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Reliability and Validity

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.

Statistical Analysis: Overview

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...

Kendall's Coefficient of Concordance

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...

Surveys

Surveys

Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.

Accuracy and Errors in Hypothesis Testing

Accuracy and Errors in Hypothesis Testing

Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5% chance...

Group Design

Group Design

The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to...

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Related Experiment Video

Updated: Jun 23, 2026

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

Published on: August 29, 2025

Evaluating agreement: conducting a reliability study.

Paul J Karanicolas¹, Mohit Bhandari, Hans Kreder

¹Department of Clinical Epidemiology and Biostatistics, McMaster University, 293 Wellington Street North, Suite 110, Hamilton, ON L8L 2X2, Canada.

The Journal of Bone and Joint Surgery. American Volume

|May 5, 2009

Summary

Reliability studies in orthopaedics assess measurement consistency. Ensuring patient, rater, and administration similarity to clinical contexts is crucial for valid results.

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A Protocol of Manual Tests to Measure Sensation and Pain in Humans

A Protocol of Manual Tests to Measure Sensation and Pain in Humans

Published on: December 19, 2016

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Last Updated: Jun 23, 2026

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

Published on: August 29, 2025

A Protocol of Manual Tests to Measure Sensation and Pain in Humans

A Protocol of Manual Tests to Measure Sensation and Pain in Humans

Published on: December 19, 2016

Area of Science:

Orthopaedic research
Biostatistics
Measurement science

Background:

Reliability studies are increasingly prevalent in orthopaedic literature.
These studies evaluate measurement error and differences between subjects.
Consistent and reproducible measurements are vital for clinical and research tools.

Purpose of the Study:

To identify common elements of reliability studies.
To suggest features enhancing reader confidence in study results.
To provide guidance for appraising and developing reliability studies.

Main Methods:

Review of common aspects in orthopaedic reliability studies.
Introduction to frequently used statistical measures for reliability.
Discussion on the importance of context similarity (patients, raters, administration).

Main Results:

Relevance of reliability studies hinges on context similarity.
Statistical measures for assessing reliability are introduced.
An approach for sample-size estimation in reliability studies is suggested.

Conclusions:

Critical appraisal of reliability studies requires understanding context relevance.
Developing robust reliability studies necessitates careful consideration of methodology.
This review aids researchers in conducting and interpreting reliability studies.