Site logo Site logo Less Likely
  • Home
  • Articles
    • Statistical Science
    • Medicine
    • Nutrition
    • All Posts
  • Dashboards
  • Links
    • About
    • How It’s Built
    • Projects
    • Glossary
    • Contact
    • Account
    • Support
    • Blog Roll

On this page

  • Categories
    • Core Methodology
    • Applications
    • Workflow & Communication
  • Subscribe
  • Archive by Year

Other Links

  • Time Machine
  • Library
Categories
All (32)
causal inference (2)
confidence intervals (1)
data analysis (1)
data visualization (1)
interactive (3)
programming (1)
stata (1)
statistical methods (1)
statistics (22)
tutorial (1)
visualization (1)

All Posts

Complete archive of statistical methodology posts

Browse the Less Likely archive of statistical methodology, uncertainty analysis, and reproducible research.
Author

Browse all posts on statistical methodology, uncertainty analysis, and reproducible research. Use the filters below to find posts by topic or search for specific content.


When Can We Say That Something Doesn’t Work?

When Can We Say That Something Doesn’t Work?

statistics

When are we allowed to conclude that an intervention doesn’t work? Is it when a study or several studies fail to find significant differences?

17 min
3 Comments

Statistics

Statistics

Articles on statistical science, inference, uncertainty, and research methods.

1 min
Climbing Down the Ladder: Abstraction, Dashboards, and Forking Paths

Climbing Down the Ladder: Abstraction, Dashboards, and Forking Paths

statistics
visualization
data analysis

A response to Gelman and Fung’s ladder of abstraction: dashboards make the ladder two-way, which helps readers climb but also invites forking paths.

Oct 1, 2026
18 min
Leave a comment
NYC comparator methods lab: demo dashboard

NYC comparator methods lab: demo dashboard

statistics
causal inference
interactive

Explore baseline, weighting, placebo, and drift sensitivity using synthetic city homicide data.

Oct 1, 2026
15 min
How much can six months tell us? NYC comparator methods lab

How much can six months tell us? NYC comparator methods lab

statistics
causal inference
interactive

A synthetic-data demonstration of baseline, weighting, placebo, and trend-sensitivity checks for NYC homicide comparisons.

Oct 1, 2026
15 min
Leave a comment
 

The P-value Is Not a Verdict: An Interactive Consonance Curve

statistics
interactive

Drag an estimate and its interval and watch the entire P-value function, every compatibility interval, and the S-value move together.

Sep 24, 2026
23 min
Leave a comment
Constructing Likelihood Functions in R, Stata, Python, Julia, MATLAB, and SQL

Constructing Likelihood Functions in R, Stata, Python, Julia, MATLAB, and SQL

statistics

Building likelihood and support functions from the same estimate in R, Stata, Python, Julia, MATLAB, and SQL, and checking they agree.

Sep 24, 2026
46 min
Leave a comment
 

How to Be a Good Collaborator to a Statistician and a Data Engineer

statistics

Good collaboration with statisticians and data engineers comes down to a set of concrete habits. Here is what each side owes the other, with checklists.

Aug 11, 2026
14 min
Leave a comment
 

The Octagon Is a One-Trial Experiment

statistics

One MMA fight tells us little about who is better. Repeat it ten times and the better fighter’s edge shows, which is what frequency probability describes.

Jun 23, 2026
9 min
Leave a comment
 

Multi-Language Code Examples

statistics
programming
tutorial

Examples of using Stata, Julia, and pseudocode in blog posts

Jan 6, 2026
5 min
Leave a comment
Confidence, Posteriors, and the Bootstrap

Confidence, Posteriors, and the Bootstrap

statistics

This guide discusses the bootstrap resampling method and its close connection to the consonance distribution and how to use certain iterations of the bootstrap to construct a consonance distribution.

Jan 12, 2025
11 min
Leave a comment
Computing Confidence Interval Functions with cifunction

Computing Confidence Interval Functions with cifunction

statistics
stata
confidence intervals
data visualization
statistical methods

How to compute and plot confidence interval functions (confidence curves, P-value functions) in Stata with the cifunction package, with worked examples.

Mar 23, 2024
11 min
Leave a comment
Your Models Are Neither Useful Nor Approximate

Your Models Are Neither Useful Nor Approximate

statistics

A discussion about models and the assumptions that underlie them.

