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

Naturalistic Observations02:30

Naturalistic Observations

17.8K
If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
17.8K
Observational Learning01:12

Observational Learning

1.1K
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
1.1K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

308
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...
308
Data Collection by Observations01:08

Data Collection by Observations

15.4K
Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
15.4K
Systematic Sampling Method01:17

Systematic Sampling Method

13.6K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures 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.
Systematic sampling is one of the simplest methods...
13.6K
Observational Studies01:11

Observational Studies

11.2K
Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...
11.2K

You might also read

Related Articles

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

Sort by
Same author

A tutorial for software options to aid in assessing functional relations in single-case experimental designs.

Behavior research methods·2026
Same author

Videoconferencing Cognitive Behavioral Therapy for Panic Disorder in an Emergency Room in Mexico: A Multiple Baseline Design.

Journal of clinical psychology in medical settings·2026
Same author

Application of association rules to ball possessions in professional men's football.

Frontiers in psychology·2025
Same author

Goal and shot prediction in ball possessions in FIFA Women's World Cup 2023: a machine learning approach.

Frontiers in psychology·2025
Same author

Editorial: Advances in sport science: latest findings and new scientific proposals, volume II.

Frontiers in psychology·2025
Same author

Technical-tactical evolution of women's football: a comparative analysis of ball possessions in the FIFA Women's World Cup France 2019 and Australia & New Zealand 2023.

Biology of sport·2025

Related Experiment Video

Updated: Feb 27, 2026

A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents
08:38

A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents

Published on: November 21, 2019

8.3K

Simulation Theory Applied to Direct Systematic Observation.

Rumen Manolov1, José L Losada1

  • 1Department of Social Psychology and Quantitative Psychology, Faculty of Psychology, University of BarcelonaBarcelona, Spain.

Frontiers in Psychology
|June 24, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces an R Shiny application to help researchers choose the best observational recording methods, like momentary time sampling, for accurate behavior estimation. It aids in minimizing bias and maximizing efficiency in observational studies.

Keywords:
alternating renewal processdirect observationinterval recordingprevalencetime sampling

More Related Videos

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

10.4K
Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation
09:49

Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation

Published on: November 18, 2015

12.9K

Related Experiment Videos

Last Updated: Feb 27, 2026

A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents
08:38

A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents

Published on: November 21, 2019

8.3K
Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

10.4K
Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation
09:49

Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation

Published on: November 18, 2015

12.9K

Area of Science:

  • Behavioral Science
  • Research Methodology
  • Data Analysis Software

Background:

  • Observational studies require careful planning, including selecting appropriate data collection methods.
  • Discontinuous recording methods like momentary time sampling, partial, and whole interval recording are common but require informed selection.
  • Existing tools may not adequately support researchers in optimizing these choices for accuracy and efficiency.

Purpose of the Study:

  • To develop an online software application using R and Shiny to aid in selecting observational recording procedures.
  • To provide graphical representations based on simulations to guide researchers in choosing optimal discontinuous recording methods.
  • To assist in identifying conditions that minimize bias and maximize efficiency in behavioral prevalence estimation.

Main Methods:

  • Development of an R Shiny application utilizing simulations based on the alternating renewal process.
  • Implementation of the alternating renewal process model via the ARPobservation R package.
  • Focus on observational recording procedures: momentary time sampling, partial interval recording, and whole interval recording.

Main Results:

  • The application provides graphical tools to visualize the performance of different discontinuous recording methods.
  • It helps identify optimal interval lengths and behavior durations for unbiased and efficient prevalence estimation.
  • The software facilitates informed decision-making for researchers planning observational studies.

Conclusions:

  • The developed R Shiny application is a valuable tool for students and researchers in observational methodology.
  • It enhances the understanding and application of discontinuous recording techniques for more accurate behavioral research.
  • The tool supports evidence-based selection of observational recording procedures to improve data quality and research efficiency.