Related Experiment Videos
Confidence intervals and p-values in clinical decision making.
1Department of Paediatric Gastroenterology, Booth Hall Children's Hospital, Central Manchester and Manchester Children's University Hospitals, Manchester, UK. tony.akobeng@cmmc.nhs.uk
Acta Paediatrica (Oslo, Norway : 1992)
|May 9, 2008
Summary
Confidence intervals (CIs) offer a precise range for treatment effects in clinical trials, unlike p-values. Reporting CIs enhances understanding of results and their clinical importance.
Area of Science:
- Medical Statistics
- Clinical Trial Analysis
Background:
- Clinical trials yield estimates of treatment effects applicable to a broader population.
- Confidence intervals (CIs) provide a range of plausible values for population parameters, indicating estimate precision.
Purpose of the Study:
- To highlight the importance of confidence intervals (CIs) in interpreting clinical trial results.
- To advocate for the use of CIs over p-values in medical literature.
Main Methods:
- Explanation of confidence intervals (CIs) and their interpretation, particularly the 95% CI.
- Comparison of CIs with p-values regarding statistical significance and clinical importance.
Main Results:
- CIs offer a range of plausible values for population parameters, reflecting the precision of the measured treatment effect.
- P-values indicate the probability of observed differences being due to chance but lack information on clinical importance.
Conclusions:
- Authors should report confidence intervals (CIs) alongside estimates in research articles.
- CIs are more informative than p-values, providing insights into both statistical significance and clinical relevance.
Related Concept Videos
01:19Interpretation of Confidence Intervals
A confidence interval is a better estimate of the population than a point estimate, as it uses a range of values from a sample instead of a single value.
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
01:09Decision Making: P-value Method
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
00:54Uncertainty: Confidence Intervals
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 't,' or...
01:21Confidence Intervals
An unbiased point estimate is often insufficient to predict a population estimate, such as population mean or population proportion. In this scenario, a confidence interval is used. A confidence interval is an estimate similar to a sample proportion. However, unlike the point estimate which is a single value, the confidence interval contains a range of values. These values have lower and upper limits, known as confidence limits, and can be designated as L1 and L2, respectively.
A confidence...
A confidence...
01:24Confidence Coefficient
The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under both the...
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...