‘power analysis’ directory
- See Also
- Gwern
- “Anti-Spaced Repetition for Serendipity ”, Gwern 2017
- “Oh Deer: Could Deer Evolve to Avoid Car Accidents? ”, Gwern 2018
- “DMT Factoring Experiment Cost Estimate ”, Gwern 2015
- “Can You Unsort Lists for Diversity? ”, Gwern 2019
- “Acne: a Good Quantified Self Topic ”, Gwern 2019
- “Statistical Notes ”, Gwern 2014
- “A/B Testing Long-Form Readability on Gwern.net ”, Gwern 2012
- “Banner Ads Considered Harmful ”, Gwern 2017
- “Magnesium Self-Experiments ”, Gwern 2013
- “Embryo Selection For Intelligence ”, Gwern 2016
- “Redshift Sleep Experiment ”, Gwern 2012
- “The Power of Twins: The Scottish Milk Experiment ”, Gwern 2016
- “Genius Revisited Revisited ”, Gwern 2016
- “LSD Microdosing RCT ”, Gwern 2012
- “Embryo Editing for Intelligence ”, Gwern 2016
- “History of Iterated Embryo Selection ”, Gwern 2019
- “Nootropics ”, Gwern 2010
- “Life Extension Cost-Benefits ”, Gwern 2015
- “The Morality of Sperm Donation ”, Gwern 2012
- “Zeo Sleep Self-Experiments ”, Gwern 2010
- “Lunar Circadian Rhythms ”, Gwern 2013
- “Caffeine Wakeup Experiment ”, Gwern 2013
- “Candy Japan’s New Box A/B Test ”, Gwern 2016
- “Diet Variance: Soylent Study ”, Gwern 2013
- “Weather and My Productivity ”, Gwern 2013
- Links
- “Epistasis and Deep Learning in Quantitative Genetics: We Explore When Deep Learning (DL) Outperforms Linear Models in Predicting Complex Phenotypes. We Show That DL Requires at Least 20% As Many Samples As Possible Epistatic Interactions, and Benefits from Marker Feature Selection and Multi-Task Learning on Correlated Phenotypes ”, Bell et al 2025
- “The Distribution of Highly Deleterious Variants across Human Ancestry Groups ”, Stolyarova et al 2025
- “Revisiting Randomization With the Cube Method ”, Davezies et al 2024
- “Impossible Hypotheses and Effect-Size Limits ”, Tilburg & Tilburg 2023
- “How Many Participants Do I Need to Test an Interaction? Conducting an Appropriate Power Analysis and Achieving Sufficient Power to Detect an Interaction ”, Sommet et al 2023
- “Replicable Brain-Phenotype Associations Require Large-Scale Neuroimaging Data ”, Liu et al 2023b
- “Identification and Analysis of Individuals Who Deviate from Their Genetically-Predicted Phenotype ”, Hawkes et al 2023
- “The Cost of Imbalance in Clinical Trials ”, Chassang & Feng 2022
- “Are Most Published Criminological Research Findings Wrong? Taking Stock of Criminological Research Using a Bayesian Simulation Approach ”, Niemeyer et al 2022
- “The Phenotype-Genotype Reference Map: Improving Biobank Data Science through Replication. ”, Bastarache et al 2022
- “Optimality of Matched-Pair Designs in Randomized Controlled Trials ”, Bai 2022
- “Statistical-Significance Tests for R2 of Out-Of-Sample Prediction Using Polygenic Scores ”, Momin et al 2022
- “Reproducible Brain-Wide Association Studies Require Thousands of Individuals ”, Marek et al 2022
- “Policy Learning and Evaluation With Randomized Quasi-Monte Carlo ”, Arnold et al 2022
- “Which Findings Should Be Published? ”, Frankel & Kasy 2022
- “The Significance Filter, the Winner’s Curse and the Need to Shrink ”, Zwet & Cator 2020
- “Is Early Blindness Protective of Psychosis or Are We Turning a Blind Eye to the Lack of Statistical Power? ”, Jefsen et al 2020
- “Is the FDA Too Conservative or Too Aggressive?: A Bayesian Decision Analysis of Clinical Trial Design ”, Isakov et al 2019
- “Exome Sequencing of Finnish Isolates Enhances Rare-Variant Association Power ”, Locke et al 2019
- “Statistical Power of Clinical Trials Has Increased Whilst Effect Size Remained Stable: an Empirical Analysis of 137,032 Clinical Trials between 1975–2017 ”, Lamberink et al 2017
- “The Power of Bias in Economics Research ”, Ioannidis et al 2017
