Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Noncompartmental Analysis: Statistical Moment Theory

Noncompartmental Analysis: Statistical Moment Theory

Noncompartmental analyses leverage statistical moment theory to examine time-related changes in macroscopic events, encapsulating the collective outcomes stemming from the constituent elements in play. Statistical moment theory is a mathematical approach used to describe the time course of drug concentration in the body without assuming a specific compartmental model. SMT provides insights into drug absorption, distribution, metabolism, and elimination by treating drug concentration versus time...

Central Tendency: Analysis

Central Tendency: Analysis

Measures of central tendency are tools used in biostatistics to identify the average or center of a dataset. They offer a single representative value for understanding and summarizing data distribution.
The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
The median, another measure,...

Equity Theory

Equity Theory

Equity theory explains how our sense of fairness influences the dynamics of close relationships. Rooted in social psychology, the theory posits that individuals evaluate fairness by comparing the ratio of their contributions to the rewards they receive. Relationship satisfaction is highest when these ratios are perceived as balanced between partners, promoting mutual reciprocity and a sense of justice.Equity vs. Equality in RelationshipsEquity is distinct from equality. Fairness does not...

Empirical Method to Interpret Standard Deviation

Empirical Method to Interpret Standard Deviation

The empirical rule, also known as the three-sigma rule, allows a statistician to interpret the standard deviation in a normally distributed dataset. The rule states that 68% of the data lies within one standard deviation from the mean, 95% lies within two standard deviations from the mean, and 99.7% lies within three standard deviations from the mean. Additionally, this rule is also called the 68-95-99.7 rule.
This rule is used widely in statistics to calculate the proportion of data values...

Regression Toward the Mean

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...

Correlation of Experimental Data

Correlation of Experimental Data

Dimensional analysis simplifies complex physical problems and guides experimental investigations, but it does not provide complete solutions. It identifies the dimensionless groups that influence a phenomenon, but experimental data is needed to establish the specific relationships and validate theoretical predictions.
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity, and...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

How to improve scientific peer review: Four schools of thought.

Learned publishing : journal of the Association of Learned and Professional Society Publishers·2024

Same author

Recommendations for accelerating open preprint peer review to improve the culture of science.

PLoS biology·2024

Same author

A guide for social science journal editors on easing into open science.

Research integrity and peer review·2024

Same author

The experiences of COVID-19 preprint authors: a survey of researchers about publishing and receiving feedback on their work during the pandemic.

PeerJ·2023

Same author

Innovations in peer review in scholarly publishing: a meta-summary.

Wellcome open research·2023

Same author

Effects of municipal boundaries measured by combining urban scaling and spatial interaction.

Journal of the Royal Society, Interface·2023

Search research articles

Related Experiment Video

Updated: Jun 1, 2026

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

Towards a new crown indicator: an empirical analysis.

Ludo Waltman¹, Nees Jan van Eck, Thed N van Leeuwen

¹Centre for Science and Technology Studies, Leiden University, Leiden, The Netherlands.

|June 10, 2011

Summary

We compared two methods for normalizing research citation counts. Differences were minimal for large groups like countries but larger for smaller units like research groups, especially concerning recent publications.

Related Experiment Videos

Last Updated: Jun 1, 2026

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

Area of Science:

Bibliometrics and scientometrics
Research evaluation
Scientific publishing

Background:

Citation-based indicators are crucial for research performance evaluation.
Normalization is necessary to account for variations in citation practices across fields and time.
Current and novel normalization methods are being explored for improved accuracy.

Purpose of the Study:

To empirically compare two distinct normalization mechanisms for citation-based research performance indicators.
To assess the impact of these mechanisms at different aggregation levels (institutional, national, group, journal).
To specifically examine the handling of recent publications with typically low citation counts.

Main Methods:

Comparative analysis of two normalization techniques applied to citation data.
Evaluation across multiple aggregation levels: countries, institutions, research groups, and journals.
Focus on the treatment of publications from recent years.

Main Results:

Normalization mechanisms show minimal differences at high aggregation levels (e.g., countries, large institutions).
Differences become more pronounced at lower aggregation levels (e.g., research groups, journals).
The handling of recent publications, characterized by low citation counts, requires careful consideration.

Conclusions:

The choice of normalization mechanism has a limited impact on broad-scale research assessments.
Discrepancies emerge at finer granularities, necessitating careful selection for specific evaluation contexts.
Further attention is needed for robustly evaluating recent scholarly output.