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Nominal Level of Measurement00:56

Nominal Level of Measurement

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. Not every statistical operation can be used with every set of data. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
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Establishing a Competing Risk Regression Nomogram Model for Survival Data
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Published on: October 23, 2020

Obtaining representative nominal groups.

Matthew R Kelley1, Daniel B Wright

  • 1Department of Psychology, Lake Forest College, Lake Forest, Illinois, USA. kelley@lakeforest.edu

Behavior Research Methods
|February 18, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces a new, flexible method for creating representative nominal groups by sampling thousands of combinations. This approach improves upon existing techniques for group effectiveness research.

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Area of Science:

  • Social Psychology
  • Organizational Behavior
  • Research Methodology

Background:

  • Group effectiveness research often compares performance to nominal groups.
  • Traditional nominal group formation methods are inadequate and inflexible.
  • Existing advanced methods (e.g., Wright, 2007) present usability challenges for complex research designs.

Purpose of the Study:

  • To introduce and validate a novel procedure for constructing representative nominal groups.
  • To offer a more flexible and accessible method for forming nominal groups in research.
  • To enhance the accuracy of group effectiveness studies by improving nominal group comparisons.

Main Methods:

  • A new algorithm samples thousands of potential nominal group combinations.
  • Calculates key sample characteristics (mean, variance, distribution) for all sampled sets.
  • Identifies and returns the nominal group set most representative of all possibilities, prioritizing similarity in mean and variance.

Main Results:

  • The new procedure effectively samples and identifies representative nominal groups.
  • Simulations confirm the method's ability to find sets with means and variances similar to population statistics.
  • The algorithm is implemented in user-friendly C++ and R formats for broad accessibility.

Conclusions:

  • The proposed sampling procedure offers a superior and more flexible alternative for forming nominal groups.
  • This method enhances the reliability of research comparing group performance to individual scores.
  • Freely available C++ and R implementations facilitate widespread adoption in group effectiveness research.