Cohort Analysis
Cohort Analysis - Related Videos
08:53
Preparation of Single-cohort Colonies and Hormone Treatment of Worker Honeybees to Analyze Physiology Associated with Role and/or Endocrine System
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Cited by 5 •
2016
Here we describe our detailed protocol for the preparation of single-cohort honeybee colonies – a useful tool for analyzing the role-associated worker physiology. We also describe detailed protocols for treating workers with juvenile hormone and ecdysone to evaluate the involvement of these hormones in the regulation of worker behavior and/or physiology.
15:04
A Neuronal and Astrocyte Co-Culture Assay for High Content Analysis of Neurotoxicity
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Cited by 46 •
2009
This article describes a novel protocol and reagent set designed for sensitive measurement of neurotoxic effects of compounds and treatments on co-cultures of neurons and astrocytes using high content analysis. Results demonstrate that high content analysis represents an exciting novel technology for neurotoxicity assessment.
09:09
Design and Analysis of Temperature Preference Behavior and its Circadian Rhythm in Drosophila
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Cited by 22 •
2014
We recently identified a novel Drosophila circadian output, temperature preference rhythm (TPR), in which the preferred temperature in flies rises during the day and falls during the night. TPR is regulated independently from another circadian output, locomotor activity. Here we describe the design and analysis of TPR in Drosophila.
10:39
Automated Analysis of Intracellular Phenotypes of Salmonella Using ImageJ
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Cited by 3 •
2022
Salmonella invades and replicates inside intestinal epithelial cells both in Salmonella-specific vacuoles and free in the cytosol (hyper-replication). A high-throughput fluorescence microscopy-based protocol is described here to quantify the intracellular phenotypes of Salmonella by two complementary image analyses through ImageJ, reaching single-cell resolution and scoring.
10:58
Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
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Cited by 12 •
2011
Visual analytics (VA) is a new approach of analyzing data interactively. In this video, we discuss the data overload problem brought on by high-throughput biological experiments, and propose VA as a solution to such problem. The video demonstrates analysis within and between immunological datasets using a VA tool called Tableau.
FAQs
Age effects reflect changes associated with a person’s developmental stage, whereas period effects arise from events or conditions affecting people at a particular historical time. Cohort effects describe differences linked to shared experiences among groups formed during the same period or exposure. Comparing cohorts across ages and measurement points helps researchers examine these influences, although they can remain difficult to distinguish completely.
Repeated measurements show whether psychological outcomes remain stable or change as participants and cohorts progress through time. This approach can distinguish a temporary response to a historical event from a pattern associated with development or shared experience. In psychology, tracking cognition, mental health, attitudes, or behavior across measurements can reveal trends that a single assessment might overlook.
Sampling differences can make cohorts appear psychologically different when their composition, rather than their shared experiences, explains the outcome. Attrition creates a related problem when participants who leave a study differ from those who remain. Researchers must therefore consider who entered each cohort and who completed later measurements before interpreting apparent changes in development, mental health, or behavior.
A study first identifies the characteristic defining each cohort, such as birth period, life stage, or exposure. Researchers then select participants, measure relevant psychological outcomes, and compare results within and between cohorts. When measurements are repeated, the analysis can examine changes over time while accounting for age, historical period, sampling differences, and participant attrition.
Psychologists may use this approach when they need to examine how social context, development, or major life events relate to patterns across groups and time. It is especially useful for studying cognition, mental health, attitudes, and behavior. Comparing cohorts can expose shifts or contrasts that an individual study, with one group or one measurement point, may not show.
The method can organize evidence about changes in cognition, mental health, attitudes, and behavior across groups that share a birth period, life stage, or exposure. Its value lies in connecting observed differences with developmental timing and historical context rather than treating every contrast as an individual difference. Interpretation remains strongest when researchers consider age, period, sampling, and attrition together.