizes, confidence intervals, and meta-analysis. New York: Routledge.Book
59, Z. (2008). Understanding psychology as a science: An introduction to scientific and statistical inference. Palgrave Macmillan.bookbeginnerCompanion Website:; Likelihoods; Bayesian Statistics; Frequentist Statistics; Philosophy of Science2008Philosophy of Science
60, R. (1997). Statistical evidence: A likelihood paradigm. CRC Press.bookadvancedLikelihood1997statistical inference
Plucker & MakelDoing Good Social Science: Trust, Accuracy, Transparencybookbeginneredited volume collecting perspectivesin press
62 & FrenchLatent Variable Modeling with RBooksIntermediate-AdvancedBook for EFA/CFA/IRT/LCA in RR; latent variable; statisticsstatistical inference
63 et al.,Applied Multiple Regression/Correlation Analysis for the Behavioral SciencesBooksIntermediate-AdvancedComprehensive resource for regression modelsStatistics; regressionstatistical inference
64 & BoskerMultilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling 1st EditionBooksIntermediate-AdvancedMultilevel modeling resourceStatistics; MLM; HLMstatistical inference
65 & JacobyTheory Construction and Model-Building Skills: A Practical Guide for Social Scientists BooksBeginner-AdvancedIntroduction to how to generate/conceptualize theoryTheory
66 & WegenerExploratory Factor Analysis (Understanding Statistics)BooksBeginner-AdvancedAccessible but comprehensive resource for how to do EFAStatistics; factor analysisstatistical inference
67 et al.,Dyadic Data AnalysisBooksIntermediate-AdvancedGo-To text for dyadic data analysisStatistics; dyadic datastatistical inference
68 to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based ApproachBooksBeginner-AdvancedAccessible text for fitting different regression models (simple, moderated, mediated, conditional process)Statistics; regression; interactions; mediationstatistical inference
69 Structural Equation ModelingBooksIntermediate-AdvancedGo-To resource for longitudinal SEMStatistics; latent variables; longitudinalstatistical inference
70 Variable Modeling Using R: A Step-by-Step GuideBooksIntermediate-AdvancedIntroductory SEM text (for use with R)Statistics; R; latent variablesstatistical inference
71 et al.,Introduction to Meta-AnalysisBooksIntermediate-AdvancedIntroductory meta-analysis textStatistics; meta-analysis
72, F. Graphical causal modelschapterintermediatevery clear introDAG, causal inference2015
73 MunroeSignificantComicBeginner
74 Syllabi for Open and Reproducible MethodsCourse Syllabigradosf project of methods course syllabi
75 MagnussonDistribution of p-values when comparing two groupsDemoBeginner
76 Your Way To Scientific GloryDemoBeginner
77 GraheCREP projectOSF projectbeginnerundergrad curriculum templates for teaching RR methods
78 Statistics AssociationAmerican Statistical Association Releases Statement On Statistical Significance And P-Valuespaperintermediatep-values2016
79, C. O., Morris, P. E., & Richler, J. Effect Size Estimates: Current Use, Calculations, and Interpretationpaperintermediateeffect size2012
80 et al., The poor availability of psychological research data for reanalysis.PaperIntermediateOpen-data; meta-science
81 et al.,The rules of the game called psychological sciencePaperIntermediateScientific norms; NHST
82 et al., Willingness to share research data is related to the strength of the evidence and the quality of reporting of statistical resultsPaperIntermediateOpen-data; misreporting; meta-science
83 & WichertsThe (mis) reporting of statistical results in psychology journalsPaperIntermediateMisreporting; meta-science
84 et al., The prevalence of statistical reporting errors in psychology (1985–2013)PaperIntermediateMisreporting; meta-science
85 et al.,Statistical reporting errors and collaboration on statistical analyses in psychological sciencePaperIntermediateMisreporting; meta-science; collaboration
86, JohnAnalytic Review as a Solution to the Misreporting of Statistical Results in Psychological SciencePaperBeginner-IntermediateMisreporting; meta-science
87, JohnExploring Small, Confirming Big: An Alternative System to The New Statistics for Advancing Cumulative and Replicable Psychological ResearchPaperBeginner-AdvancedMeta-science; systems for research; the new statistics
88, J. P. A. (2005). Why most published research findings are false. PloS MEDICINE, 2, 696-701.Papercompute probability of true finding given p < .05 using Bayesian argumentthe problem
IoannidisIoannidis, J. P. A. (2012). Why science is not necessarily self-correcting. Perspectives on Psychological Science, 7, 645-654.Paperthe problem
Begley & EllisBegley, C. G. & Ellis, L. M. (2012). Raise standards for preclinical cancer research. Nature, 483, 531-533.Paper11 / 59 studies had reproducible resultsreplication, biology, cancerthe problem
Simmons, Nelson, & SimonsohnSimmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science, 22(11), 1359-1366.PaperDescribes QRPs and has compelling simulationthe problem
Ferguson & Heene Ferguson, C. J. & Heene, M. (2012). A vast graveyard of undead theories: Publication bias and psychological science’s aversion to the null. Perspectives on Psychological Science, 7(6), 555-561.Paper
Makel, Plucker, & HegartyMakel, M. C., Plucker, J. A., & Hegarty, B. (2012). Replications in psychology research: How often do they really occur? Perspectives on Psychological Science, 7(6), 537-542.Paper
MakelMakel, M. C. (2014). The empirical march of science: Making science better at self-correction. Psychology of Aesthetics, Creativity, and the Arts.Paper
McBee & Matthews: McBee, M. T. & Matthews, M. S. (2014). Change starts with journal editors: In response to Makel (2014). Psychology of Aesthetics, Creativity, and the Arts, Vol 8(1), Feb 2014, 8-10.Paper
Simmons et al. SPS dialogue - A 21 word solutionPaper
Makel & Plucker - Facts are more important than noveltyPaper
Nosek, Spies, & MotylNosek, B. A., Spies, J. R., & Motyl, M. (2012). Scientific Utopia II. Restructuring Incentives and Practices to Promote Truth Over Publishability. Perspectives on Psychological Science, 7(6), 615-631.Paper
McBee & MatthewsWelcoming quality in non significance and replication work, but moving beyond the p value: announcing new editorial policies for quantitative research in JoAAPaper
Pashler & Wagenmakers Intro to the special issuePaper