Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Ordinal Level of Measurement00:55

Ordinal Level of Measurement

32.0K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
32.0K
Ranks01:02

Ranks

462
Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
462
Stereotype Content Model02:16

Stereotype Content Model

15.4K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
15.4K
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

483
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
483
Nominal Level of Measurement00:56

Nominal Level of Measurement

37.0K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. Not every statistical operation can be used with every set of data. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
The data that cannot be measured but can be grouped into categories fall under the nominal level of measurement. Data that is measured using a nominal...
37.0K
Stereotype Threat and Self-fulfilling Prophecies02:09

Stereotype Threat and Self-fulfilling Prophecies

41.9K
When we hold a stereotype about a person, we have expectations that he or she will fulfill that stereotype. A self-fulfilling prophecy is an expectation held by a person that alters his or her behavior in a way that tends to make it true. When we hold stereotypes about a person, we tend to treat the person according to our expectations. This treatment can influence the person to act according to our stereotypic expectations, thus confirming our stereotypic beliefs. Research by Rosenthal and...
41.9K

You might also read

Related Articles

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

Sort by
Same author

Identifying Weekly Physical and Physiological Profiles in Professional Basketball Using Heart Rate Variability and Training Load Clustering.

Research quarterly for exercise and sport·2026
Same author

Resistance to doxorubicin-induced proteinuria and proteolytic activation of ENaC in 129S2/SvPas mice.

Physiological reports·2025
Same author

Fluoroscopy-guided celiac plexus block - Trans-Aortic approach.

Interventional pain medicine·2025
Same author

A chickpea MAGIC population to dissect the genetics of complex traits.

The plant genome·2025
Same author

Improving YOLO-based breast mass detection with transfer learning pretraining on the OPTIMAM Mammography Image Database.

Computers in biology and medicine·2025
Same author

A new multi-object tracking pipeline based on computer vision techniques for mussel farms.

Journal of the Royal Society of New Zealand·2024
Same journal

Bias of Odds Ratio Estimate in Fisher's Exact Test.

International journal of methods in psychiatric research·2026
Same journal

Estimating the Joint Probability Density for Index Construction: Some Simplifications Using the TWEAK as Example.

International journal of methods in psychiatric research·2026
Same journal

Group, Subgroup and Person-Specific Longitudinal Associations Between Physical Activity and Affect in Individuals With and Without Depressive and Anxiety Disorders.

International journal of methods in psychiatric research·2026
Same journal

Interviewer and Respondent Sociodemographic Characteristics, Rapport, and Their Joint Impact on Data Quality in the NESDA Study.

International journal of methods in psychiatric research·2026
Same journal

Validation of the Arabic Version of the Eight-Item Difficulties in Emotion Regulation Scale-8 (DERS-8) in Egypt.

International journal of methods in psychiatric research·2026
Same journal

Explainable Temporal Deep Learning for EEG-Based Depression Detection Using Resting-State Brain Dynamics.

International journal of methods in psychiatric research·2026
See all related articles

Related Experiment Video

Updated: Jan 18, 2026

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
08:13

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

6.8K

A method for ordinal outcomes: The ordered stereotype model.

Daniel Fernandez1, Ivy Liu2, Roy Costilla3

  • 1Research and Development Unit, Parc Sanitari Sant Joan de Déu, Fundació Sant Joan de Déu, CIBERSAM, Barcelona, Spain.

International Journal of Methods in Psychiatric Research
|October 1, 2019
PubMed
Summary
This summary is machine-generated.

The ordered stereotype model offers advantages for analyzing ordinal data in psychological and psychiatric research. This study compares its performance against common models, highlighting its utility for ordinal outcomes.

Keywords:
goodness-of-fitordered stereotype modelordinal dataproportional odds model

More Related Videos

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.9K
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

Related Experiment Videos

Last Updated: Jan 18, 2026

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
08:13

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

6.8K
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.9K
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

Area of Science:

  • Statistics
  • Psychometrics
  • Psychiatry

Background:

  • Ordinal variables are frequently used in psychological and psychiatric studies.
  • Traditional continuous models may introduce bias (e.g., floor/ceiling effects) when applied to ordinal data.
  • The ordered stereotype model is specifically designed for ordinal outcomes, offering a potentially more accurate analysis.

Purpose of the Study:

  • To introduce and evaluate the ordered stereotype model for analyzing ordinal data.
  • To compare the performance of the ordered stereotype model against more common models like linear regression and proportional odds models.
  • To assess the impact of treating ordinal responses as continuous.

Main Methods:

  • A simulation study was conducted comparing the ordered stereotype model with proportional odds and linear regression models.
  • The study varied the number of ordinal categories (3, 4, 5) and sample sizes (100, 500, 1000).
  • The trend odds model was also included in the analysis.

Main Results:

  • In a real-life example, the ordered stereotype, proportional odds, and trend odds models yielded similar conclusions regarding covariate significance.
  • The simulation study indicated that the ordered stereotype model's performance varied across different scenarios.
  • The study highlighted potential issues with treating ordinal responses as continuous.

Conclusions:

  • The ordered stereotype model is applicable to various psychiatric research areas involving ordinal outcomes.
  • A key advantage is its ability to handle ordinal data without assuming equally spaced intervals between categories.
  • This model provides a valuable alternative for analyzing ordinal data, potentially improving accuracy and avoiding biases inherent in continuous data approaches.