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Related Concept Videos

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.
Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures from...
Confidence Coefficient01:24

Confidence Coefficient

The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under both the...
Kendall's Coefficient of Concordance01:20

Kendall's Coefficient of Concordance

Kendall's Coefficient of Concordance (W), also known as Kendall's W, is a non-parametric statistical measure used to assess the agreement or concordance between multiple raters or judges when they rank a set of items. It is often used when you have ordinal data (ranks) and you want to see if there is consistency or consensus among the raters. It is widely applied in research areas such as psychology, medicine, and social sciences, where multiple judges are asked to rank or rate subjects or...
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...

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Related Experiment Video

Updated: Jun 10, 2026

Digital PCR-based Competitive Index for High-throughput Analysis of Fitness in Salmonella
07:11

Digital PCR-based Competitive Index for High-throughput Analysis of Fitness in Salmonella

Published on: May 13, 2019

A reliability analysis of the revised competitiveness index.

Paul B Harris1, John M Houston

  • 1Department of Psychology, Rollins College, 1000 Holt Ave., Winter Park, FL 32789, USA. pharris@rollins.edu

Psychological Reports
|August 18, 2010
PubMed
Summary

The Revised Competitiveness Index demonstrates high reliability and a stable factor structure, confirming it measures competitiveness as a stable trait. This validated psychological measure is suitable for trait assessment.

Related Experiment Videos

Last Updated: Jun 10, 2026

Digital PCR-based Competitive Index for High-throughput Analysis of Fitness in Salmonella
07:11

Digital PCR-based Competitive Index for High-throughput Analysis of Fitness in Salmonella

Published on: May 13, 2019

Area of Science:

  • Psychological assessment
  • Personality psychology
  • Social psychology

Background:

  • The Revised Competitiveness Index (RCI) is a key measure for assessing individual competitiveness.
  • Understanding the psychometric properties of the RCI is crucial for its accurate application in research and practice.
  • Previous research has established the RCI's utility, but ongoing validation is essential.

Purpose of the Study:

  • To evaluate the psychometric properties of the Revised Competitiveness Index.
  • To determine the test-retest reliability and inter-item reliability of the RCI.
  • To analyze the factor structure of the RCI in a sample of undergraduate students.

Main Methods:

  • The study involved 280 undergraduate students (200 women, 80 men) aged 18–28 years.
  • Test-retest reliability was assessed over a specified period.
  • Inter-item reliability and factor structure were analyzed using statistical methods.

Main Results:

  • The Revised Competitiveness Index exhibited high test-retest reliability.
  • High inter-item reliability was found, indicating consistency among scale items.
  • A stable factor structure was confirmed, supporting the measure's construct validity.

Conclusions:

  • The Revised Competitiveness Index is a reliable and valid instrument for measuring competitiveness.
  • Findings support the conceptualization of competitiveness as a stable personality trait.
  • The RCI is appropriate for research and clinical settings requiring assessment of competitive traits.