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Related Concept Videos

Odds Ratio01:09

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The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
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Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
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In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
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Uncertainty: Confidence Intervals00:54

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The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
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Hazard Ratio01:12

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The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
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Propagation of Uncertainty from Random Error00:59

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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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Related Experiment Video

Updated: Mar 14, 2026

An R-Based Landscape Validation of a Competing Risk Model
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Admitting to uncertainty in the LR.

James M Curran1

  • 1University of Auckland, Department of Statistics, Private Bag 92019, Auckland 1142, New Zealand.

Science & Justice : Journal of the Forensic Science Society
|October 6, 2016
PubMed
Summary

Reporting uncertainty in the likelihood ratio is currently best practice in scientific analysis. While Bayes factors offer a future alternative, they are too complex for most current applications.

Area of Science:

  • Statistics
  • Scientific Methodology

Background:

  • Likelihood ratios are fundamental in statistical inference.
  • Accurate reporting of uncertainty is crucial for scientific reproducibility.

Purpose of the Study:

  • To advocate for the current best practice of reporting uncertainty in likelihood ratios.
  • To discuss the potential future adoption of Bayes factors.

Main Methods:

  • The paper reviews current statistical knowledge and practices.
  • It analyzes the feasibility of reporting Bayes factors.

Main Results:

  • Reporting uncertainty in the likelihood ratio is identified as the optimal current method.
  • The calculation of Bayes factors is currently limited to simple cases.
Keywords:
Bayes factorBayesianLikelihood ratioSampling uncertaintyStatistics

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Conclusions:

  • Emphasize the importance of reporting uncertainty in likelihood ratios for robust scientific conclusions.
  • Acknowledge Bayes factors as a developing alternative for specific scenarios.