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Related Concept Videos

Statistical Analysis: Overview01:11

Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
Diagnostic and Statistical Manual of Mental Disorders (DSM)01:27

Diagnostic and Statistical Manual of Mental Disorders (DSM)

The Diagnostic and Statistical Manual of Mental Disorders (DSM) serves as the primary classification system for mental health disorders, providing standardized diagnostic criteria for clinicians and researchers. First published by the American Psychiatric Association (APA) in 1952, the DSM has undergone several revisions to reflect evolving psychiatric understanding. The fifth edition, DSM-5, released in 2013, introduced key updates that expanded diagnostic categories and modified diagnostic...
Regression Toward the Mean01:52

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...
Chi-square Analysis02:46

Chi-square Analysis

The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
Biostatistics: Overview01:20

Biostatistics: Overview

Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
Self-Presentation: Self-Monitoring and Self-Handicapping02:05

Self-Presentation: Self-Monitoring and Self-Handicapping

People can go to great lengths to protect their self-image and present themselves in ways that they want others to see them. Sociologist Erving Goffman presented the idea that a person is like an actor on a stage. Calling his theory dramaturgy, Goffman believed that we use “impression management” to present ourselves to others as we hope to be perceived. Each situation is a new scene, and individuals perform different roles depending on who is present (Goffman, 1959). Think about the way you...

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Related Experiment Video

Updated: Jul 8, 2026

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
05:02

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

Using publication statistics for evaluation in academic psychiatry.

Robert G Maunder1

  • 1Department of Psychiatry, Mount Sinai Hospital and University of Toronto, Ontario. rmaunder@mtsinai.on.ca

Canadian Journal of Psychiatry. Revue Canadienne De Psychiatrie
|January 12, 2008
PubMed
Summary

Publication statistics vary by academic rank and discipline in psychiatry. Citation ratio offers a fair measure for evaluating faculty, minimizing bias across different fields.

Related Experiment Videos

Last Updated: Jul 8, 2026

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
05:02

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

Area of Science:

  • Academic Medicine
  • Psychiatry Research
  • Bibliometrics

Background:

  • The evaluation of university faculty relies heavily on publication statistics, but their validity remains unproven.
  • Assessing academic productivity in psychiatry requires understanding how publication metrics differ across ranks and specialties.

Purpose of the Study:

  • To investigate variations in publication statistics among psychiatric faculty based on academic rank.
  • To identify potential biases in publication metrics across different psychiatric disciplines.

Main Methods:

  • Analysis of the 10 most recent publications from psychiatric faculty at two medical schools.
  • Comparison of metrics including time to publish, 5-year impact, citation rate, and citation ratio.
  • Stratification by academic rank, institution, and comparison between neuroscience and clinical subspecialty leaders.

Main Results:

  • All publication statistics demonstrated significant associations with academic rank (P < 0.001) and institutional differences.
  • Basic scientists showed higher 5-year impact compared to clinical subspecialists (P = 0.04).
  • Citation ratio was comparable between basic scientists and clinical subspecialists, suggesting reduced disciplinary bias.

Conclusions:

  • Publication statistics are demonstrably different across academic ranks within psychiatry.
  • The citation ratio appears to be a robust metric, mitigating biases inherent in comparing diverse disciplines.
  • Publication statistics, particularly citation ratio, may offer valuable insights for evaluating psychiatric faculty performance.