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Multiple comparisons problem


Multiple comparisons problem - Wikipedia

Multiple comparisons problem ... In statistics, the multiple comparisons, multiplicity or multiple testing problem occurs when one considers a set of statistical ...

Common pitfalls in statistical analysis: The perils of multiple testing

Multiple testing refers to situations where a dataset is subjected to statistical testing multiple times - either at multiple time-points or through multiple ...

The Multiple Comparison Problem Explained | Statistics - Physiotutors

The multiple comparison problem is the issue that arises when multiple tests on the same sample are performed. An example will illustrate this. Eg. Let's ...

Basics: When does the multiple comparison problem occur?

Multiple comparisons arise when a statistical analysis involves multiple simultaneous statistical tests, each of which has a potential to produce a discovery.

How do I deal with the multiple comparisons problem? : r/AskStatistics

At the same time, since you have larger samples, you could simultaneously reduce the rate of type I error as you increase sample size (as long ...

Correction For Multiple Comparisons - Statsig Glossary

The multiple comparisons problem ... When running experiments with multiple metrics or variants, the probability of observing a false positive result increases.

The Problem of Multiple Comparisons | NEJM Evidence - YouTube

This animated video reviews the problem of multiple comparisons in research studies and explains how performing multiple statistical ...

Navigating the Multiple Comparison problem in statistics - VSNi

When a set of statistical inferences is considered simultaneously, the multiple comparison problem occurs. Due to this, there is a higher chance of finding a ...

6.1: Multiple Comparisons - Statistics LibreTexts

The classic approach to the multiple comparison problem is to control the familywise error rate. Instead of setting the critical P level for significance, or ...

10.3 - Multiple Comparisons | STAT 500

Multiple comparisons conducts an analysis of all possible pairwise means. For example, with three brands of cigarettes, A, B, and C, if the ANOVA test was ...

Multiple Testing Problem / Multiple Comparisons - Statistics How To

If you use the standard alpha level of 5% (which is the probability of getting a false positive), you're going to get around 500 significant results — most of ...

The Problem of Multiple Comparisons - NEJM Evidence

The Problem of Multiple Comparisons. 3m 19s. This animated video reviews the problem of multiple comparisons in research studies and explains ...

What is the proper way to apply the multiple comparison test? - PMC

Multiple comparisons tests (MCTs) are performed several times on the mean of experimental conditions. When the null hypothesis is rejected in a validation, MCTs ...

Multiple comparisons: To compare or not to ... - ScienceDirect.com

When making multiple comparisons in a study, however, the likelihood of making a Type-I error can dramatically increase. When conducting multiple comparisons, ...

The Misleading Effect of Noise: The Multiple Comparisons Problem

The CEO's mistake is an example of the multiple comparisons problem. The issue comes down to the noisiness of data in the real world. While the ...

When it makes sense to not correct for multiple comparisons

Instead report all of the individual P values and confidence intervals, and make it clear that no mathematical correction was made for multiple comparisons.

Multiple Testing

In this article, we describe the problem of multiple testing more formally and discuss meth- ods which account for the multiplicity issue. In particular ...

[Q] What counts as 'multiple comparisons'? : r/statistics - Reddit

There is no strict definition of multiple comparisons in the statistics literature: it sometimes refers to comparing multiple groups between each other or ...

Adjust for Multiple Comparisons? It's Not That Simple

Multiple comparisons are an unavoidable problem in medical research. The human organism is complex; in our efforts to understand how to maintain our health ...

The problem with unadjusted multiple and sequential statistical testing

Unadjusted sequential sampling leads to severe statistical issues, such as an inflated rate of false positive findings.