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Related Concept Videos

Data Validation01:03

Data Validation

Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
Data Validation01:15

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Reliability and Validity01:29

Reliability and Validity

Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.

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Using UnGraph to extract data from image files: verification of reliability and validity.

William R Shadish1, Isabel C C Brasil2, David A Illingworth2

  • 1University of California Merced, P.O. Box 2039, 95344, Merced, CA. wshadish@ucmerced.edu.

Behavior Research Methods
|February 3, 2009
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Summary

Researchers can confidently extract data from graphs in single-case designs. Data extraction using the UnGraph program proved highly reliable and valid, ensuring extracted data closely matches original numerical descriptions.

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Area of Science:

  • Behavioral Science
  • Research Methodology

Background:

  • Data extraction from graphs is crucial for research synthesis.
  • Single-case designs frequently present results graphically.

Purpose of the Study:

  • To assess the reliability and validity of data extraction from single-case design graphs.
  • To determine if coders extract similar data and if it matches original numerical data.

Main Methods:

  • Utilized 91 graphs from single-case designs.
  • Employed the UnGraph computer program for data extraction by paired coders.
  • Assessed inter-coder reliability and compared extracted data to author-provided numerical descriptions.

Main Results:

  • Extraction demonstrated high reliability, with coders extracting identical numbers and nearly identical values.
  • Extraction showed high validity, with extracted data means correlating almost perfectly with reported means.
  • Few discrepancies were found in individual cases.

Conclusions:

  • Data extraction from single-case design graphs using UnGraph is reliable and valid.
  • Researchers can confidently use extracted graph data, as it closely mirrors original numerical data.