The Curious Engineer

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Data Colada

datacolada.org

Thinking about evidence and vice versa

ScienceMath

’15’20’25
Posts
139 from 17 Sep 2013 to 19 Oct 2026
Posting
monthly (10 in the last year)
Kind
personal blog
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https://datacolada.org/feed

2026 8

  1. [140] De-Qualtricsification: ResearchBox Automatically Converts Inscrutable Qualtrics Files Into Simple PDFs
  2. [139] Artificial Deadlines (Part 2): Retrograding Ariely & Wertenbroch (2002)
  3. [138] Artificial Deadlines (Part 1): Evidence of Fraud in an Influential Study About Procrastination
  4. [137] OSF Will Stop Accepting Your Research Files, You Can Use ResearchBox Instead
  5. [136] Metadata Falsificada: The Cover-Up File in Gino v. Harvard
  6. [134] Figuring Out Figure 1
  7. [133] Heterofriendly: The Intuition for Why You Always Need Robust Standard Errors
  8. [132] statuser: R in user-friendly mode

2025 10

  1. [131] Bending Over Backwards: The Quadratic Puts the U in AI
  2. [130] ResearchBox: Even Easier to Use and More Transparently Permanent than Before
  3. [129] P-curve works in practice, but would it work if you dropped a piano on it?
  4. [128] LinkedOut: The Best Published Audit Study, And Its Interesting Shortcoming
  5. [127] Meaningless Means #4: Correcting Scientific Misinformation
  6. [126] Stimulus Plots
  7. [125] “Complexity” 2: Don’t be mean to the median
  8. [124] “Complexity”: 75% of participants missed comprehension questions in AER paper critiquing Prospect Theory
  9. [123] Dear Political Scientists: The binning estimator violates ceteris paribus
  10. [122] Arresting Flexibility: A QJE field experiment on police behavior with about 40 outcome variables

2024 6

  1. [121] Dear Political Scientists: Don’t Bin, GAM Instead
  2. [120] Off-Label Smirnov: How Many Subjects Show an Effect in Between-Subjects Experiments?
  3. [119] A Hidden Confound in a Psych Methods Pre‑registrations Critique
  4. [118] Harvard’s Gino Report Reveals How A Dataset Was Altered
  5. [117] The Impersonator: The Fake Data Were Coming From Inside the Lab
  6. [116] Our (First?) Day In Court

2023 9

  1. [115] Preregistration Prevalence
  2. [114] Exhibits 3, 4, and 5
  3. [113] Data Litigada: Thank You (And An Update)
  4. [112] Data Falsificada (Part 4): “Forgetting The Words”
  5. [111] Data Falsificada (Part 3): “The Cheaters Are Out of Order”
  6. [110] Data Falsificada (Part 2): “My Class Year Is Harvard”
  7. [109] Data Falsificada (Part 1): “Clusterfake”
  8. [108] MRAN is Dead, long live GRAN
  9. [107] Meaningless Means #3: The Truth About Lies

2022 7

  1. [106] Meaningless Means #2: The Average Effect of Nudging in Academic Publications is 8.7%
  2. [105] Meaningless Means #1: The Average Effect of Nudging Is d = .43
  3. [104] Meaningless Means: Some Fundamental Problems With Meta-Analytic Averages
  4. [103] Mediation Analysis is Counterintuitively Invalid
  5. [102] R on Steroids: Running WAY faster simulations in R
  6. [101] Transparency Makes Research Evaluable: Evaluating a Field Experiment on Crime Published in Nature
  7. [100] Groundhog 2.0: Further addressing the threat R poses to reproducible research

2021 5

  1. [99] Hyping Fisher: The Most Cited 2019 QJE Paper Relied on an Outdated Stata Default to Conclude Regression p -values Are Inadequate
  2. [98] Evidence of Fraud in an Influential Field Experiment About Dishonesty
  3. [97] Data Replicada #10: Does Goal Conflict Affect Time Spent on Work and Leisure?
  4. [96] Madam Speaker: Are Female Presenters Treated Worse in Econ Seminars?
  5. [95] Groundhog: Addressing The Threat That R Poses To Reproducible Research

2020 12

  1. [94] Data Replicada #9: Are Progression Ads More Credible?
  2. [93] ResearchBox: Open Research Made Easy
  3. [92] Data Replicada #8: Is The Left-Digit Bias Stronger When Prices Are Presented Side-By-Side?
  4. [91] p-hacking fast and slow: Evaluating a forthcoming AER paper deeming some econ literatures less trustworthy
  5. [90] Data Replicada #7: Does Displaying Multiple Copies of a Product Increase Its Perceived Effectiveness?
  6. [89] Data Replicada #6: The Problem of (Weird) Differential Attrition
  7. [88] The Hot-Hand Artifact for Dummies & Behavioral Scientists
  8. [87] Data Replicada #5: Do Human-Like Products Inspire More Holistic Judgments?
  9. [86] The Data Colada Seminar Series
  10. [85] Data Replicada #4: The Problem of Hidden Confounds
  11. [84] Data Replicada #3: Does Self-Concept Uncertainty Influence Magazine Subscription Choice?
  12. [83] Data Replicada #2: Do Self-Construal and Group Size Influence How People Make Choices on Behalf of a Group?

