Nonrandomized Evidence
Nonrandomized Evidence - Related Videos
02:55
The Evidence for Evolution
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2026
Genetic variations accumulating within populations over generations give rise to biological evolution. Evolutionary changes can result in the formation of novel varieties and entire new species. These changes are responsible for the diverse forms of life inhabiting the planet. The evidence for evolution suggests that all living organisms descended from common ancestors.The collection of fossils within sedimentary rocks give a record of common ancestry and often depicts the history of evolution.
11:49
Enhanced Genetic Analysis of Single Human Bioparticles Recovered by Simplified Micromanipulation from Forensic ‘Touch DNA’ Evidence
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Cited by 26 •
2015
Here we describe an optimized and efficient removal strategy for the collection of bio-particles present in ‘touch DNA’ samples, together with an enhanced amplification protocol involving a one-step 5 µl micro-volume lysis/STR amplification, to permit the recovery of short tandem repeat (STR) profiles of the bio-particle donor(s).
05:35
Experience is Instrumental in Tuning a Link Between Language and Cognition: Evidence from 6- to 7- Month-Old Infants' Object Categorization
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Cited by 1 •
2017
At 3-4 months, listening to human and nonhuman primate vocalizations boosts infants' cognition; by 6 months, only human vocalizations exert this cognitive advantage. We describe an exposure manipulation that reveals the powerful shaping role of experience as infants specify which sounds to link to cognition and which to tune out.
11:50
High-frequency High-resolution Echocardiography: First Evidence on Non-invasive Repeated Measure of Myocardial Strain, Contractility, and Mitral Regurgitation in the Ischemia-reperfused Murine Heart
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Cited by 9 •
2010
High frequency Doppler ultrasound is a novel technology for assessing regional myocardial function. This work presents first evidence demonstrating applicability of this versatile imaging platform for the repeated measure of myocardial strain, dp/dt, and mitral regurgitation in the ischemia-reperfused (IR) murine heart.
08:02
Evidence for EpCAM and Cytokeratin Expressing Epithelial Cells in Normal Human and Murine Blood and Bone Marrow
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Cited by 2 •
2023
This paper presents a reproducible method with new findings on the presence of epithelial cells in normal human and mouse blood and bone marrow using flow cytometry and immunofluorescence microscopy. Krt1-14;mTmG transgenic mice were used as an in vivo method to confirm these findings.
FAQs
The main analytical challenge is confounding: a factor associated with both the intervention or exposure and the outcome can make groups appear different for reasons unrelated to the intervention. Matching pairs or groups with similar characteristics, stratification compares defined subgroups, and statistical adjustment accounts for measured differences. These approaches can reduce, but do not automatically eliminate, bias.
Selection bias arises when people who receive an intervention differ systematically from those who do not, including through how groups enter a study. Unlike randomization, which helps balance such differences by design, nonrandomized analyses must address them after groups have formed. This distinction explains why their findings generally have less protection against systematic bias, even when analysis is careful.
Quasi-experimental methods can add structure to comparisons when researchers cannot assign treatment randomly. Their value comes from examining naturally occurring changes or contrasts while using an explicit design and transparent analysis. In medicine, this can support evaluation of healthcare delivery and treatment outcomes, but interpretation still depends on how convincingly the design addresses alternative explanations for observed differences.
A practical workflow begins by defining the intervention or exposure, identifying naturally occurring comparison groups, and selecting relevant outcomes. Researchers then choose a cohort, registry, observational, or quasi-experimental design and apply matching, stratification, or statistical adjustment to address measured differences. Reporting the design and analysis transparently helps readers judge the strength and limitations of the result.
Because participants are observed in real-world healthcare settings, this evidence can show treatment effectiveness and safety across broader patient populations. Registries and cohort studies may include people underrepresented in clinical trials, making their outcomes relevant to routine care. These findings can complement trial evidence by describing how interventions perform among patients encountered in ordinary medical practice.
Nonrandomized evidence is especially useful when randomization is impractical or unethical. It can evaluate healthcare delivery, examine outcomes in populations that clinical trials may underrepresent, generate hypotheses for future research, and inform medical decisions. Its usefulness depends on careful design and transparent analysis, because observed associations may still reflect confounding or selection bias rather than the intervention itself.