- “What Exactly Is ‘N’ in Cell Culture and Animal Experiments? ”, Lazic et al 2017
- “Empirical Assessment of Published Effect Sizes and Power in the Recent Cognitive Neuroscience and Psychology Literature ”, Szucs & Ioannidis 2017
- “Refiltering Hypothesis Tests to Control Sign Error ”, Owen 2016
- “Don’t Fight the Power (Analysis) ”, Westfall 2015
- “An Implantable Microdevice to Perform High-Throughput in Vivo Drug Sensitivity Testing in Tumors ”, Jonas et al 2015
- “The Power of Optimization Over Randomization in Designing Experiments Involving Small Samples ”, Bertsimas et al 2015
- “Small Telescopes: Detectability and the Evaluation of Replication Results ”, Simonsohn 2015
- “On the Genetic Architecture of Intelligence and Other Quantitative Traits ”, Hsu 2014
- “Trap of Trends to Statistical-Significance: Likelihood of Near-Statistically-Significant p-Values Becoming More Statistically-Significant With Extra Data ”, Wood et al 2014
- “Replicability and Robustness of Genome-Wide-Association Studies for Behavioral Traits ”, Rietveld et al 2014
- “Impact of Measurement Error on Testing Genetic Association With Quantitative Traits ”, Liao et al 2013
- “On the Near Impossibility of Measuring the Returns to Advertising ”, Lewis & Rao 2013
- “Improving the Sensitivity of Online Controlled Experiments by Utilizing Pre-Experiment Data ”, Deng et al 2013
- “Rerandomization to Improve Covariate Balance in Experiments ”, Morgan & Rubin 2012
- “Scale Coarseness As a Methodological Artifact: Correcting Correlation Coefficients Attenuated From Using Coarse Scales ”, Aguinis et al 2008
- “Should We Take Measurements at an Intermediate Design Point? ”, Gelman 2000
- “Most Published Research Findings Are False—But a Little Replication Goes a Long Way ”, Moonesinghe et al 2026
- “Counterbalancing in the Design of Experiments ”
- “Computational Analysis of Lifespan Experiment Reproducibility ”
- “Analyzing DeepMind’s Probabilistic Methods for Evaluating Agent Capabilities ”
- “From Classical Methods to Generative Models: Tackling the Unreliability of Neuroscientific Measures in Mental Health Research ”
- “Optimal Design in Psychological Research ”
- Wikipedia (6)
- Miscellaneous
- Bibliography
See Also
Gwern
“Anti-Spaced Repetition for Serendipity ”, Gwern 2017
“Oh Deer: Could Deer Evolve to Avoid Car Accidents? ”, Gwern 2018
“DMT Factoring Experiment Cost Estimate ”, Gwern 2015
“Can You Unsort Lists for Diversity? ”, Gwern 2019
“Acne: a Good Quantified Self Topic ”, Gwern 2019
“Statistical Notes ”, Gwern 2014
“A/B Testing Long-Form Readability on Gwern.net ”, Gwern 2012
“Magnesium Self-Experiments ”, Gwern 2013
“Embryo Selection For Intelligence ”, Gwern 2016
“Redshift Sleep Experiment ”, Gwern 2012
“The Power of Twins: The Scottish Milk Experiment ”, Gwern 2016
“Genius Revisited Revisited ”, Gwern 2016
“LSD Microdosing RCT ”, Gwern 2012
“Embryo Editing for Intelligence ”, Gwern 2016
“History of Iterated Embryo Selection ”, Gwern 2019
“Nootropics ”, Gwern 2010
“Life Extension Cost-Benefits ”, Gwern 2015
“The Morality of Sperm Donation ”, Gwern 2012
“Zeo Sleep Self-Experiments ”, Gwern 2010
“Lunar Circadian Rhythms ”, Gwern 2013
“Caffeine Wakeup Experiment ”, Gwern 2013
“Candy Japan’s New Box A/B Test ”, Gwern 2016
“Diet Variance: Soylent Study ”, Gwern 2013
“Weather and My Productivity ”, Gwern 2013
Links
“Epistasis and Deep Learning in Quantitative Genetics: We Explore When Deep Learning (DL) Outperforms Linear Models in Predicting Complex Phenotypes. We Show That DL Requires at Least 20% As Many Samples As Possible Epistatic Interactions, and Benefits from Marker Feature Selection and Multi-Task Learning on Correlated Phenotypes ”, Bell et al 2025
