These procedures for forming confidence intervals are attractive because they require weaker assumptions than parametric methods. Several of the procedures exploit the relationship between hypothesis tests and confidence intervals and these require hypotheses to be found that give specified P values. Finding the appropriate hypotheses can be computationally demanding, but for some problems there are efficient search techniques
Well-recommended methods of forming ‘confidence intervals’ for a binomial proportion give interval e...
Previously, researchers were reported P value as a basis for conclusion, but in this era of evidence...
We compare four methods of computing confidence intervals for a proportion. These four methods are •...
We consider construction of two-sided nonparametric confidence intervals in a smooth function model ...
The recent American Psychological Association Task Force on Statistical Inference report suggested t...
Nonparametric techniques provide no analytical solutions for confidence intervals. The bootstrap and...
Interval estimates -- estimates of parameters that include an allowance for sampling uncertainty -- ...
Often, the reader of a published paper is interested in a comparison of parameters that has not been...
Includes bibliographical references (pages 60-61)Confidence intervals are a very useful tool for mak...
The manuscript is an attempt to present in a single document the various types of confidence interva...
Often, the reader of a published paper is interested in a comparison of parameters that has not been...
Classical confidence intervals are often misunderstood by particle physicists and the general public...
We describe a non-parametric method based on the sole assumption that the data points form an i.i.d ...
AbstractThe behaviors of various confidence/credible interval constructions are explored, particular...
This article examines the role of the confidence interval (CI) in statistical inference and its adva...
Well-recommended methods of forming ‘confidence intervals’ for a binomial proportion give interval e...
Previously, researchers were reported P value as a basis for conclusion, but in this era of evidence...
We compare four methods of computing confidence intervals for a proportion. These four methods are •...
We consider construction of two-sided nonparametric confidence intervals in a smooth function model ...
The recent American Psychological Association Task Force on Statistical Inference report suggested t...
Nonparametric techniques provide no analytical solutions for confidence intervals. The bootstrap and...
Interval estimates -- estimates of parameters that include an allowance for sampling uncertainty -- ...
Often, the reader of a published paper is interested in a comparison of parameters that has not been...
Includes bibliographical references (pages 60-61)Confidence intervals are a very useful tool for mak...
The manuscript is an attempt to present in a single document the various types of confidence interva...
Often, the reader of a published paper is interested in a comparison of parameters that has not been...
Classical confidence intervals are often misunderstood by particle physicists and the general public...
We describe a non-parametric method based on the sole assumption that the data points form an i.i.d ...
AbstractThe behaviors of various confidence/credible interval constructions are explored, particular...
This article examines the role of the confidence interval (CI) in statistical inference and its adva...
Well-recommended methods of forming ‘confidence intervals’ for a binomial proportion give interval e...
Previously, researchers were reported P value as a basis for conclusion, but in this era of evidence...
We compare four methods of computing confidence intervals for a proportion. These four methods are •...