Jan 1, 2024
11 min
Leave a comment
Using Stata: Producing Consonance Functions

Using Stata: Producing Consonance Functions

statistics

A simple guide on how to produce consonance functions in Stata.

Jan 1, 2024
16 min
Leave a comment
Simulation of a Two-Group Parallel-Arm RCT with Interim Analyses

Simulation of a Two-Group Parallel-Arm RCT with Interim Analyses

statistics

A simulation of a two-group parallel-arm randomized trial with interim analysis using the rpact package.

Feb 1, 2021
13 min
Leave a comment
Tables, Graphs, and Computations from Rafi & Greenland (2020)

Tables, Graphs, and Computations from Rafi & Greenland (2020)

This post goes through the R code and logic that was used to construct the figures and concepts in Rafi & Greenland (2020) BMC MRM.

Dec 12, 2020
39 min
Leave a comment
What Makes a Sensitivity Analysis?

What Makes a Sensitivity Analysis?

statistics

Sensitivity analyses are an important part of statistical analyses, however, there are major misconceptions about what they do and what qualifies as such an analysis.

Dec 12, 2020
97 min
Leave a comment
 

Medicine Is Being Treated with Snake-Oil Statistics

statistics
Suggested Running Head: Snake Oil Statistics
Nov 11, 2020
16 min
Leave a comment
Quality Control in Statistical Analyses

Quality Control in Statistical Analyses

statistics

Experienced statisticians and data analysts are familiar with stories where a coding error has led to an entire conclusion changing, even leading to a retraction. It’s the sort of stuff that keeps people up at night.

Jun 13, 2020
43 min
Leave a comment
Book Review: Regression and Other Stories by Gelman, Hill, and Vehtari

Book Review: Regression and Other Stories by Gelman, Hill, and Vehtari

An early look at Gelman et als new book, Regression and Other Stories, which is an update to their seminal 2006 book, Data Analysis Using Regression and Multilevel Hierarchical Models.

Jun 11, 2019
3 min
Leave a comment
Book Review: Fisher, Neyman, and the Creation of Classical Statistics

Book Review: Fisher, Neyman, and the Creation of Classical Statistics

A review of Erich Lehmann’s last book, Fisher, Neyman, and the Creation of Classical Statistics.

Dec 30, 2018
25 min
1 Comment
GAMS

GAMS

statistics

Some sample scripts

Nov 11, 2018
8 min
Leave a comment
P-values Are Tough And S-values Can Help

P-values Are Tough And S-values Can Help

statistics

An extensive discussion about what P-values are, their properties, common interpretations, misinterpretations, and how a measure called an S-value may better help us interpret them.

Nov 11, 2018
29 min
3 webmentions12 Comments
We May Not Understand Control Groups

We May Not Understand Control Groups

Discussions praising the efficiency of randomized trials are widespread, however, few of these discussions take a close look at some of the common assumptions that individuals hold regarding randomized trials. And unfortunately, these common assumptions may be based on outdated evidence and simplistic ideas.

Oct 28, 2018
11 min
1 webmentionLeave a comment
Misplaced Confidence in Observed Power

Misplaced Confidence in Observed Power

statistics

Another misinterpretation of what statistical power is and how trial results should be interpreted.

Sep 30, 2018
3 min
Leave a comment
Misplaced Confidence in Observed Power

Misplaced Confidence in Observed Power

Another misinterpretation of what statistical power is and how trial results should be reported in a popular journal.

Sep 30, 2018
2 min
Leave a comment
The Bradford Hill Criteria Don’t Hold Up

The Bradford Hill Criteria Don’t Hold Up

The Bradford Hill viewpoints are commonly used as a checklist to argue for causality when randomized trials aren’t possible. However, the originator of these viewpoints never intended for them to be used this way. In this post, I examine the shortcomings of using these viewpoints as a checklist in the real world.

Sep 6, 2018
14 min
11 Comments
Misuse of Standard Error in Clinical Trials

Misuse of Standard Error in Clinical Trials

statistics

Analytic statistics are commonly used to make inferences from the data. However, they are often misused because of misconceptions about what they do. In this post, I discuss how standard error is commonly misused in clinical trials.

Aug 7, 2018
5 min
1 Comment
Vitamin E, Mortality, and the Bayesian Gloss

Vitamin E, Mortality, and the Bayesian Gloss

A look at a time when Bayesian data analysis went off the rails.

