Reliability Validity
Reliability Validity - Related Videos
01:29
Reliability and Validity
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2020
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. Unfortunately, being consistent in measurement does not necessarily mean that you have measured something correctly. To illustrate this concept, consider a kitchen...
05:13
Reliability in Psychology Experiments
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2023
Source: Laboratories of Gary Lewandowski, Dave Strohmetz, and Natalie Ciarocco—Monmouth University In order to study something scientifically, a researcher needs to determine a way to quantify it. However, psychological constructs can be challenging to measure and quantify. This video examines reliability in the context of content analysis. A recent study in the journal Pediatrics reported that 4-year-olds who watched a fast-paced cartoon had worse performance on cognitive tasks, such as...
01:25
Distribution Reliability and Automation
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2024
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
11:33
V3 Stain-free Workflow for a Practical, Convenient, and Reliable Total Protein Loading Control in Western Blotting
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Cited by 53 •
2013
V3 workflow is a western blot procedure using stain-free gels. The stain-free technology allows researchers to visualize protein separation quality, to verify the transfer efficiency, and most importantly, to validate the change in the protein of interest using total protein quantification as a reliable loading control.
09:15
Reliable and High Efficiency Extraction of Kidney Immune Cells
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Cited by 12 •
2016
Techniques that are reliable and efficient for the isolation of kidney immune cells are needed for downstream applications. This requires surface antibody labeling of a small number of kidney immune cells. Herein, we describe a concise method for isolation of kidney immune cells that seemingly achieves this goal.
FAQs
A measure may show stable scores or signals across repeated assessments yet fail to represent the intended construct. Consistency limits random measurement error, but it does not establish that a task, recording, or imaging measure captures the relevant cognitive or neural phenomenon. Researchers therefore examine reliability alongside validity so reproducible but conceptually misaligned findings are not treated as genuine biology.
These approaches examine different parts of measurement performance. Test-retest consistency asks whether results remain similar across assessments, internal agreement examines whether items within an assessment provide coherent information, and rater agreement evaluates whether different observers reach similar judgments. Selecting among them depends on whether variation may arise across time, among items, or between evaluators.
Validity is examined through expected relationships rather than direct access to the construct itself. Researchers compare a measure with theoretical predictions, related measures, or relevant outcomes, then assess whether the observed pattern supports the intended interpretation. This approach helps determine whether behavioral, cognitive, electrophysiological, or neuroimaging results correspond to the phenomenon they are supposed to represent.
Observed differences become more interpretable when the measurement is both consistent and appropriately linked to the intended construct. Weak reliability can make genuine differences difficult to detect because results vary through measurement error, whereas weak validity can make consistent differences reflect an incorrectly defined construct. Considering both principles strengthens conclusions about biological or behavioral phenomena.
Begin by identifying the construct and the type of measurement involved, such as a behavioral task, cognitive assessment, electrophysiological recording, or neuroimaging measure. Then choose a suitable reliability assessment, such as test-retest consistency, internal agreement, or rater agreement, and examine validity through theoretical expectations, related measures, or relevant outcomes.
The principles apply across several measurement classes, including behavioral tasks, cognitive assessments, electrophysiological recordings, and neuroimaging measures. For each, researchers must determine whether results are sufficiently consistent and whether they support the intended interpretation. Applying the same quality framework across these modalities improves confidence when linking measured differences to neural or behavioral phenomena.
Uneven evidence calls for cautious interpretation rather than treating every observed pattern as equally informative. Strong consistency supports confidence that results are reproducible, while validity evidence supports confidence in their meaning. If either is limited, conclusions about neural or behavioral differences should acknowledge that measurement error or an unsuitable construct may influence the findings.