- See Also
-
Gwern
- “Creatine Cognition Meta-Analysis”, Gwern 2013
- “The Replication Crisis: Flaws in Mainstream Science”, Gwern 2010
- “Lithium in Ground-Water and Well-Being”, Gwern 2010
- “Catnip Immunity and Alternatives”, Gwern 2015
- “Dual n-Back Meta-Analysis”, Gwern 2012
- “Iodine and Adult IQ Meta-Analysis”, Gwern 2012
- “Conscientiousness & Online Education”, Gwern 2012
-
Links
- “Reproducible Variability: Assessing Investigator Discordance across 9 Research Teams Attempting to Reproduce the Same Observational Study”, Ostropolets et al 2023
- “A Spotlight on Bias in the Growth Mindset Intervention Literature: A Reply to Commentaries That Contextualize the Discussion (Oyserman 2023; Yan & Schuetze 2023) and Illustrate the Conclusion (Tipton Et Al 2023)”, Macnamara & Burgoyne 2023
- “With Great Power Comes Great Responsibility: Common Errors in Meta-Analyses and Meta-Regressions in Strength & Conditioning Research”, Kadlec et al 2022
- “Are Most Published Criminological Research Findings Wrong? Taking Stock of Criminological Research Using a Bayesian Simulation Approach”, Niemeyer et al 2022
- “Do Meta-Analyses Oversell the Longer-Term Effects of Programs? (Part 1): Detecting Follow-Up Selection Bias in Studies of Postsecondary Education Programs”, Bailey & Weiss 2022
- “Revisiting Meta-Analytic Estimates of Validity in Personnel Selection: Addressing Systematic Overcorrection for Restriction of Range”, Sackett et al 2021
- “No Strong Evidence of Stereotype Threat in Females: A Reassessment of the Meta-Analysis”, Warne 2021
- “No Need to Choose: Robust Bayesian Meta-Analysis With Competing Publication Bias Adjustment Methods”, Bartoš et al 2021
- “The Statistical Properties of RCTs and a Proposal for Shrinkage”, Zwet et al 2020
- “Specification Curve Analysis”, Simonsohn et al 2020
- “Estimating Population Mean Power Under Conditions of Heterogeneity and Selection for Significance”, Brunner & Schimmack 2020
- “Comparing Meta-Analyses and Preregistered Multiple-Laboratory Replication Projects”, Kvarven et al 2019
- “Statistical Methods for Replicability Assessment”, Hung & Fithian 2019
- “What Can We Learn from Many Labs Replications? 3. Can Replication Studies Detect Fraud?”, Stroebe 2019
- “Estimation of Clinical Trial Success Rates and Related Parameters”, Wong et al 2019
- “Improving Active Learning in Systematic Reviews”, Singh et al 2018
- “The Heterogeneity Problem in Meta-Analytic Structural Equation Modeling (MASEM) Revisited: A Reply to Cheung”, Yu et al 2018
- “Evaluation of Evidence of Statistical Support and Corroboration of Subgroup Claims in Randomized Clinical Trials”, Association 2017
- “Performance of Informative Priors Skeptical of Large Treatment Effects in Clinical Trials: A Simulation Study”, Pedroza et al 2015
- “Assessment of Vibration of Effects due to Model Specification Can Demonstrate the Instability of Observational Associations”, Patel et al 2015
- “Predictive Distributions for Between-Study Heterogeneity and Simple Methods for Their Application in Bayesian Meta-Analysis”, Turner et al 2014
- “Meta-Analysis Using Effect Size Distributions of Only Statistically-Significant Studies”, Assen et al 2014
- “Association Between Analytic Strategy and Estimates of Treatment Outcomes in Meta-Analyses”, Dechartres et al 2014
- “p-Curve: A Key to the File-Drawer”, Simonsohn et al 2014
- “When Mice Mislead: Tackling a Long-Standing Disconnect between Animal and Human Studies, Some Charge That Animal Researchers Need Stricter Safeguards and Better Statistics to Ensure Their Science Is Solid”, Couzin-Frankel 2013
- “PET-PEESE: Meta-Regression Approximations to Reduce Publication Selection Bias”, Stanley & Doucouliagos 2013
- “Methods for Second Order Meta-Analysis and Illustrative Applications”, Schmidt & Oh 2013
- “The Ironic Effect of Significant Results on the Credibility of Multiple-Study Articles”, Schimmack 2012
- “Statistically-Significant Meta-Analyses of Clinical Trials Have Modest Credibility and Inflated Effects”, Pereira & Ioannidis 2011
- “The Truth Wears Off: Is There Something Wrong With the Scientific Method?”, Lehrer 2010
- “CONSORT 2010 Statement: Updated Guidelines for Reporting Parallel Group Randomized Trials Free”, Schulz 2010