2019 10

  1. [82] Data Replicada #1: Do Elevated Viewpoints Increase Risk Taking?
  2. [81] Data Replicada
  3. [80] Interaction Effects Need Interaction Controls
  4. [79] Experimentation Aversion: Reconciling the Evidence
  5. [78c] Bayes Factors in Ten Recent Psych Science Papers
  6. [78b] Hyp-Chart, the Missing Link Between P-values and Bayes Factors
  7. [78a] If you think p-values are problematic, wait until you understand Bayes Factors
  8. [77] Number-Bunching: A New Tool for Forensic Data Analysis
  9. [76] Heterogeneity Is Replicable: Evidence From Maluma, MTurk, and Many Labs
  10. [75] Intentionally Biased: People Purposely Don’t Ignore Information They “Should” Ignore

2018 8

  1. [74] In Press at Psychological Science: A New ‘Nudge’ Supported by Implausible Data
  2. [73] Don’t Trust Internal Meta-Analysis
  3. [72] Metacritic Has A (File-Drawer) Problem
  4. [71] The (Surprising?) Shape of the File Drawer
  5. [70] How Many Studies Have Not Been Run? Why We Still Think the Average Effect Does Not Exist
  6. [69] Eight things I do to make my open research more findable and understandable
  7. [68] Pilot-Dropping Backfires (So Daryl Bem Probably Did Not Do It)
  8. [67] P-curve Handles Heterogeneity Just Fine

2017 11

  1. [66] Outliers: Evaluating A New P-Curve Of Power Poses
  2. [65] Spotlight on Science Journalism: The Health Benefits of Volunteering
  3. [64] How To Properly Preregister A Study
  4. [63] “Many Labs” Overestimated The Importance of Hidden Moderators
  5. [62] Two-lines: The First Valid Test of U-Shaped Relationships
  6. [61] Why p-curve excludes ps>.05
  7. [60] Forthcoming in JPSP: A Non-Diagnostic Audit of Psychological Research
  8. [59] PET-PEESE Is Not Like Homeopathy
  9. [58] The Funnel Plot is Invalid Because of This Crazy Assumption: r(n,d)=0
  10. [57] Interactions in Logit Regressions: Why Positive May Mean Negative
  11. [56] TWARKing: Test-Weighting After Results are Known

2016 11

  1. [55] The file-drawer problem is unfixable, and that’s OK
  2. [54] The 90x75x50 heuristic: Noisy & Wasteful Sample Sizes In The “Social Science Replication Project”
  3. [53] What I Want Our Field To Prioritize
  4. [52] Menschplaining: Three Ideas for Civil Criticism
  5. [51] Greg vs. Jamal: Why Didn’t Bertrand and Mullainathan (2004) Replicate?
  6. [50] Teenagers in Bikinis: Interpreting Police-Shooting Data
  7. [49] P-Curve Won’t Do Your Laundry, But Will Identify Replicable Findings
  8. [48] P-hacked Hypotheses Are Deceivingly Robust
  9. [47] Evaluating Replications: 40% Full ≠ 60% Empty
  10. [46] Controlling the Weather
  11. [45] Ambitious P-Hacking and P-Curve 4.0

2015 13

  1. [44] AsPredicted: Pre-registration Made Easy
  2. [43] Rain & Happiness: Why Didn’t Schwarz & Clore (1983) ‘Replicate’ ?
  3. [42] Accepting the Null: Where to Draw the Line?
  4. [41] Falsely Reassuring: Analyses of ALL p-values
  5. [40] Reducing Fraud in Science
  6. [39] Power Naps: When do Within-Subject Comparisons Help vs Hurt (yes, hurt) Power?
  7. [38] A Better Explanation Of The Endowment Effect
  8. [37] Power Posing: Reassessing The Evidence Behind The Most Popular TED Talk
  9. [36] How to Study Discrimination (or Anything) With Names; If You Must
  10. [35] The Default Bayesian Test is Prejudiced Against Small Effects
  11. [34] My Links Will Outlive You
  12. [33] “The” Effect Size Does Not Exist
  13. [32] Spotify Has Trouble With A Marketing Research Exam

2014 18

  1. [31] Women are taller than men: Misusing Occam’s Razor to lobotomize discussions of alternative explanations
  2. [30] Trim-and-Fill is Full of It (bias)
  3. [29] Help! Someone Thinks I p-hacked
  4. [28] Confidence Intervals Don’t Change How We Think about Data
  5. [27] Thirty-somethings are Shrinking and Other U-Shaped Challenges
  6. [26] What If Games Were Shorter?
  7. [25] Maybe people actually enjoy being alone with their thoughts
  8. [24] P-curve vs. Excessive Significance Test
  9. [23] Ceiling Effects and Replications
  10. [22] You know what’s on our shopping list
  11. [21] Fake-Data Colada: Excessive Linearity
  12. [20] We cannot afford to study effect size in the lab
  13. [19] Fake Data: Mendel vs. Stapel
  14. [18] MTurk vs. The Lab: Either Way We Need Big Samples
  15. [17] No-way Interactions
  16. [15] Citing Prospect Theory
  17. [13] Posterior-Hacking
  18. [12] Preregistration: Not just for the Empiro-zealots

2013 11

  1. [11] “Exactly”: The Most Famous Framing Effect Is Robust To Precise Wording
  2. [10] Reviewers are asking for it
  3. [9] Titleogy: Some facts about titles
  4. [8] Adventures in the Assessment of Animal Speed and Morality
  5. [7] Forthcoming in the American Economic Review: A Misdiagnosed Failure-to-Replicate
  6. [6] Samples Can’t Be Too Large
  7. [5] The Consistency of Random Numbers
  8. [4] The Folly of Powering Replications Based on Observed Effect Size
  9. [3] A New Way To Increase Charitable Donations: Does It Replicate?
  10. [2] Using Personal Listening Habits to Identify Personal Music Preferences
  11. [1] "Just Posting It" works, leads to new retraction in Psychology