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

Systems for data analysis

J K Rao1, L F Callahan

  • 1Aging Studies Branch, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.

Rheumatic Diseases Clinics of North America
|May 1, 1995
PubMed
Summary
This summary is machine-generated.

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

Development and validation of the Flare-OA questionnaire for measuring flare in knee and hip osteoarthritis.

Osteoarthritis and cartilage·2022
Same author

The association between walking speed from short- and standard-distance tests with the risk of all-cause mortality among adults with radiographic knee osteoarthritis: data from three large United States cohort studies.

Osteoarthritis and cartilage·2020
Same author

Hip symptoms are associated with premature mortality: the Johnston County Osteoarthritis Project.

Osteoarthritis and cartilage·2020
Same author

Evaluation of the self-directed format of Walk With Ease in patients with systemic lupus erythematosus: the Walk-SLE Pilot Study.

Lupus·2019
Same author

A machine learning approach to knee osteoarthritis phenotyping: data from the FNIH Biomarkers Consortium.

Osteoarthritis and cartilage·2019
Same author

The impact of painful knee osteoarthritis on mortality: a community-based cohort study with over 24 years of follow-up.

Osteoarthritis and cartilage·2018
Same journal

Bridging the Divide in Global Rheumatology.

Rheumatic diseases clinics of North America·2026
Same journal

Foreword.

Rheumatic diseases clinics of North America·2026
Same journal

Pulmonary Complications of Biological Therapies in Inflammatory and Autoimmune Diseases.

Rheumatic diseases clinics of North America·2026
Same journal

Artificial Intelligence and Social Determinants of Health.

Rheumatic diseases clinics of North America·2026
Same journal

Updates in Ultrasound in Rheumatology.

Rheumatic diseases clinics of North America·2026
Same journal

Health Systems Strengthening to Promote Access to Care for Rheumatic and Musculoskeletal Diseases Globally.

Rheumatic diseases clinics of North America·2026
See all related articles

This review covers essential steps for data analysis systems, from planning to statistical analysis. It guides software choices for data entry and analysis, aiding researchers in managing and interpreting scientific data effectively.

Area of Science:

  • Data analysis systems
  • Scientific research methodology
  • Information management in science

Background:

  • Effective data analysis is crucial for scientific research.
  • A systematic approach is required for building robust data analysis systems.
  • Software selection significantly impacts data management and analysis efficiency.

Purpose of the Study:

  • To review the key stages involved in creating a data analysis system.
  • To discuss critical software selection considerations for data entry and analysis.
  • To provide resources for data management and statistical analysis software.

Main Methods:

  • Review of established data analysis system development steps.
  • Comparative analysis of software options for data entry and statistical analysis.

Related Experiment Videos

  • Compilation of a software directory in the appendix.

    • Main Results:

    • Identified core components of a data analysis system: study planning, form design, data entry, data verification, and statistical analysis.
    • Highlighted the importance of informed software choices for efficient data handling.
    • Provided a comprehensive list of relevant software tools.

    Conclusions:

    • Successful data analysis systems depend on meticulous planning and execution of each stage.
    • Appropriate software selection is fundamental for accurate and efficient data management and statistical analysis.
    • The article serves as a guide for researchers navigating the complexities of data analysis system implementation.