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 Experiment Videos

Accuracy in parameter estimation for a general class of effect sizes: A sequential approach.

Ken Kelley1, Francis Bilson Darku2, Bhargab Chattopadhyay2

  • 1Department of Information Technology, Analytics, and Operations, Mendoza College of Business, University of Notre Dame.

Psychological Methods
|April 7, 2017
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

A sequential approach for noninferiority or equivalence of a linear contrast under cost constraints.

Psychological methods·2023
Same author

Sample size planning for replication studies: The devil is in the design.

Psychological methods·2022
Same author

Improved inference in mediation analysis: Introducing the model-based constrained optimization procedure.

Psychological methods·2020
Same author

Indirect Effects in Sequential Mediation Models: Evaluating Methods for Hypothesis Testing and Confidence Interval Formation.

Multivariate behavioral research·2019
Same author

Common language effect size for correlations.

The Journal of general psychology·2019
Same author

Sequential accuracy in parameter estimation for population correlation coefficients.

Psychological methods·2019

Sequential estimation offers a flexible approach to statistical inference. This method allows for adaptive sample sizes, enabling the construction of narrow confidence intervals for effect sizes without prior parameter assumptions.

Area of Science:

  • Statistics
  • Statistical Theory
  • Methodology

Background:

  • Sequential estimation is a recognized statistical inference approach.
  • It involves adaptive sample sizes determined by stopping rules based on study outcomes.
  • Traditional methods often require pre-specified, unknown population parameters.

Purpose of the Study:

  • To develop a general theory for sequential estimation procedures.
  • To construct narrow confidence intervals for a general class of effect sizes.
  • To achieve a specified confidence level and an upper bound on interval width.

Main Methods:

  • Development of a general theory for sequential estimation.
  • Application to constructing confidence intervals for effect sizes.

Related Experiment Videos

  • Methodology is distribution-free, avoiding assumptions about population distributions.

    • Main Results:

    • A novel sequential estimation procedure is presented.
    • The procedure allows for confidence interval construction without requiring pre-specified population parameters.
    • The approach is distribution-free, enhancing generalizability.

    Conclusions:

    • The developed theory provides a flexible and widely applicable method for sequential estimation.
    • This approach offers advantages over traditional sample size planning, especially for effect size estimation.
    • The distribution-free nature ensures robustness across various populations.