confidence intervals

Confidence intervals and interval estimates more generally have applications across the whole range of quantitative studies.

The Six Sigma Black Belt should be able to compute confidence intervals for various statistics.

Confidence Intervals may be calculated for the means of the data sets.

We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) by means of multivariable Cox proportional hazards regression models.

Simulation results are presented to compare the performances of these confidence intervals.

However, computing bootstrap confidence intervals directly for the CE ratio produce results closer to the predetermined significance level.

Transforming the data or truncating the confidence intervals at realistic values can solve the problem of out of range values.

Thus, confidence intervals are used to indicate the reliability of an estimate.

SPC charting method which uses confidence intervals to establish whether statistically significant events are occurring.

Glass in building - Procedures for goodness of fit and confidence intervals for Weibull distributed glass strength data.

In other words, studies with more precise results (narrower confidence intervals) are given more weight.

In this note we present a bootstrap procedure for estimating bias-corrected confidence intervals for CE ratios.

Frequencies and rates were calculated, and 95% confidence intervals were determined for mortality rates.

Point prevalence estimates, 95% confidence intervals and design effects were calculated.

Statistical interpretation of data - Part 7 : median - Estimation and confidence intervals.

We estimated odds ratios (ORs) for such behaviours and their 95% confidence intervals (CIs) after adjusting for age and sex.

We used logistic regression analyses to estimate the relative risk of birth outcomes with 95% confidence intervals.

The most intuitive way to answer these questions is to construct confidence intervals for the statistics.

Confidence intervals and P-values were adjusted for the cluster design.

It is the best general technique for producing confidence intervals.

The upper limit of the confidence intervals for both hazard ratios excluded the predefined non inferiority margin of 1. 23.

Rely on bootstrapping as the best way to compute confidence intervals.

Horizontal bars in the plot indicate 90% confidence intervals (colored) and 95% confidence intervals (black).

See the Confidence intervals section in the article supplement for more discussion.

Quantify and present findings with appropriate indicators of measurement error or uncertainty (such as confidence intervals).

I use mathematical statistics analysis, such as confidence intervals, hypothesis testing, K-means Cluster, regression analysis and so on.

Coverage Accuracy of Confidence Intervals for a Conditional Probability Density Function

Empirical Likelihood Confidence Intervals of Nonparametric Regression Functions

Parametric and Bootstrap Estimations of Confidence Intervals for Analyte Concentrations of Composite Samples

Simultaneous Confidence Intervals with Fixed Length and Probability of Coverage for Estimable Functions in Normal Linear Models

Statistical interpretation of data; tests and confidence intervals relating to expectations and variances

Application Condition Computing Binomial Proportion 95% Confidence Intervals Using Normal Approximate Method

Two-stage Approach to Fixed-width Confidence Intervals for the Parameters in Location and Scale Family of Distributions

Empirical Likelihood Confidence Intervals of Density Function under Dependent Samples

Statistical interpretation of data - Tests and confidence intervals relating to proportions

Guide to statistical interpretation of data - Median - Estimation and confidence intervals

Reliability Confidence Intervals for Fielded, Repairable Systems

The Confidence Intervals of the Nonparametric Regression Function

Procedures for goodness-of-fit tests, confidence intervals and lower confidence limits for Weibull distributed data

Exact Confidence Intervals for a Variance Ratio in Mixed Linear Models

Statistical interpretation of data - Tests and confidence intervals relating to proportions; Technical Corrigendum 1

Methods for evaluation of errors and their confidence intervals for flood forecasting

Determination of confidence intervals for frequency analysis by using Bootstrap

Five Methods for the Estimation of Confidence Intervals on Survival Rate

Empirical Likelihood Confidence Intervals for M-Functionals

Analysis of Variance via Confidence Intervals

How to Estimate Confidence Intervals of Proportions for Different Population Sizes and Sample Sizes

this paper is concerned with the sequential confidence intervals for unknown parameters based on moment estimates

Confidence Intervals for Variance Components Based on Multi-Vari Analysis

Estimation of Process Capability Indices and Their Confidence Intervals Based on Subsamples