- “CONSORT 2010 Explanation and Elaboration: Updated Guidelines for Reporting Parallel Group Randomized Trials”, Moher 2010
- “CONSORT 2010 Statement: Updated Guidelines for Reporting Parallel Group Randomized Trials”, Schulz et al 2010
- “Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement”, Moher et al 2009
- “Overstating the Evidence: Double Counting in Meta-Analysis and Related Problems”, Senn 2009
- “Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration”, Vandenbroucke et al 2007
- “An Exploratory Test for an Excess of Statistically-Significant Findings”, Ioannidis & Trikalinos 2007
- “Methods of Meta-Analysis: Correcting Error and Bias in Research Findings”, Hunter & Schmidt 2004
- “Improving the Reporting Quality of Nonrandomized Evaluations of Behavioral and Public Health Interventions: The TREND Statement”, Jarlais 2004
- “Measuring Inconsistency in Meta-Analyses”, Higgins 2003
- “Personal Reflections on Lessons Learned from Randomized Trials Involving Newborn Infants, 1951–1967”, Silverman 2003
- “Psychological Testing and Psychological Assessment: A Review of Evidence and Issues”, Meyer et al 2001
- “Trim and Fill: A Simple FunnelPlotBased Method of Testing and Adjusting for Publication Bias in MetaAnalysis”
- “Bias in Meta-Analysis Detected by a Simple, Graphical Test”, Egger et al 1997
- “The Effects of Corticosteroid Administration Before Preterm Delivery: an Overview of the Evidence from Controlled Trials”
- “The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration”, Liberati et al 2024
- “16.5.4 How to Include Multiple Groups from One Study”
- Sort By Magic
- Miscellaneous
- Bibliography
See Also
Gwern
“Creatine Cognition Meta-Analysis”, Gwern 2013
“The Replication Crisis: Flaws in Mainstream Science”, Gwern 2010
“Lithium in Ground-Water and Well-Being”, Gwern 2010
“Catnip Immunity and Alternatives”, Gwern 2015
“Dual n-Back Meta-Analysis”, Gwern 2012
“Iodine and Adult IQ Meta-Analysis”, Gwern 2012
“Conscientiousness & Online Education”, Gwern 2012
Links
“Reproducible Variability: Assessing Investigator Discordance across 9 Research Teams Attempting to Reproduce the Same Observational Study”, Ostropolets et al 2023
“A Spotlight on Bias in the Growth Mindset Intervention Literature: A Reply to Commentaries That Contextualize the Discussion (Oyserman 2023; Yan & Schuetze 2023) and Illustrate the Conclusion (Tipton Et Al 2023)”, Macnamara & Burgoyne 2023
“With Great Power Comes Great Responsibility: Common Errors in Meta-Analyses and Meta-Regressions in Strength & Conditioning Research”, Kadlec et al 2022
“Are Most Published Criminological Research Findings Wrong? Taking Stock of Criminological Research Using a Bayesian Simulation Approach”, Niemeyer et al 2022
“Do Meta-Analyses Oversell the Longer-Term Effects of Programs? (Part 1): Detecting Follow-Up Selection Bias in Studies of Postsecondary Education Programs”, Bailey & Weiss 2022
“Revisiting Meta-Analytic Estimates of Validity in Personnel Selection: Addressing Systematic Overcorrection for Restriction of Range”, Sackett et al 2021
“No Strong Evidence of Stereotype Threat in Females: A Reassessment of the Meta-Analysis”, Warne 2021
No Strong Evidence of Stereotype Threat in Females: A Reassessment of the Meta-Analysis
“No Need to Choose: Robust Bayesian Meta-Analysis With Competing Publication Bias Adjustment Methods”, Bartoš et al 2021
No Need to Choose: Robust Bayesian Meta-Analysis with Competing Publication Bias Adjustment Methods
“The Statistical Properties of RCTs and a Proposal for Shrinkage”, Zwet et al 2020
The statistical properties of RCTs and a proposal for shrinkage
“Specification Curve Analysis”, Simonsohn et al 2020
“Estimating Population Mean Power Under Conditions of Heterogeneity and Selection for Significance”, Brunner & Schimmack 2020
Estimating Population Mean Power Under Conditions of Heterogeneity and Selection for Significance
“Comparing Meta-Analyses and Preregistered Multiple-Laboratory Replication Projects”, Kvarven et al 2019
Comparing meta-analyses and preregistered multiple-laboratory replication projects
“Statistical Methods for Replicability Assessment”, Hung & Fithian 2019
“What Can We Learn from Many Labs Replications? 3. Can Replication Studies Detect Fraud?”, Stroebe 2019
What Can We Learn from Many Labs Replications? 3. Can replication studies detect fraud?
