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 BohannonI Fooled Millions Into Thinking Chocolate Helps Weight Loss. Here's How.ArticleBeginner2015
3 & McCulloughArticlesintermediatePETPEESE application, ego depletion
4 O'HaganArticlesbeginnerBayes Factors
5, Bayes
6 EtzBlogintermediatelikelihood
7 EtzBlogintermediateBayes Factorsstatistical inference
8 Gelmanblogvariousstatistical analysis, research methods, repoducibility
9, AndrewStatistical Modeling, Causal Inference, and Social ScienceBlogIntermediatestatistical inference
10 MoreyBlogintermediateR package tutorial
11 software
12 LakensData peeking without p-hackingBlogintermediatesequential testing
13 LakensWhat is a p-value?Blogbeginnerp-values
14 LakensAlways use Welch t-testBlogintermediatet-test
15 SimonsohnBlogadvancedBayes Factors
16 applicationassessing evidence
17 evidence
18 BishopThe Amazing Significo: why researchers need to understand pokerBlogBeginnerp-hacking
19 HughesBlogp-curve, R indexassessing evidence
20 RouderBlogadvancedresponse to Uri SimonsohnBayes Factors
21 Watch: Michael LaCour archivesBlogIntermediateCollection of articles about the faking of data, discovery through replication attempt
22 DotschDegrees of Freedom Tutorialblogbeginnerexplanation about degrees of freedom for ANOVA2015statistics
23 MagnussonCalculating the overlap of two normal distributions using monte carlo intergrationblog
24 MagnussonVisualizing a one-way ANOVAblogvisualization
25 MagnussonInterpreting confidence intervalsblogvisualization
x`Kristoffer MagnussonInterpreting cohen's d effect sizeblogvisualization
27 MagnussonInterpreting correlationsblogvisualization
28 MagnussonUnderstanding Statistical Power and Significance Testing: an interactive visualizationblogbeginngervisualization
29 MagnussonDistribution of p-values when comparing two groupsblogvisualization
30 MagnussonEffect of sample size on teh accuracy of Cohen's d estimatesblog
31 MagnussonExpected overestiationg of Cohen's d under publication biasblogvisualization
32 MagnussonHow to tell when error bars correspond to a significant p-valueblog
33 MagnussonBayesian inferenceblogvisualization
34 MagnussonThe t-distritbution and its normal approximationblogvisualization
35 MagnussonUsing R and lme/lmer to fit different two- and three- level longitudinal modelsblog
36 MagnussonShort R script to plot effect sizes (Cohen's d) and share overlapping areblog
37 MagnussonP-curve visualization updated with log x-axisblogvisualization
38 VazireWhy p=.048 should be rareBlogp-values
39 InzlichtA tale of two papersBlogfile drawer
40 GervaisBlogp-curveassessing evidence
41 GervaisBlogClass Projectp-curveassessing evidence
42, BenBad Science log, post-Guardianblogintermediate2015
43 FunderBlogbeginnerBayes statistical inference
44 inference
45 SrivastavaThe Hardest ScienceBlogvarious
46 psyborgs lab, PettitReplication in Psychology: a historical perspectiveblogbeginningreproducibility2015
47 SchimmackBlogTIVA
48 SchimmackBlogintermediatecriticismBayes Factors
49, JohnTutorial/R code for creating plots for 2-way interactionsBlogIntermediateR; data-visualization; interactions
50, JohnTutorial/R code for creating funnel/forest plotsBlogIntermediateR; data-visualization; meta-analysis
51, JohnTutorial/R code for creating scree/parallel analysis plotsBlogIntermediateR; data-visualization; factor analysis
52, BenBad Science blog on the Guardian webpagesblogintermediate2011
53 GrantBlog advancedBayes, frequentiststatistical inference
54 EtzBlog (I think it is now also a paper?)Bayes, replication projectstatistical inference
55 Incidental EconomistPre-registration of clinical trials is associated with fewer positive findingsBlog postBeginner
56, G. (2012). Understanding the new statistics: Effect sizes, confidence intervals, and meta-analysis. New York: Routledge.Book
57 StapelFaking Science: A True Story of Academic FraudBookintro, intermediate2014
58, 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
59, R. (1997). Statistical evidence: A likelihood paradigm. CRC Press.bookadvancedLikelihood1997statistical inference
Plucker & MakelDoing Good Social Science: Trust, Accuracy, Transparencybookbeginneredited volume collecting perspectivesin press
61 et al.,Dyadic Data AnalysisBooksIntermediate-AdvancedGo-To text for dyadic data analysisStatistics; dyadic datastatistical inference
62 & WegenerExploratory Factor Analysis (Understanding Statistics)BooksBeginner-AdvancedAccessible but comprehensive resource for how to do EFAStatistics; factor analysisstatistical inference
63 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
64 et al.,Introduction to Meta-AnalysisBooksIntermediate-AdvancedIntroductory meta-analysis textStatistics; meta-analysis
65 Structural Equation ModelingBooksIntermediate-AdvancedGo-To resource for longitudinal SEMStatistics; latent variables; longitudinalstatistical inference
66 & BoskerMultilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling 1st EditionBooksIntermediate-AdvancedMultilevel modeling resourceStatistics; MLM; HLMstatistical inference
67 et al.,Applied Multiple Regression/Correlation Analysis for the Behavioral SciencesBooksIntermediate-AdvancedComprehensive resource for regression modelsStatistics; regressionstatistical inference
