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

Calculating and Interpreting the Linear Correlation Coefficient01:11

Calculating and Interpreting the Linear Correlation Coefficient

8.3K
The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable, x, and the dependent variable, y. Hence, it is also known as the Pearson product-moment correlation coefficient. It can be calculated using the following equation:
8.3K
Reliability and Validity01:29

Reliability and Validity

14.0K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
14.0K
Calculating the Equilibrium Constant02:46

Calculating the Equilibrium Constant

38.1K
The equilibrium constant for a reaction is calculated from the equilibrium concentrations (or pressures) of its reactants and products. If these concentrations are known, the calculation simply involves their substitution into the Kc expression.
For example, gaseous nitrogen dioxide forms dinitrogen tetroxide according to this equation:
38.1K
Calculating Standard Free Energy Changes02:49

Calculating Standard Free Energy Changes

25.6K
The free energy change for a reaction that occurs under the standard conditions of 1 bar pressure and at 298 K is called the standard free energy change. Since free energy is a state function, its value depends only on the conditions of the initial and final states of the system. A convenient and common approach to the calculation of free energy changes for physical and chemical reactions is by use of widely available compilations of standard state thermodynamic data. One method involves the...
25.6K
Calculating pH Changes in a Buffer Solution02:45

Calculating pH Changes in a Buffer Solution

58.8K
A buffer can prevent a sudden drop or increase in the pH of a solution after the addition of a strong acid or base up to its buffering capacity; however, such addition of a strong acid or base does result in the slight pH change of the solution. The small pH change can be calculated by determining the resulting change in the concentration of buffer components, i.e., a weak acid and its conjugate base or vice versa. The concentrations obtained using these stoichiometric calculations can be used...
58.8K
Interpreting R Charts01:22

Interpreting R Charts

355
R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
355

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

Specific Multimodal Imaging of Deep-Seated Tumor with High Intratumoral Retention <i>via In Situ</i> Assembly of Probes.

ACS nano·2026
Same author

Low-Profile Metasurface Antenna for Broadband RCS Reduction and Omnidirectional Radiation.

Materials (Basel, Switzerland)·2026
Same author

The role of sortilin in cardiovascular calcification: mechanisms and therapeutic potential.

Frontiers in cardiovascular medicine·2026
Same author

Unpacking contextual changes underlying self-injurious thoughts and behaviors among bullying-involved adolescents and young adults in the aftermath of the COVID-19 pandemic.

BMC psychology·2026
Same author

Association of PAX1/JAM3 gene methylation, HR-HPV, and TCT with high-grade cervical lesions in a high-risk cohort: a multinomial logistic regression analysis.

BMC women's health·2026
Same author

Finerenone in Treating a 12-Year-Old Boy Suffering Gitelman Syndrome Without Causing Gynecomastia.

Nephrology (Carlton, Vic.)·2026
Same journal

Bayesian Machine Learning Tools for Alcohol Use Disorder Research: The bpaup R Package.

Multivariate behavioral research·2026
Same journal

A Unified Framework for Jointly modelling Response Times and Item Position Effects in Computer-Based Learning Assessments.

Multivariate behavioral research·2026
Same journal

Generalizability Theory Applied to Daily Relationship Quality: Substantive and Statistical Directions.

Multivariate behavioral research·2026
Same journal

A Modularized Higher-Order Diagnostic Classification Model for Clustered Attribute Hierarchies.

Multivariate behavioral research·2026
Same journal

Generalizing Causal Effects to a Target Population Without Individual-Level Data from the Target Population.

Multivariate behavioral research·2026
Same journal

betaselectr: Selective (and Proper) Standardization in Structural Equation Models.

Multivariate behavioral research·2026
関連記事をすべて見る

関連する実験動画

Updated: Feb 6, 2026

How to Obtain Reliable Visual Event-related Potentials in Newborns
07:39

How to Obtain Reliable Visual Event-related Potentials in Newborns

Published on: October 24, 2019

6.8K

bifactorモデルにおける最大信頼性の計算と解釈

Sijia Li1, Victoria Savalei1

  • 1Department of Psychology, University of British Columbia, Vancouver, Canada.

Multivariate behavioral research
|February 4, 2026
PubMed
まとめ
この要約は機械生成です。

研究者はしばしばbifactorモデルで最大信頼性を誤用します。新しい方程式が提供されていますが、最適な複合(OLC)およびサブ複合(OLSC)は、信頼性と解釈の問題が少なく、グループ因子には信頼性がありません。

キーワード:
bifactorモデル係数H確認的因子分析最大信頼性回帰因子スコア

さらに関連する動画

Imaging In-Stent Restenosis: An Inexpensive, Reliable, and Rapid Preclinical Model
09:46

Imaging In-Stent Restenosis: An Inexpensive, Reliable, and Rapid Preclinical Model

Published on: September 14, 2009

14.3K
A Reliable Porcine Fascio-Cutaneous Flap Model for Vascularized Composite Allografts Bioengineering Studies
05:34

A Reliable Porcine Fascio-Cutaneous Flap Model for Vascularized Composite Allografts Bioengineering Studies

Published on: March 31, 2022

2.8K

関連する実験動画

Last Updated: Feb 6, 2026

How to Obtain Reliable Visual Event-related Potentials in Newborns
07:39

How to Obtain Reliable Visual Event-related Potentials in Newborns

Published on: October 24, 2019

6.8K
Imaging In-Stent Restenosis: An Inexpensive, Reliable, and Rapid Preclinical Model
09:46

Imaging In-Stent Restenosis: An Inexpensive, Reliable, and Rapid Preclinical Model

Published on: September 14, 2009

14.3K
A Reliable Porcine Fascio-Cutaneous Flap Model for Vascularized Composite Allografts Bioengineering Studies
05:34

A Reliable Porcine Fascio-Cutaneous Flap Model for Vascularized Composite Allografts Bioengineering Studies

Published on: March 31, 2022

2.8K