“Estimation of Clinical Trial Success Rates and Related Parameters”, Wong et al 2019
Estimation of clinical trial success rates and related parameters
“Improving Active Learning in Systematic Reviews”, Singh et al 2018
“The Heterogeneity Problem in Meta-Analytic Structural Equation Modeling (MASEM) Revisited: A Reply to Cheung”, Yu et al 2018
“Evaluation of Evidence of Statistical Support and Corroboration of Subgroup Claims in Randomized Clinical Trials”, Association 2017
“Performance of Informative Priors Skeptical of Large Treatment Effects in Clinical Trials: A Simulation Study”, Pedroza et al 2015
“Assessment of Vibration of Effects due to Model Specification Can Demonstrate the Instability of Observational Associations”, Patel et al 2015
“Predictive Distributions for Between-Study Heterogeneity and Simple Methods for Their Application in Bayesian Meta-Analysis”, Turner et al 2014
“Meta-Analysis Using Effect Size Distributions of Only Statistically-Significant Studies”, Assen et al 2014
Meta-analysis using effect size distributions of only statistically-significant studies
“Association Between Analytic Strategy and Estimates of Treatment Outcomes in Meta-Analyses”, Dechartres et al 2014
Association Between Analytic Strategy and Estimates of Treatment Outcomes in Meta-analyses
“p-Curve: A Key to the File-Drawer”, Simonsohn et al 2014
“When Mice Mislead: Tackling a Long-Standing Disconnect between Animal and Human Studies, Some Charge That Animal Researchers Need Stricter Safeguards and Better Statistics to Ensure Their Science Is Solid”, Couzin-Frankel 2013
“PET-PEESE: Meta-Regression Approximations to Reduce Publication Selection Bias”, Stanley & Doucouliagos 2013
PET-PEESE: Meta-regression approximations to reduce publication selection bias
“Methods for Second Order Meta-Analysis and Illustrative Applications”, Schmidt & Oh 2013
Methods for second order meta-analysis and illustrative applications
“The Ironic Effect of Significant Results on the Credibility of Multiple-Study Articles”, Schimmack 2012
The Ironic Effect of Significant Results on the Credibility of Multiple-Study Articles
“Statistically-Significant Meta-Analyses of Clinical Trials Have Modest Credibility and Inflated Effects”, Pereira & Ioannidis 2011
“The Truth Wears Off: Is There Something Wrong With the Scientific Method?”, Lehrer 2010
The Truth Wears Off: Is there something wrong with the scientific method?