Jun 20, 2018
8 min
Leave a comment
Problems with the Number Needed to Treat

Problems with the Number Needed to Treat

The number needed to treat is a popular statistic used in medicine, but it has several problems associated with the way it is used and in this blog post, I discuss some of those problems and possible solutions.

May 27, 2018
9 min
Leave a comment
Myth: Covariates Need to Be Balanced in RCTs

Myth: Covariates Need to Be Balanced in RCTs

Many people believe that the purpose of randomization is to perfectly balance out both known and unknown covariates in order to reach causal inferences, however, this is simply not true and is a misunderstanding of the process of randomization.

Apr 10, 2018
4 min
3 Comments
Stan: Bayesian Modeling Examples

Stan: Bayesian Modeling Examples

statistics

Sample scripts and examples for Bayesian modeling using Stan.

Jan 1, 2018
15 min
Leave a comment
No matching items

Categories

Explore posts by topic:

Core Methodology

  • Bootstrap Methods - Resampling techniques for uncertainty quantification
  • Bayesian Statistics - Bayesian approaches to inference
  • Sensitivity Analysis - Exploring assumption impacts
  • Statistical Inference - Confidence intervals, hypothesis testing

Applications

  • Causal Inference - Bradford Hill criteria, study design
  • Model Selection - Choosing and validating models
  • Data Management - Data cleaning and preparation
  • Visualization - Effective presentation of results

Workflow & Communication

  • Statistical Workflow - Best practices for analysis pipelines
  • Reproducible Research - Transparent, reproducible methods
  • Scientific Communication - Reporting statistical findings

Subscribe

Stay updated on new posts:

  • RSS Feed
  • Twitter: @dailyzad
  • GitHub: Watch repository

Archive by Year

  • 2025
  • 2024
  • 2023
Back to top

Comments

Webmentions

Replies, likes, and mentions from around the web, tracked via Webmention.io. What’s a webmention?

No webmentions yet.

This website uses cookies. By continuing to read, you accept the use of cookies.
Source Code
---
title: "All Posts"
description: "Browse the Less Likely archive of statistical methodology, uncertainty analysis, and reproducible research."
subtitle: "Complete archive of statistical methodology posts"
author: []
listing:
  - id: all-posts
    contents:
      - statistics/*.qmd
      - "!statistics/market-basket.qmd"   # internal — never list publicly
    sort: "date desc"
    type: default
    categories: true
    sort-ui: [date, title]
    filter-ui: [title, description, categories]
    fields: [image, date, title, description, categories, reading-time]
    feed: true
    page-size: 100
page-layout: full
---

Browse all posts on statistical methodology, uncertainty analysis, and reproducible research. Use the filters below to find posts by topic or search for specific content.

---

::: {#all-posts}
:::

---

## Categories

Explore posts by topic:

### Core Methodology
- [Bootstrap Methods](#category=bootstrap) - Resampling techniques for uncertainty quantification
- [Bayesian Statistics](#category=bayesian) - Bayesian approaches to inference
- [Sensitivity Analysis](#category=sensitivity-analysis) - Exploring assumption impacts
- [Statistical Inference](#category=statistical-inference) - Confidence intervals, hypothesis testing

### Applications
- [Causal Inference](#category=causal-inference) - Bradford Hill criteria, study design
- [Model Selection](#category=model-selection) - Choosing and validating models
- [Data Management](#category=data-management) - Data cleaning and preparation
- [Visualization](#category=visualization) - Effective presentation of results

### Workflow & Communication
- [Statistical Workflow](#category=statistical-workflow) - Best practices for analysis pipelines
- [Reproducible Research](#category=reproducible-research) - Transparent, reproducible methods
- [Scientific Communication](#category=scientific-communication) - Reporting statistical findings

---

## Subscribe

Stay updated on new posts:

- [RSS Feed](blog.xml)
- [Twitter: \@dailyzad](https://twitter.com/dailyzad)
- [GitHub: Watch repository](https://github.com/yourusername/LessLikely)

---

## Archive by Year

- [2025](posts.qmd#year=2025)
- [2024](posts.qmd#year=2024)
- [2023](posts.qmd#year=2023)

© 2026 Less Likely · Privacy · License · Comment Policy

Built with Quarto · RSS

Netlify Status