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

Case Studies01:22

Case Studies

There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it.
Multiple Regression01:25

Multiple Regression

Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Regression Analysis01:11

Regression Analysis

Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
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...
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
Microsoft Excel: Regression Analysis01:18

Microsoft Excel: Regression Analysis

Regression analysis in Microsoft Excel is a powerful statistical method for examining the relationship between a dependent variable and one or more independent variables. It's used extensively in fields such as economics, biology, and business to predict outcomes, understand relationships, and make data-driven decisions. The most common type is linear regression, which attempts to fit a straight line through the data points to model the relationship between variables.
To perform regression...

You might also read

Related Articles

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

Sort by
Same author

Navigating the help-seeking maze: Examining stigma, depression, and negative network orientation in college students' help-seeking attitudes.

The American journal of orthopsychiatry·2025
Same author

Social Connectedness and Negative Emotion Modulation: Social Media Use for Coping Among College Students During the COVID-19 Pandemic.

Emerging adulthood (Print)·2024
Same author

The role of personal identity as a resource for college students during COVID-19.

Journal of American college health : J of ACH·2023
Same author

Alcohol Use Severity among Hispanic Emerging Adults: Examining Intragroup Marginalization, Bicultural Self-Efficacy, and the Role of Gender within a Stress and Coping Framework.

Behavioral medicine (Washington, D.C.)·2021
Same author

Mental health among Latinx emerging adults: Examining the role of familial accusations of assimilation and ethnic identity.

Journal of clinical psychology·2021
Same author

Racial Justice Activist Burnout of Women of Color in the United States: Practical Tools for Counselor Intervention.

International journal for the advancement of counseling·2021
Same journal

Planned missingness in intensive longitudinal studies: Extensions and comparisons of multiform designs.

Behavior research methods·2026
Same journal

A validity-guided workflow for robust large language model research in psychology.

Behavior research methods·2026
Same journal

Are 7-point Likert scales preferable to 5-point scales in language research?

Behavior research methods·2026
Same journal

Generative psychometrics via AI-GENIE: Automatic item generation and validation with network-integrated evaluation.

Behavior research methods·2026
Same journal

Exploring psychological tradeoffs: Developing and demonstrating an R Shiny app for Pareto optimization.

Behavior research methods·2026
Same journal

The performance of Bayesian fit measures in detecting misspecified multilevel structural equation modeling.

Behavior research methods·2026
See all related articles

Related Experiment Video

Updated: Jun 3, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

Robust regression for single-case data analysis: how can it help?

Daniel F Brossart1, Richard I Parker, Linda G Castillo

  • 1Department of Educational Psychology, Texas A&M University, College Station, TX 77843-4225, USA. brossart@tamu.edu

Behavior Research Methods
|March 26, 2011
PubMed
Summary
This summary is machine-generated.

Outliers are common in single-case research data. Robust regression methods offer a more reliable analysis of treatment effectiveness compared to ordinary least squares (OLS) regression.

More Related Videos

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

Related Experiment Videos

Last Updated: Jun 3, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

Area of Science:

  • Behavioral Science
  • Psychology
  • Research Methodology

Background:

  • Single-case research designs are frequently used in psychology and behavioral science.
  • Outliers can significantly impact statistical analyses, potentially distorting findings.
  • The presence and effect of outliers in single-case data require careful examination.

Purpose of the Study:

  • To investigate the prevalence of outliers in published single-case research.
  • To compare the efficacy of ordinary least squares (OLS) regression with robust regression in detecting outliers and estimating effect sizes.
  • To assess the agreement of robust regression results with visual judgments of treatment effectiveness.

Main Methods:

  • Analysis of a convenience sample of published single-case research data.
  • Application of the Allison & Gorman (1993) procedure for single-case data analysis.
  • Comparison between ordinary least squares (OLS) regression and robust regression methods.

Main Results:

  • Outliers were found to be common in the analyzed single-case data.
  • Significant differences were observed in outlier detection and effect size estimation between OLS and robust regression.
  • Robust regression demonstrated greater agreement with visual assessments of treatment effectiveness.

Conclusions:

  • Outliers are a prevalent issue in single-case research, necessitating robust analytical approaches.
  • Robust regression provides a more accurate and reliable estimation of effect sizes in the presence of outliers.
  • Researchers and practitioners should consider robust methods for analyzing single-case data to ensure valid conclusions about treatment effectiveness.