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Related Concept Videos

Uncertainty in Measurement: Accuracy and Precision03:37

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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
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Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
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Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
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Accuracy and Precision01:52

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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.  Highly accurate...
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Related Experiment Video

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Meta-Analysis of the Effectiveness and Safety of Shugan Jieyu Capsules for the Treatment of Insomnia
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Systematic reviews and meta-analyses addressing comparative test accuracy questions.

Mariska M G Leeflang1, Johannes B Reitsma2

  • 11Department Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam Public Health, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

Diagnostic and Prognostic Research
|May 17, 2019
PubMed
Summary

Comparing diagnostic tests is crucial, but current studies often evaluate single tests, potentially biasing comparative accuracy. Novel statistical methods are needed for accurate meta-analyses of diagnostic test performance.

Area of Science:

  • Medical diagnostics
  • Biostatistics
  • Systematic reviews

Background:

Keywords:
Comparative accuracyDiagnostic test accuracyMeta-analysisSystematic reviews

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  • Most clinical questions involve comparing diagnostic tests, yet studies often assess only one test's accuracy.
  • Combining single-test accuracy data in systematic reviews can lead to biased comparative accuracy estimates.
  • This bias arises from evaluating tests independently rather than in direct comparison within the same patient population.