Jove
Visualize
お問い合わせ
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する概念動画

Crossover Experiments01:16

Crossover Experiments

Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...
McNemar's Test01:23

McNemar's Test

McNemar's Test is a nonparametric statistical test used to determine if there is a significant difference in proportions between two related groups when the outcome is binary (e.g., yes/no, success/failure). It is beneficial when we have paired data, such as pre-test/post-test designs, where the same subjects are measured under two different conditions. The test is named after the statistician Quinn McNemar, who introduced it in 1947. It is commonly used in situations where subjects are...

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

Response-adaptive randomization with imperfect intermediate endpoints.

Clinical trials (London, England)·2026
Same author

Treatment of indolent systemic mastocytosis with sarilumab is not supported in a randomized trial.

The journal of allergy and clinical immunology. Global·2025
Same author

Futility Monitoring in Clinical Trials.

Statistics in medicine·2025
Same author

Does Remdesivir Lower COVID-19 Mortality? A Subgroup Analysis of Hospitalized Adults Receiving Supplemental Oxygen.

Statistics in medicine·2024
Same author

Changing interim monitoring in response to internal clinical trial data.

Biometrics·2024
Same author

Genetically defined individual reference ranges for tryptase limit unnecessary procedures and unmask myeloid neoplasms.

Blood advances·2022
Same journal

A statistical evaluation of decision-making methods and the efficiency of Bayesian multi-arm multi-stage trials.

Clinical trials (London, England)·2026
Same journal

Accounting for non-adherence: A re-analysis of the Liraglutide Effect and Action in Diabetes: Evaluation of Cardiovascular Outcome Results trial.

Clinical trials (London, England)·2026
Same journal

Phase I design for partially ordered groups with late-onset toxicity.

Clinical trials (London, England)·2026
Same journal

Trial informed consent forms, the Declaration of Helsinki and the SPIRIT 2025 statement.

Clinical trials (London, England)·2026
Same journal

17th Annual University of Pennsylvania Conference on statistical issues in clinical trials - Covariate adjustment in randomized clinical trials: New methods and applications (Morning panel discussion).

Clinical trials (London, England)·2026
Same journal

17th Annual University of Pennsylvania Conference on statistical issues in clinical trials - Covariate adjustment in randomized clinical trials: New methods and applications (Afternoon panel discussion).

Clinical trials (London, England)·2026
関連記事をすべて見る

関連する実験動画

Updated: Jun 2, 2026

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
07:05

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

Published on: September 10, 2018

6.5K

バイナリエンドポイントを備えた2つの武器の試験のイベント駆動計画です.

Erica H Brittain1, Raphaël N Morsomme1, Michael A Proschan1

  • 1Office of Biostatistics Research, NIAID, NIH, Bethesda, MD, USA.

Clinical trials (London, England)
|February 16, 2026
PubMed
まとめ
この要約は機械生成です。

イベントの確率が低い臨床試験では,イベントの数はサンプルサイズよりも安定しています. この安定性は,適応的な試験設計を強化し,バイナリエンドポイントのための単純なイベント主導の戦略を可能にすることができます.

キーワード:
クリニック・トライアル 臨床試験バイナリデータのバイナリデータです.イベント駆動型トライアルオッズ比率 オッズ比率 オッズ比率は,オッズ比率は,オッズ比率は,オッズ比率は,オッズ比率は,オッズ比率は,オッズ比率は,オッズ比率はリスク差の差は,リスク差の差です.リスク比率リスク比率は,サンプルサイズ計算の計算

さらに関連する動画

Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats
09:12

Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats

Published on: March 17, 2019

10.1K
RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

3.4K

関連する実験動画

Last Updated: Jun 2, 2026

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
07:05

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

Published on: September 10, 2018

6.5K
Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats
09:12

Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats

Published on: March 17, 2019

10.1K
RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

3.4K

科学分野:

  • バイオ統計学 バイオ統計学
  • 臨床試験のデザイン
  • 統計力の分析 統計力の分析

背景:

  • バイナリエンドポイントを持つ臨床試験のサンプルサイズ計算は,しばしば不確実なイベントの確率に依存します.
  • 生存試験は,未知のパラメータに対して,サンプルのサイズよりも敏感なイベントの数によって推進されます.
  • この研究では,バイナリな結果を持つ2つの腕のランダム化試験におけるサンプルサイズに対するイベントカウントの相対的な安定性を調査しています.

研究 の 目的:

  • バイナリエンドポイント試験のサンプルサイズと比較したイベント数の相対的な安定性を定量化します.
  • この相対的な安定性を利用して,適応的試験設計の強化を探求する.
  • このような環境における単純なイベント主導戦略の潜在的利益を評価する.

主な方法:

  • 相対リスク,オッズ比,リスク差のサンプルサイズに対するイベント数の安定性を評価するために,サンプルサイズの式を使用した.
  • 比較的安定した条件下でイベント駆動設計を評価するためのシミュレーションを実施.
  • 様々な分析方法と試験停止戦略を使用して,タイプIエラー率とパワーを評価しました.

主要な成果:

  • イベントの数は,相対リスク (イベントの確率 < 1/3) とオッズ比 (イベントの確率 < 0.20) のサンプルサイズよりも少なくとも3倍安定しています.
  • この安定性は,エラー率や治療効果の大きさとは無関係です.
  • イベント駆動設計のシミュレーションは,アシンプトティックな方法がタイプIエラーを膨らませる一方で,他のアプローチは有利な動作特性を示すことを示しました.

結論:

  • 事件の確率が適度に低い試験では,イベントの数に焦点を当てることで,試験計画と無意味性評価を助けることができます.
  • このアプローチは,バイナリエンドポイントのためのシンプルで実行可能で魅力的なイベント駆動設計の開発を容易にする可能性があります.
  • イベント中心の視点を採用することで,臨床試験の計画と実行を簡素化することができます.