Data Colada
Menu
  • Home
  • Table of Contents
  • Feedback Policy
  • Seminar
  • About
Menu

[84] Data Replicada #3: Does Self-Concept Uncertainty Influence Magazine Subscription Choice?

Posted on February 11, 2020February 11, 2020 by Joe & Leif

In the third installment of Data Replicada, we report our attempt to replicate a recently published Journal of Consumer Research (JCR) article entitled, “The Uncertain Self: How Self-Concept Structure Affects Subscription Choice” (.htm). The central theory in the paper can be expressed in the following way: If you are uncertain about your own self-concept, then…

Read more

[83] Data Replicada #2: Do Self-Construal and Group Size Influence How People Make Choices on Behalf of a Group?

Posted on January 15, 2020February 11, 2020 by Joe & Leif

In this second installment of Data Replicada, we report two attempts to replicate a study in a recently published Journal of Consumer Research (JCR) article entitled, “Wine for the Table: Self-Construal, Group Size, and Choice for Self and Others” (.htm). Imagine that you are in a monthly book club and it is your job to…

Read more

[82] Data Replicada #1: Do Elevated Viewpoints Increase Risk Taking?

Posted on December 11, 2019February 11, 2020 by Joe & Leif

In this post, we report our attempt to replicate a study in a recently published Journal of Marketing Research (JMR) article entitled, “Having Control Over and Above Situations: The Influence of Elevated Viewpoints on Risk Taking” (.htm). The article’s abstract summarizes the key result: “consumers’ views of scenery from a high physical elevation induce an…

Read more

[81] Data Replicada

Posted on December 9, 2019December 9, 2019 by Joe & Leif

With more than mild trepidation, we are introducing a new column called Data Replicada. In this column, we will report the results of exact (or close) preregistered replications of recently published findings. Anyone who has been paying attention will have noticed that the publication of exact (or close) replications has become increasingly common. So why…

Read more

[80] Interaction Effects Need Interaction Controls

Posted on November 20, 2019February 11, 2020 by Uri Simonsohn

In a recent referee report I argued something I have argued in several reports before: if the effect of interest in a regression is an interaction, the control variables addressing possible confounds should be interactions as well. In this post I explain that argument using as a working example a 2011 QJE paper (.htm) that…

Read more

[79] Experimentation Aversion: Reconciling the Evidence

Posted on November 7, 2019February 11, 2020 by Berkeley Dietvorst, Rob Mislavsky, and Uri Simonsohn

A PNAS paper (.htm) proposed that people object “to experiments that compare two unobjectionable policies” (their title). In our own work (.htm), we arrive at the opposite conclusion: people “don’t dislike a corporate experiment more than they dislike its worst condition” (our title). In a forthcoming PNAS letter, we identified a problem with the statistical…

Read more

[78c] Bayes Factors in Ten Recent Psych Science Papers

Posted on September 25, 2019February 11, 2020 by Uri Simonsohn

For this post, the third in a series on Bayes factors (.htm), I wanted to get a sense for how Bayes factors were being used with real data from real papers, so I looked at the 10 most recent empirical papers in Psychological Science containing the phrase "Bayes factor" (.zip). After browsing them all, I…

Read more

[78b] Hyp-Chart, the Missing Link Between P-values and Bayes Factors

Posted on September 11, 2019February 12, 2020 by Uri Simonsohn

Just two steps are needed to go from computing p-values to computing Bayes factors. This post explains both steps and introduces Hyp-Chart, the missing link we arrive at if we take only the first step. Hyp-Chart is a graph that shows how well the data fit the null vs. every possible alternative hypothesis [1]. Hyp-Chart…

Read more

[78a] If you think p-values are problematic, wait until you understand Bayes Factors

Posted on September 6, 2019September 6, 2019 by Uri Simonsohn

Would raising the minimum wage by $4 lead to greater unemployment? Milton, a Chicago economist, has a theory (supply and demand) that says so. Milton believes the causal effect is anywhere between 1% and 10%. After the minimum wage increase of $4, unemployment goes up 1%.  Milton feels bad about the unemployed but good about…

Read more

[77] Number-Bunching: A New Tool for Forensic Data Analysis

Posted on May 25, 2019November 18, 2020 by Uri Simonsohn

In this post I show how one can analyze the frequency with which values get repeated within a dataset – what I call “number-bunching” – to statistically identify whether the data were likely tampered with. Unlike Benford’s law (.htm), and its generalizations, this approach examines the entire number at once, not only the first or…

Read more
  • Previous
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • …
  • 12
  • Next

Get Colada email alerts.

Join 8,283 other subscribers

Social media

We tweet new posts: @DataColada
And mastopost'em: @DataColada@mas.to
And link to them on our Facebook page

Recent Posts

  • [114] Exhibits 3, 4, and 5
  • [113] Data Litigada: Thank You (And An Update)
  • [112] Data Falsificada (Part 4): "Forgetting The Words"
  • [111] Data Falsificada (Part 3): "The Cheaters Are Out of Order"
  • [110] Data Falsificada (Part 2): "My Class Year Is Harvard"

Get blogpost email alerts

Join 8,283 other subscribers

tweeter & facebook

We tweet new posts: @DataColada
And link to them on our Facebook page

Posts on similar topics

    search

    © 2021, Uri Simonsohn, Leif Nelson, and Joseph Simmons. For permission to reprint individual blog posts on DataColada please contact us via email..