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

Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
Types of Selection01:46

Types of Selection

Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
Dose-Response Relationship: Selectivity and Specificity01:25

Dose-Response Relationship: Selectivity and Specificity

Drugs exert their therapeutic effects by interacting with receptors, enzymes, or ion channels that are present throughout the human body. The strength and duration of the interaction between a drug and its target receptor are characterized by the selectivity and specificity of the drug. Selectivity refers to a drug's strong preference for its intended target over other targets. For instance, isoprenaline, a non-selective β-adrenergic agonist, interacts with both β1- and β2-adrenergic receptors...
Structuralism01:26

Structuralism

Structuralism, an early psychological theory developed by Wilhelm Wundt and his student Edward Bradford Titchener, sought to dissect the human mind into its most fundamental components. Wundt's groundbreaking work in his laboratory set the stage for Titchener to define structuralism's goal as cataloging the "atoms" of the mind—sensations, images, and feelings—akin to how chemists identify elements of matter.
Titchener's approach to structuralism was unique. He employed introspection, a method...

You might also read

Related Articles

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

Sort by
Same author

From barriers to benefits: A personalized sleep intervention enhances sleep duration and emotional health in chronic short sleepers.

British journal of psychology (London, England : 1953)·2026
Same author

semfindr: An R Package for Identifying Influential Cases in Structural Equation Modeling.

Multivariate behavioral research·2026
Same author

How plausible is my model? Assessing model plausibility of structural equation models using Bayesian posterior probabilities (BPP).

Behavior research methods·2026
Same author

Forming bootstrap confidence intervals and examining bootstrap distributions of standardized coefficients in structural equation modelling: A simplified workflow using the R package semboottools.

Behavior research methods·2026
Same author

High spatial frequency signals drive emotion-related perceptual decision making under emotion-guided attention.

Emotion (Washington, D.C.)·2025
Same author

A systematic review and meta-analysis of group-based trajectory modeling of sleep duration across age groups and in relation to health outcomes.

Sleep·2025
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

Exploring the Use of Multiple Imputation for Handling Missing Covariates in Meta-Regression with Dependent Effect Sizes.

Multivariate behavioral research·2026
See all related articles

Related Experiment Video

Updated: Jun 3, 2026

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

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

Published on: September 27, 2019

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

Rong Wei Sun1, Florbela Chang2, Wendie Yang2

  • 1School of Arts and Humanities, Tung Wah College, Hong Kong SAR, China.

Multivariate Behavioral Research
|June 2, 2026
PubMed
Summary
This summary is machine-generated.

Standardizing variables in psychology can be misleading. A new R package, betaselectr, offers accurate standardized coefficients and confidence intervals for structural equation modeling and regression analyses.

Keywords:
Standardizationmoderationstructural equation modeling

More Related Videos

How Virtual Celebrity Characteristics Drive Purchase Intention: Testing the Stimulus-Organism-Response Framework with Structural Equation Modeling
07:35

How Virtual Celebrity Characteristics Drive Purchase Intention: Testing the Stimulus-Organism-Response Framework with Structural Equation Modeling

Published on: March 3, 2026

Related Experiment Videos

Last Updated: Jun 3, 2026

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

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

Published on: September 27, 2019

How Virtual Celebrity Characteristics Drive Purchase Intention: Testing the Stimulus-Organism-Response Framework with Structural Equation Modeling
07:35

How Virtual Celebrity Characteristics Drive Purchase Intention: Testing the Stimulus-Organism-Response Framework with Structural Equation Modeling

Published on: March 3, 2026

Area of Science:

  • Psychology
  • Statistics
  • Data Analysis

Background:

  • Standardization enhances result interpretability in psychological research.
  • Commonly used structural equation modeling (SEM) programs often standardize results.
  • Existing standardization methods can be misleading in specific analytical situations.

Purpose of the Study:

  • To address limitations in current standardization practices in SEM and multiple regression.
  • To provide accurate standardized coefficients, standard errors, and confidence intervals.
  • To develop a tool for researchers to properly handle standardization in complex models.

Main Methods:

  • Development of the R package `betaselectr`.
  • Implementation of methods to correctly standardize coefficients in three problematic scenarios: dummy variables, moderation product terms, and variables with inherent meaningful units.
  • Inclusion of confidence interval calculations that account for sampling error in standard deviations.

Main Results:

  • The `betaselectr` package correctly computes standardized coefficients in situations where standard SEM software fails.
  • It provides unbiased standard errors and confidence intervals for standardized results.
  • The package is applicable to both structural equation modeling and multiple regression.

Conclusions:

  • Proper standardization is crucial for accurate interpretation of regression and SEM results.
  • `betaselectr` offers a reliable solution for researchers facing common standardization challenges.
  • The package improves the quality and trustworthiness of standardized statistical findings in psychological science.