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Multiple comparisons problem: History & Standards

Multiple comparisons, multiplicity or multiple testing problem occurs when many statistical tests are performed on the same dataset. Each test has its own chance of a Type I error (false positive), so the overall probability of making at least one false positive increases as the number of tests grows. In statistics, this occurs when one simultaneously…

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Multiple comparisons problem topic overview

The analysis highlights History and Standards as prominent areas in the source structure around Multiple comparisons problem.

Related topics
41
Source areas
5
Connected nodes
46
Extracted relationships
5
Related term clusters
20
Bridge connections
46

What this topic covers Research coverage

Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.

Large-scale multiple testing · 14 topics
Definition · 12 topics
Controlling procedures · 5 topics
History · 5 topics
Overview · 5 topics

Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.

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Explore all related topics Closing gaps

Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.

Overview

History

Definition

Controlling procedures

Large-scale multiple testing

For the semantics nerds

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Advanced semantic analysis

How Multiple comparisons problem connects Entity context

See recurring relationship patterns around Multiple comparisons problem before inspecting the individual extracted relationships.

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

multiple tests comparisons one testing number statistical false error hypotheses true significant independent problem test correction null displaystyle rate probability

Multiple comparisons problem relationships Subject–Predicate–Object triples

TTTA extracted 5 structured relationships around Multiple comparisons problem. Examples in this analysis include Tukey → instance of → HistoryThe problem of multiple comparisons received increased attention in the 1950s with the work of statisticians and microarrays → instance of → when using technologies. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
Tukeyinstance ofHistoryThe problem of multiple comparisons received increased attention in the 1950s with the work of statisticians0.80text
Schefféinstance ofHistoryThe problem of multiple comparisons received increased attention in the 1950s with the work of statisticians0.80text
microarraysinstance ofwhen using technologies0.80text
expression levels of tens of thousands of genes can be measuredinstance ofwhen using technologies0.80text
and genotypes for millions of genetic markers can be measuredinstance ofwhen using technologies0.80text

Related concept clusters Related term clusters

The concept neighborhoods around Multiple comparisons problem bring nearby vocabulary together. In this analysis, examples include Multiple, Testing and Problem. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • Multiple comparisons problem
    • Multiple
    • Testing
    • Problem
    • Statistical
    • Tests
    • Analysis
    • Significant
    • Independent
    • False
    • Also
    • Hypothesis
    • Correction
  • multiple comparisons problem
    • Multiple
    • Testing
    • Also
    • Problem
    • Correction
    • Statistical
    • Tests
    • Analysis
    • Significant
    • Independent
    • Many
    • False
  • statistical inferences
    • Made
    • Tests
    • Testing
    • Inferences
    • Statistical
    • Number
    • Developed
    • Observed
    • Analysis
    • Family-wise
    • Likely
    • Results
  • family-wise error rate
    • Rate
    • Family-wise
    • False
    • Alpha
    • Displaystyle
    • Results
    • Positives
    • Least
    • Tests
    • Number
    • Also
    • Correction
  • sampling error
    • Family-wise
    • Rate
    • False
    • Displaystyle
    • Alpha
    • Positives
    • Least
    • Tests
    • Number
    • Also
    • Probability
    • Results
  • expected number
    • Tests
    • Null
    • One
    • Hypotheses
    • Likely
    • Positives
    • Inferences
    • True
    • Made
    • Also
    • Level
    • Probability
  • false positives
    • Positives
    • Also
    • Hypotheses
    • True
    • Rate
    • Null
    • Significant
    • Tests
    • Family-wise
    • Hypothesis
    • Level
    • Results
  • statistical test
    • Hypothesis
    • Tests
    • Null
    • Testing
    • Significant
    • True
    • Inferences
    • Developed
    • Level
    • Observed
    • Results
    • Analysis

Connections between topic areas Semantic bridges

For Multiple comparisons problem, one of the stronger structural bridges in this analysis connects Multiple comparisons problem with Large-scale multiple testing. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3
Multiple comparisons problem — Large-scale multiple testing · splits 32 ⟂ 15
Multiple comparisons problem — Definition · splits 34 ⟂ 13
Multiple comparisons problem — Overview · splits 41 ⟂ 6
Multiple comparisons problem — History · splits 41 ⟂ 6
Multiple comparisons problem — Controlling procedures · splits 41 ⟂ 6

Map overview Semantic statistics

Multiple comparisons problem

Nodes47
Edges46
Triples5
Avg. degree1.96
Density0.042553
Components1

Source & methodology

TTTA analyzes the structure around Multiple comparisons problem to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History & Standards, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — Multiple comparisons problem · EN edition · Analysis: TopicsToTalkAbout

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