68 Variable Modeling Using R: A Step-by-Step GuideBooksIntermediate-AdvancedIntroductory SEM text (for use with R)Statistics; R; latent variablesstatistical inference
69 & JacobyTheory Construction and Model-Building Skills: A Practical Guide for Social Scientists BooksBeginner-AdvancedIntroduction to how to generate/conceptualize theoryTheory
70 & FrenchLatent Variable Modeling with RBooksIntermediate-AdvancedBook for EFA/CFA/IRT/LCA in RR; latent variable; statisticsstatistical inference
71, F. Graphical causal modelschapterintermediatevery clear introDAG, causal inference2015
72 MunroeSignificantComicBeginner
73 Syllabi for Open and Reproducible MethodsCourse Syllabigradosf project of methods course syllabi
74 TIERCuricculumbeginnerundergrad curriculum templates for teaching RR methods
75 Your Way To Scientific GloryDemoBeginner
76 MagnussonDistribution of p-values when comparing two groupsDemoBeginner
77 GraheCREP projectOSF projectbeginnerundergrad curriculum templates for teaching RR methods
78 GallistelBayes for Beginners: Probability and Liklihoodpaperbeginner
DOI: 10.1037//OOO3-O66X.56.2.12Meyer et alPsychological Testing and Psychological AssessmentA Review of Evidence and Issuespaperintermediatereview2001
80 RosenthalRosnow, R.L., & Rosenthal, R. (1989). Statistical procedures and the justification of knowledge in psychological science. American Psychologist, 44, 1276-1284.paperintermediateStatistical Inference; NHST; Power1989statistical inference
81, R. S. (2000). Null hypothesis significance testing: a review of an old and continuing controversy. Psychological methods, 5(2), 241-301.paperbeginnerNHST; Frequentist Statistics; p-value2000NHST
82, D. J. (2011). Feeling the Future: Experimental Evidence for Anomalous Retroactive Influences on Cognition and Affect. Journal of Personality and Social Psychology, 100(3), 407-425.Papercanary in the coal mine
DOI: 10.1097/EDE.0b013e31818131e7IoannidisWhy Most Discovered True Associations Are Inflatedpaperintermediateidentifying problems
DOI: 10.1177/0956797611417632Simmons, Nelson, SimonsohnFalse-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significantpaperbeginningidentifying problems2011
DOI: 10.1177/0956797611430953John, Loewenstein, PrelecMeasuring the Prevalence of Questionable Research Practices With Incentives for Truth Tellingpaperintermediateidentifying problems2012
DOI: 10.1177/1740774507079441Ioannidis, TrikalinosAn exploratory test for an excess of significant findingspaperadvancedidentifying problems2007
DOI: 10.1177/1948550615612150Fiedler & SchwarzQuestionable Research Practices Revisitedpaperbeginningquestionable research practicies2015
DOI: 10.1177/2378023115625071PetersonThe Baby Factory: Difficult Research Objects, Disciplinary Standards, and the Production of Statistical Significancepaperbeginningquestionable research practicies2016
doi:10.1017/XPS.2015.19Mullinix, Leeper, Druckman FreeseThe Generalizability of Survey Experiments∗paperintermediatereproducibility2015
doi:10.1038/nrn3475ButtonPower failure: why small sample size undermines the reliability of neurosciencepaperintermediatepower2013
DOI:10.1136/bmj.318.7175.23Rooyen, Godlec, Evans, Black, Smiththe effect of open peer review on quality of reviews and on reviewers' recommendations: A randomized trialspaperintermediateopen peer review1999
92 Hilgard StaaksLakens, D., Hilgard, J., & Staaks, J. (2016). On the reproducibility of meta-analyses: six practical recommendations. BMC Psychology, 4, 24.; Publication Bias2016meta-analysis
93, J. (1992). Statistical power analysis. Current Directions in Psychological Science, 1(3), 98–101.paperbeginnerPower; Power Analysis1992Power
94, C. O., Morris, P. E., & Richler, J. Effect Size Estimates: Current Use, Calculations, and Interpretationpaperintermediateeffect size2012
95 TrikalinosIoannidis, J.P.A. & Trikalinos, T.A. (2007). An exploratory test for an excess of significant findings. Clinical Trials, 4, 245-253.paperintermediatePublication Bias2007Meta-Analysis
96, P. E. (1978). Theoretical risks and tabular asterisks: Sir Karl, Sir Ronald, and the slow progress of soft psychology. Journal of Consulting and Clinical Psychology, 46, 806-834.paperbeginnerNHST1978the problem
97 GigerenzerSedlmeier, P. & Gigerenzer, G. (1989). Do studies of statistical power have an effect on the power of studies? Psychological Bulletin, 105, 309-316.paperbeginnerPower; Publication Bias1989the problem
98 PetersLeBel, E.P., & Peters, K.R. (2011). Fearing the future of empirical psychology: Bem’s (2011) evidence of psi as a case study in deficiencies in modal research practice. Review of General Psychology, 15, 371-379.paperbeginnerP-hacking; Replication; Psi; NHST2011the problem
99 - ‘Fanelli, D. (2010) “Positive” Results Increase Down the Hierarchy of the Sciences. PLoS ONE 5(4): e10068. doi:10.1371/journal.pone.0010068Paper
100, Baaker, & MolenarWicherts, J. M., Baaker, M., & Molenar, D. (2011). Willingness to Share Research Data Is Related to the Strength of the Evidence and the Quality of Reporting of Statistical Results. PLoS ONE 6(11): e26828. doi:10.1371/journal.pone.0026828Paper