scispace - formally typeset
M

Mark J. Brandt

Researcher at Michigan State University

Publications -  134
Citations -  12288

Mark J. Brandt is an academic researcher from Michigan State University. The author has contributed to research in topics: Ideology & Politics. The author has an hindex of 31, co-authored 121 publications receiving 10029 citations. Previous affiliations of Mark J. Brandt include Tilburg University & New York University Abu Dhabi.

Papers
More filters
Journal ArticleDOI

Estimating the reproducibility of psychological science

Alexander A. Aarts, +290 more
- 28 Aug 2015 - 
TL;DR: A large-scale assessment suggests that experimental reproducibility in psychology leaves a lot to be desired, and correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.
Journal ArticleDOI

Investigating variation in replicability: A “Many Labs” replication project

Richard A. Klein, +50 more
- 01 Jan 2014 - 
TL;DR: The authors compared variation in the replicability of 13 classic and contemporary effects across 36 independent samples totaling 6,344 participants and found that the results of these experiments are more dependent on the effect itself than on the sample and setting used to investigate the effect.
Journal ArticleDOI

Many Labs 2: Investigating Variation in Replicability Across Samples and Settings

Richard A. Klein, +190 more
TL;DR: This paper conducted preregistered replications of 28 classic and contemporary published findings, with protocols that were peer reviewed in advance, to examine variation in effect magnitudes across samples and settings, and found that very little heterogeneity was attributable to the order in which the tasks were performed or whether the task were administered in lab versus online.
Journal ArticleDOI

The Replication Recipe: What Makes for a Convincing Replication?

TL;DR: This article developed a replication recipe to facilitate close and convincing replication attempts, outlining standard criteria for a convincing close replication, including faithfully recreating the original study while keeping track of differences, achieving high statistical power, checking the study's assumptions in new contexts, and pre-registering the study.