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Replication crisis 14/15 https://en.wikipedia.org/wiki/Replication_crisis reference science, encyclopedia 2026-05-05T06:28:33.005921+00:00 kb-cron

==== Cross-validation ==== One common statistical problem is overfitting, that is, when researchers fit a regression model over a large number of variables but a small number of data points. For example, a typical fMRI study of emotion, personality, and social cognition has fewer than 100 subjects, but each subject has 10,000 voxels. The study would fit a sparse linear regression model that uses the voxels to predict a variable of interest, such as self-reported stress. But the study would then report on the p-value of the model on the same data it was fitted to. The standard approach in statistics, where data is split into a training and a validation set, is resisted because test subjects are expensive to acquire. One possible solution is cross-validation, which allows model validation while also allowing the whole dataset to be used for model-fitting.

=== Replication efforts ===

==== Funding ==== In July 2016, the Netherlands Organisation for Scientific Research made €3 million available for replication studies. The funding is for replication based on reanalysis of existing data and replication by collecting and analysing new data. Funding is available in the areas of social sciences, health research and healthcare innovation. In 2013, the Laura and John Arnold Foundation funded the launch of The Center for Open Science with a $5.25 million grant. By 2017, it provided an additional $10 million in funding. It also funded the launch of the Meta-Research Innovation Center at Stanford at Stanford University run by Ioannidis and medical scientist Steven Goodman to study ways to improve scientific research. It also provided funding for the AllTrials initiative led in part by medical scientist Ben Goldacre.

==== Emphasis in post-secondary education ====

Based on coursework in experimental methods at MIT, Stanford, and the University of Washington, it has been suggested that methods courses in psychology and other fields should emphasize replication attempts rather than original studies. Such an approach would help students learn scientific methodology and provide numerous independent replications of meaningful scientific findings that would test the replicability of scientific findings. Some have recommended that graduate students should be required to publish a high-quality replication attempt on a topic related to their doctoral research prior to graduation.

==== Replication database ==== There has been a concern that replication attempts have been growing. As a result, this may lead to lead to research waste. In turn, this has led to a need to systematically track replication attempts. As a result, several databases have been created (e.g.). The databases have created a replication database that includes psychology among other disciplines, to promote theory-driven research and optimize the use of academic and institutional resource, while promoting trust in science.

===== Final year thesis ===== Some institutions require undergraduate students to submit a final year thesis that consists of an original piece of research. Daniel Quintana, a psychologist at the University of Oslo in Norway, has recommended that students should be encouraged to perform replication studies in thesis projects, as well as being taught about open science.

===== Semi-automated =====

Researchers demonstrated a way of semi-automated testing for reproducibility: statements about experimental results were extracted from, as of 2022 non-semantic, gene expression cancer research papers and subsequently reproduced via robot scientist "Eve". Problems of this approach include that it may not be feasible for many areas of research and that sufficient experimental data may not get extracted from some or many papers even if available.

==== Involving original authors ==== Psychologist Daniel Kahneman argued that, in psychology, the original authors should be involved in the replication effort because the published methods are often too vague. Others, such as psychologist Andrew Wilson, disagree, arguing that the original authors should write down the methods in detail. An investigation of replication rates in psychology in 2012 indicated higher success rates of replication in replication studies when there was author overlap with the original authors of a study (91.7% successful replication rates in studies with author overlap compared to 64.6% successful replication rates without author overlap).

==== Big team science ==== The replication crisis has led to the formation and development of various large-scale and collaborative communities to pool their resources to address a single question across cultures, countries and disciplines. The focus is on replication, to ensure that the effect generalizes beyond a specific culture and investigate whether the effect is replicable and genuine. This allows interdisciplinary internal reviews, multiple perspectives, uniform protocols across labs, and recruiting larger and more diverse samples. Researchers can collaborate by coordinating data collection or fund data collection by researchers who may not have access to the funds, allowing larger sample sizes and increasing the robustness of the conclusions.

=== Broader changes to scientific approach ===

==== Emphasize triangulation, not just replication ==== Psychologist Marcus R. Munafò and Epidemiologist George Davey Smith argue, in a piece published by Nature, that research should emphasize triangulation, not just replication, to protect against flawed ideas. They claim that,

replication alone will get us only so far (and) might actually make matters worse ... [Triangulation] is the strategic use of multiple approaches to address one question. Each approach has its own unrelated assumptions, strengths and weaknesses. Results that agree across different methodologies are less likely to be artefacts. ... Maybe one reason replication has captured so much interest is the often-repeated idea that falsification is at the heart of the scientific enterprise. This idea was popularized by Karl Popper's 1950s maxim that theories can never be proved, only falsified. Yet an overemphasis on repeating experiments could provide an unfounded sense of certainty about findings that rely on a single approach. ... philosophers of science have moved on since Popper. Better descriptions of how scientists actually work include what epistemologist Peter Lipton called in 1991 "inference to the best explanation".

==== Complex systems paradigm ====