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Related Concept Videos

Confidence Intervals01:21

Confidence Intervals

9.2K
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...
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Confidence Interval for Estimating Population Mean01:25

Confidence Interval for Estimating Population Mean

7.6K
A point estimate of the population mean is obtained from a single sample. Such a point estimate does not represent a population well because it needs to account for variability in the population. Single point estimate can also be biased despite the sample being selected randomly. Thus, a point estimate is often unreliable. A confidence interval is needed to reduce this unreliability.
A confidence interval for the mean is a range of values that provides an estimate of the population mean. As the...
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Interpretation of Confidence Intervals01:19

Interpretation of Confidence Intervals

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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...
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Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

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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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Prediction Intervals01:03

Prediction Intervals

2.5K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
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Confidence Coefficient01:24

Confidence Coefficient

9.1K
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...
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An R-Based Landscape Validation of a Competing Risk Model
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Confidence interval estimation in R-DAS.

Olga A Vsevolozhskaya1, James C Anthony1

  • 1Michigan State University, United States.

Drug and Alcohol Dependence
|September 2, 2014
PubMed
Summary
This summary is machine-generated.

The Restricted-Use Data Analysis System (R-DAS) enables new insights into extra-medical pain reliever use. It allows researchers to analyze sensitive data, revealing state-level differences previously unavailable.

Keywords:
IncidenceMisuseOpiatesOpioidsPain relieversR-DAS

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Area of Science:

  • Public Health
  • Epidemiology
  • Data Analysis

Background:

  • The National Survey on Drug Use and Health (NSDUH) has provided public-use data for over 25 years.
  • The Substance Abuse and Mental Health Services Administration (SAMHSA) manages the NSDUH and expanded data access.
  • In 2012, SAMHSA introduced the Restricted-Use Data Analysis System (R-DAS) for advanced data analysis.

Purpose of the Study:

  • To guide users of R-DAS-like systems in statistical analysis.
  • To address challenges in approximating confidence intervals (CI) with restricted data.
  • To enable pairwise comparisons of estimates not typically available.

Main Methods:

  • The study focuses on statistical methods for analyzing restricted survey data.
  • It clarifies issues related to confidence interval approximation.
  • It provides methods for estimating CI when data is suppressed due to confidentiality.

Main Results:

  • Empirical estimates illustrate the extra-medical use of pain relievers in the US.
  • This use is a significant public health concern, often for non-prescribed purposes.
  • The R-DAS facilitates the analysis of sensitive drug use patterns.

Conclusions:

  • The R-DAS allows for the derivation of state-level estimates on extra-medical prescription pain reliever (EMPPR) use.
  • New insights into male-female and age-related differences in EMPPR use are now possible.
  • These findings were previously unreported and inaccessible without specialized research methods.