“CONSORT 2010 Statement: Updated Guidelines for Reporting Parallel Group Randomized Trials Free”, Schulz 2010
CONSORT 2010 Statement: Updated Guidelines for Reporting Parallel Group Randomized Trials Free
“CONSORT 2010 Explanation and Elaboration: Updated Guidelines for Reporting Parallel Group Randomized Trials”, Moher 2010
“CONSORT 2010 Statement: Updated Guidelines for Reporting Parallel Group Randomized Trials”, Schulz et al 2010
CONSORT 2010 Statement: updated guidelines for reporting parallel group randomized trials
“Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement”, Moher et al 2009
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
“Overstating the Evidence: Double Counting in Meta-Analysis and Related Problems”, Senn 2009
Overstating the evidence: double counting in meta-analysis and related problems
“Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration”, Vandenbroucke et al 2007
“An Exploratory Test for an Excess of Statistically-Significant Findings”, Ioannidis & Trikalinos 2007
An exploratory test for an excess of statistically-significant findings
“Methods of Meta-Analysis: Correcting Error and Bias in Research Findings”, Hunter & Schmidt 2004
Methods of Meta-Analysis: Correcting Error and Bias in Research Findings
“Improving the Reporting Quality of Nonrandomized Evaluations of Behavioral and Public Health Interventions: The TREND Statement”, Jarlais 2004
“Measuring Inconsistency in Meta-Analyses”, Higgins 2003
“Personal Reflections on Lessons Learned from Randomized Trials Involving Newborn Infants, 1951–1967”, Silverman 2003
Personal reflections on lessons learned from randomized trials involving newborn infants, 1951–1967
“Psychological Testing and Psychological Assessment: A Review of Evidence and Issues”, Meyer et al 2001
Psychological testing and psychological assessment: A review of evidence and issues
“Trim and Fill: A Simple FunnelPlotBased Method of Testing and Adjusting for Publication Bias in MetaAnalysis”
“Bias in Meta-Analysis Detected by a Simple, Graphical Test”, Egger et al 1997
“The Effects of Corticosteroid Administration Before Preterm Delivery: an Overview of the Evidence from Controlled Trials”
“The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration”, Liberati et al 2024
“16.5.4 How to Include Multiple Groups from One Study”
Sort By Magic
Annotations sorted by machine learning into inferred 'tags'. This provides an alternative way to browse: instead of by date order, one can browse in topic order. The 'sorted' list has been automatically clustered into multiple sections & auto-labeled for easier browsing.
Beginning with the newest annotation, it uses the embedding of each annotation to attempt to create a list of nearest-neighbor annotations, creating a progression of topics. For more details, see the link.
statistical-robustness
effect-sizes
replication
Miscellaneous
Bibliography
-
https://osf.io/mhv8f/: “Are Most Published Criminological Research Findings Wrong? Taking Stock of Criminological Research Using a Bayesian Simulation Approach”, -
https://www.mdrc.org/work/publications/do-meta-analyses-oversell-longer-term-effects-programs-part-1: “Do Meta-Analyses Oversell the Longer-Term Effects of Programs? (Part 1): Detecting Follow-Up Selection Bias in Studies of Postsecondary Education Programs”, -
https://osf.io/preprints/psyarxiv/kvsp7/: “No Need to Choose: Robust Bayesian Meta-Analysis With Competing Publication Bias Adjustment Methods”, -
https://arxiv.org/abs/2011.15004: “The Statistical Properties of RCTs and a Proposal for Shrinkage”, -
2020-simonsohn.pdf: “Specification Curve Analysis”, -
2020-brunner.pdf: “Estimating Population Mean Power Under Conditions of Heterogeneity and Selection for Significance”, -
https://www.tandfonline.com/doi/full/10.1080/01973533.2019.1577736#section-heading-2: “What Can We Learn from Many Labs Replications? 3. Can Replication Studies Detect Fraud?”, -
https://onlinelibrary.wiley.com/doi/full/10.1002/sim.6381: “Predictive Distributions for Between-Study Heterogeneity and Simple Methods for Their Application in Bayesian Meta-Analysis”, -
2014-vanassen.pdf: “Meta-Analysis Using Effect Size Distributions of Only Statistically-Significant Studies”, -
https://jamanetwork.com/journals/jama/article-abstract/1895246: “Association Between Analytic Strategy and Estimates of Treatment Outcomes in Meta-Analyses”, -
2014-simonsohn.pdf: “p-Curve: A Key to the File-Drawer”, -
2013-stanley.pdf: “PET-PEESE: Meta-Regression Approximations to Reduce Publication Selection Bias”, -
https://www.newyorker.com/magazine/2010/12/13/the-truth-wears-off: “The Truth Wears Off: Is There Something Wrong With the Scientific Method?”,