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

One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

6.8K
One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
6.8K
One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

4.3K
One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
4.3K
Nominal Level of Measurement00:56

Nominal Level of Measurement

41.0K
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...
41.0K
Sampling Plans01:23

Sampling Plans

1.1K
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
1.1K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

314
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...
314
Sample Size Calculation01:19

Sample Size Calculation

6.8K
Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
6.8K

You might also read

Related Articles

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

Sort by
Same author

Early Screening for Decoding- and Language-Related Reading Difficulties in First and Third Grades.

Assessment for effective intervention : official journal of the Council for Educational Diagnostic Services·2026
Same author

Adolescent Sexting in Romantic Relationships and Daily Positive and Negative Affect Dynamics: A Dyadic Intensive Longitudinal Study.

Computers in human behavior·2026
Same author

A primer on intensive longitudinal psychometrics.

Behavior research methods·2026
Same author

Dynamic measurement invariance cutoffs for longitudinal and dyadic data.

Behavior research methods·2026
Same author

Evidence-based practice attitude scale for Latinx mental health professionals: a novel application of confirmatory factor analysis.

Implementation science communications·2026
Same author

Practical Implications of Sum Scores Being Psychometrics' Greatest Accomplishment.

Psychometrika·2026
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

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

Multivariate behavioral research·2026
See all related articles

Related Experiment Video

Updated: Mar 9, 2026

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

4.5K

Accommodating Small Sample Sizes in Three-Level Models When the Third Level is Incidental.

Daniel McNeish1, Kathryn R Wentzel2

  • 1a Department of Methodology and Statistics , Utrecht University.

Multivariate Behavioral Research
|December 25, 2016
PubMed
Summary
This summary is machine-generated.

Modeling three-level clustered data with small sample sizes is challenging. This study evaluates seven methods for three-level models with small samples at the highest level, offering guidance for researchers.

Keywords:
HLMThree-levelmixed-effects modelmultilevel modelsmall sample

More Related Videos

The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition
05:15

The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

Published on: February 19, 2018

11.4K
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

9.9K

Related Experiment Videos

Last Updated: Mar 9, 2026

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

4.5K
The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition
05:15

The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

Published on: February 19, 2018

11.4K
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

9.9K

Area of Science:

  • Statistics
  • Educational Psychology

Background:

  • Small sample sizes pose challenges in statistical modeling, particularly for clustered data.
  • Existing guidance primarily addresses two-level models, leaving a gap in three-level data analysis.
  • Three-level models are particularly susceptible to small sample issues at the highest hierarchical level.

Purpose of the Study:

  • To investigate the performance of various statistical methods for three-level data when the highest level sample size is small.
  • To provide practical recommendations for researchers dealing with incidentally nested data structures.
  • To highlight the impact of method selection on analytical outcomes in three-level modeling.

Main Methods:

  • A simulation study was conducted to assess seven different statistical methods.
  • The focus was on three-level data structures with a small number of units at the third level.
  • An educational psychology dataset was used as a motivating example.

Main Results:

  • The performance of the seven evaluated methods varied significantly under small sample conditions at the third level.
  • The choice of statistical method demonstrably influenced the results and interpretations.
  • No single method consistently outperformed others across all simulated scenarios.

Conclusions:

  • Researchers must carefully consider the chosen statistical method when modeling three-level data with small higher-level samples.
  • The findings underscore the need for specific methodological guidance tailored to three-level hierarchical data.
  • Further research may be warranted to develop and validate robust methods for such complex data structures.