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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.

Data Validation

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...

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Related Experiment Video

Updated: Jul 20, 2025

Development of a Virtual Reality Assessment of Everyday Living Skills

Development of a Virtual Reality Assessment of Everyday Living Skills

Published on: April 23, 2014

Validity evidence for a virtual multiple mini interview at a pharmacy program.

Sarah Hammond¹, Jacqueline E McLaughlin², Wendy C Cox^3,4

¹School of Social Work, UNC Chapel Hill, Chapel Hill, NC, USA.

BMC Medical Education

|August 3, 2023

Summary

This summary is machine-generated.

Virtual multiple mini-interviews (vMMIs) show promise as a valid and reliable admissions tool, comparable to in-person interviews. Further research is needed to refine vMMI strategies for admissions and recruitment.

Keywords:

Assessment Multiple mini interview Pharmacy Remote Validity Virtual

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Area of Science:

Admissions Processes
Health Professions Education
Psychometrics

Background:

Many health professions schools now use virtual admissions interviews.
Research indicates virtual multiple mini-interviews (vMMIs) are feasible and affordable.
However, limited research exists on the validity of vMMIs.

Purpose of the Study:

To assess the validity and reliability of vMMIs.
To compare candidate performance in vMMIs versus in-person MMIs.

Main Methods:

Exploratory factor analysis and Pearson correlations analyzed vMMI data.
Cronbach alpha assessed internal consistency.
Independent t-tests and Cohen's d compared in-person and vMMI scores.

Main Results:

Factor analysis confirmed vMMI stations as single factors with high loadings.
vMMI stations explained most variance, showing high internal consistency.
Significant score differences with medium effect sizes were found for teamwork and integrity stations.

Conclusions:

vMMIs offer a valid and reliable alternative to traditional in-person MMIs.
Further investigation is required to understand rating differences and optimize vMMIs for institutional goals.