“The Distribution of Highly Deleterious Variants across Human Ancestry Groups ”, Stolyarova et al 2025
The distribution of highly deleterious variants across human ancestry groups
“Revisiting Randomization With the Cube Method ”, Davezies et al 2024
“Impossible Hypotheses and Effect-Size Limits ”, Tilburg & Tilburg 2023
“How Many Participants Do I Need to Test an Interaction? Conducting an Appropriate Power Analysis and Achieving Sufficient Power to Detect an Interaction ”, Sommet et al 2023
“Replicable Brain-Phenotype Associations Require Large-Scale Neuroimaging Data ”, Liu et al 2023b
Replicable brain-phenotype associations require large-scale neuroimaging data
“Identification and Analysis of Individuals Who Deviate from Their Genetically-Predicted Phenotype ”, Hawkes et al 2023
Identification and analysis of individuals who deviate from their genetically-predicted phenotype
“The Cost of Imbalance in Clinical Trials ”, Chassang & Feng 2022
“Are Most Published Criminological Research Findings Wrong? Taking Stock of Criminological Research Using a Bayesian Simulation Approach ”, Niemeyer et al 2022
“The Phenotype-Genotype Reference Map: Improving Biobank Data Science through Replication. ”, Bastarache et al 2022
The Phenotype-Genotype Reference Map: Improving biobank data science through replication.
“Optimality of Matched-Pair Designs in Randomized Controlled Trials ”, Bai 2022
Optimality of Matched-Pair Designs in Randomized Controlled Trials
“Statistical-Significance Tests for R2 of Out-Of-Sample Prediction Using Polygenic Scores ”, Momin et al 2022
Statistical-Significance tests for R2 of out-of-sample prediction using polygenic scores
“Reproducible Brain-Wide Association Studies Require Thousands of Individuals ”, Marek et al 2022
Reproducible brain-wide association studies require thousands of individuals
“Policy Learning and Evaluation With Randomized Quasi-Monte Carlo ”, Arnold et al 2022
Policy Learning and Evaluation with Randomized Quasi-Monte Carlo
“Which Findings Should Be Published? ”, Frankel & Kasy 2022
“The Significance Filter, the Winner’s Curse and the Need to Shrink ”, Zwet & Cator 2020
The Significance Filter, the Winner’s Curse and the Need to Shrink
“Is Early Blindness Protective of Psychosis or Are We Turning a Blind Eye to the Lack of Statistical Power? ”, Jefsen et al 2020
“Is the FDA Too Conservative or Too Aggressive?: A Bayesian Decision Analysis of Clinical Trial Design ”, Isakov et al 2019
“Exome Sequencing of Finnish Isolates Enhances Rare-Variant Association Power ”, Locke et al 2019
Exome sequencing of Finnish isolates enhances rare-variant association power :
“Statistical Power of Clinical Trials Has Increased Whilst Effect Size Remained Stable: an Empirical Analysis of 137,032 Clinical Trials between 1975–2017 ”, Lamberink et al 2017
“The Power of Bias in Economics Research ”, Ioannidis et al 2017
“What Exactly Is ‘N’ in Cell Culture and Animal Experiments? ”, Lazic et al 2017
“Empirical Assessment of Published Effect Sizes and Power in the Recent Cognitive Neuroscience and Psychology Literature ”, Szucs & Ioannidis 2017
“Refiltering Hypothesis Tests to Control Sign Error ”, Owen 2016
“Don’t Fight the Power (Analysis) ”, Westfall 2015
“An Implantable Microdevice to Perform High-Throughput in Vivo Drug Sensitivity Testing in Tumors ”, Jonas et al 2015
An implantable microdevice to perform high-throughput in vivo drug sensitivity testing in tumors
“The Power of Optimization Over Randomization in Designing Experiments Involving Small Samples ”, Bertsimas et al 2015
The Power of Optimization Over Randomization in Designing Experiments Involving Small Samples
“Small Telescopes: Detectability and the Evaluation of Replication Results ”, Simonsohn 2015
