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

6.5K
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:
6.5K
One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

3.9K
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...
3.9K
Ordinal Level of Measurement00:55

Ordinal Level of Measurement

31.7K
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...
31.7K
Cluster Sampling Method01:20

Cluster Sampling Method

13.9K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
13.9K
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

507
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...
507
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

459
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...
459

You might also read

Related Articles

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

Sort by
Same author

A systematic review of interventions in the early course of bipolar disorder I or II: a report of the International Society for Bipolar Disorders Taskforce on early intervention.

International journal of bipolar disorders·2023
Same author

Diffusion imaging markers of bipolar versus general psychopathology risk in youth at-risk.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology·2018
Same author

Reward-related neural activity and structure predict future substance use in dysregulated youth.

Psychological medicine·2016
Same author

Predicting clinical outcome from reward circuitry function and white matter structure in behaviorally and emotionally dysregulated youth.

Molecular psychiatry·2016
Same author

Behavioral and emotional dysregulation trajectories marked by prefrontal-amygdala function in symptomatic youth.

Psychological medicine·2014
Same author

A COMPARISON OF THE McMASTER AND CIRCUMPLEX FAMILY ASSESSMENT INSTRUMENTS*.

Journal of marital and family therapy·2010
Same journal

Editorial: Intergenerational Benefits of Treating Maternal Depression: Recognizing Externalities.

Journal of the American Academy of Child and Adolescent Psychiatry·2026
Same journal

Preventing Child Abuse Through a Brief Parenting Intervention: 2.5 Year Outcomes From the Safer Kids Randomized Controlled Trial.

Journal of the American Academy of Child and Adolescent Psychiatry·2026
Same journal

Reducing Unnecessary Medical Screening for Pediatric Psychiatric Admissions in the Emergency Department: A Quality Improvement Approach to Implementing Choosing Wisely Recommendations.

Journal of the American Academy of Child and Adolescent Psychiatry·2026
Same journal

Aberrant Brain Topological Properties in Early-Onset and Adult-Onset Schizophrenia: Evidence from First-Episode Drug-Naïve and Medicated Groups.

Journal of the American Academy of Child and Adolescent Psychiatry·2026
Same journal

Data-Driven Profiles of Youth Executive Function and Their Longitudinal Associations With Externalizing Problems.

Journal of the American Academy of Child and Adolescent Psychiatry·2026
Same journal

Editorial: In the Service of Our Children.

Journal of the American Academy of Child and Adolescent Psychiatry·2026
See all related articles

Related Experiment Videos

Scaling structured interview data: a comparison of two methods.

J Cerel1, M A Fristad

  • 1Department of Psychology, The Ohio State University, Columbus 43210-1250, USA.

Journal of the American Academy of Child and Adolescent Psychiatry
|April 6, 2001
PubMed
Summary
This summary is machine-generated.

This study presents two dimensional scales, Behavior, Anxiety, Mood, and Other (BAMO) and DICA-SUM, derived from structured interviews for child psychopathology research. BAMO offers clearer insights into the number of diagnoses endorsed compared to DICA-SUM.

Related Experiment Videos

Area of Science:

  • Child and Adolescent Psychiatry
  • Psychometric Assessment
  • Clinical Psychology

Background:

  • Structured interviews are crucial for research but often yield only categorical diagnostic data.
  • Dimensional scales are needed to complement categorical data for a more nuanced understanding of psychopathology.
  • Existing structured interviews, like the Diagnostic Interview for Children and Adolescents-Revised (DICA-R), can be adapted to generate dimensional data.

Purpose of the Study:

  • To introduce and evaluate two novel dimensional scales, Behavior, Anxiety, Mood, and Other (BAMO) and DICA-SUM, derived from the DICA-R structured interview.
  • To compare the psychometric and pragmatic characteristics of the BAMO and DICA-SUM scales.
  • To explore the utility of dimensional scales in enhancing the interpretation of data from structured interviews in child psychopathology research.

Main Methods:

  • Data were collected from 570 children aged 5-18 years, including bereaved, depressed, and community samples.
  • The study involved an ongoing longitudinal childhood bereavement study conducted between 1987 and 1996.
  • Two dimensional scales, BAMO and DICA-SUM, were constructed from the Diagnostic Interview for Children and Adolescents-Revised (DICA-R).

Main Results:

  • Both BAMO and DICA-SUM demonstrated comparable discriminant and convergent validity with other child psychopathology measures.
  • The BAMO scale provided clearer information regarding the approximate number of endorsed diagnoses compared to DICA-SUM.
  • The findings suggest that dimensional scales derived from structured interviews can capture different aspects of psychopathology.

Conclusions:

  • Two methods for creating dimensional scales from structured interviews were identified and examined.
  • The use of dimensional scales, such as BAMO, can potentially improve the comparability of results across different research studies.
  • Dimensional data from structured interviews offer a more comprehensive assessment of child psychopathology than purely categorical data.