Small Telescopes: Detectability and the Evaluation of Replication Results
“On the Genetic Architecture of Intelligence and Other Quantitative Traits ”, Hsu 2014
On the genetic architecture of intelligence and other quantitative traits
“Trap of Trends to Statistical-Significance: Likelihood of Near-Statistically-Significant p-Values Becoming More Statistically-Significant With Extra Data ”, Wood et al 2014
“Replicability and Robustness of Genome-Wide-Association Studies for Behavioral Traits ”, Rietveld et al 2014
Replicability and robustness of genome-wide-association studies for behavioral traits
“Impact of Measurement Error on Testing Genetic Association With Quantitative Traits ”, Liao et al 2013
Impact of Measurement Error on Testing Genetic Association with Quantitative Traits
“On the Near Impossibility of Measuring the Returns to Advertising ”, Lewis & Rao 2013
On the Near Impossibility of Measuring the Returns to Advertising
“Improving the Sensitivity of Online Controlled Experiments by Utilizing Pre-Experiment Data ”, Deng et al 2013
Improving the sensitivity of online controlled experiments by utilizing pre-experiment data
“Rerandomization to Improve Covariate Balance in Experiments ”, Morgan & Rubin 2012
“Scale Coarseness As a Methodological Artifact: Correcting Correlation Coefficients Attenuated From Using Coarse Scales ”, Aguinis et al 2008
“Should We Take Measurements at an Intermediate Design Point? ”, Gelman 2000
Should we take measurements at an intermediate design point?
“Most Published Research Findings Are False—But a Little Replication Goes a Long Way ”, Moonesinghe et al 2026
Most Published Research Findings Are False—But a Little Replication Goes a Long Way
“Counterbalancing in the Design of Experiments ”
“Computational Analysis of Lifespan Experiment Reproducibility ”
Computational Analysis of Lifespan Experiment Reproducibility
“Analyzing DeepMind’s Probabilistic Methods for Evaluating Agent Capabilities ”
Analyzing DeepMind’s Probabilistic Methods for Evaluating Agent Capabilities
“From Classical Methods to Generative Models: Tackling the Unreliability of Neuroscientific Measures in Mental Health Research ”
“Optimal Design in Psychological Research ”
Wikipedia (6)
Miscellaneous
Bibliography
https://research.arcadiascience.com/pub/result-gp-deep-learning-scaling/release/1/: “Epistasis and Deep Learning in Quantitative Genetics: We Explore When Deep Learning (DL) Outperforms Linear Models in Predicting Complex Phenotypes. We Show That DL Requires at Least 20% As Many Samples As Possible Epistatic Interactions, and Benefits from Marker Feature Selection and Multi-Task Learning on Correlated Phenotypes ”,https://journals.sagepub.com/doi/full/10.1177/25152459231197605: “Impossible Hypotheses and Effect-Size Limits ”,https://journals.sagepub.com/doi/full/10.1177/25152459231178728: “How Many Participants Do I Need to Test an Interaction? Conducting an Appropriate Power Analysis and Achieving Sufficient Power to Detect an Interaction ”,2023-liu-2.pdf: “Replicable Brain-Phenotype Associations Require Large-Scale Neuroimaging Data ”,https://osf.io/mhv8f/: “Are Most Published Criminological Research Findings Wrong? Taking Stock of Criminological Research Using a Bayesian Simulation Approach ”,2022-marek.pdf: “Reproducible Brain-Wide Association Studies Require Thousands of Individuals ”,2017-ioannidis.pdf: “The Power of Bias in Economics Research ”,2015-bertsimas.pdf: “The Power of Optimization Over Randomization in Designing Experiments Involving Small Samples ”,2008-aguinis.pdf: “Scale Coarseness As a Methodological Artifact: Correcting Correlation Coefficients Attenuated From Using Coarse Scales ”,