DISTRATE: Stata module to compute direct standardized rates with improved confidence interval (original) (raw)
Related papers
The Stata Journal: Promoting communications on statistics and Stata, 2019
In August 2017, the National Center for Health Statistics (NCHS), part of the U.S. Federal Statistical System, published new standards for determining the reliability of proportions estimated using their data. These standards require one to take the Korn–Graubard confidence interval (CI), CI widths, sample size, and degrees of freedom to assess reliability of a proportion and determine whether it can be presented. The assessment itself involves determining whether several conditions are met. In this article, I present kg_nchs, a postestimation command that is used following svy: proportion. It allows Stata users to a) calculate the Korn–Graubard CI and associated statistics used in applying the NCHS presentation standards for proportions and b) display a series of three dichotomous flags that show whether the standards are met. I provide empirical examples to show how kg_nchs can be used to easily apply the standards and prevent Stata users from needing to perform manual calculation...
2014
Abstract. This paper describes an update of the ellip command for graphing confidence ellipses in Stata 8. Two of the most notable new features are the option to graph confidence ellipses around variable means and the ability to add inscribed lines. These features allow a geometric characterization of linear regression with unequal error variances, as in McCartin (2003).
An application of the interval estimation for the At-Risk-of-Poverty Rate assessment
Metody Ilościowe w Badaniach Ekonomicznych, 2022
In the document [Eurostat (Your Key to European Statistics) 2020], At-Risk-of-Poverty Rate (ARPR in short) is defined as the percentage of population with an income not exceeding 60% of the general population median income. Extensive and thorough research on the estimation of this measure has been conducted since its introduction. For example, in the paper of [Zieliński 2009a] a non-parametric, distribution-free confidence interval for ARPR has been constructed. An example of application of the confidence interval proposed by [Zieliński 2009a] has been given in [Zieliński 2009b]. Some other interesting approach regarding the interval estimation of ARPR has been proposed in [Luo and Qin 2017], where the authors introduced new concepts of the interval estimation for the so-called Low-Income Proportion (LIP) measure, which is a generalization of ARPR. The LIP measure and thus, the ARPR parameter in particular, are important indexes describing the inequality in an income distribution. B...
Confidence intervals: Concepts, fallacies, criticisms, solutions and beyond
Network Biology, 2022
http://www.iaees.org/publications/journals/nb/articles/2022-12(3)/confidence-intervals-fallacies-criticisms-solutions.pdf For a long time, confidence interval theory is the basis of statistics, and confidence interval has been regarded as an important content of statistical analysis. Almost all statistical textbooks and statistical analysis software contain the contents of confidence intervals, which are used to estimate statistical parameters or parameters of mathematical models, and are an important part of many methods such as interval estimation, analysis of variance, and regression analysis, etc. They are recommended or required by the method guidelines of many reputable journals. So far, confidence interval theory and methods have been widely used in various scientific or engineering fields including life sciences, medicine, environmental science, chemistry, physics, and psychology. However, due to the fallacies or deficiencies of the confidence interval theory and methodology, it has caused a wide range of misuses, and has been criticized more and more in recent years. Some statisticians even suggest abandoning the confidence interval theory. To avoid the problems of classical confidence interval theory, one can use Bayesian credible intervals, use uncertainty methods, calculate confidence intervals by avoiding statistic significance tests, or use the Bootstrap credible interval method proposed by me, etc. In practice, for controlled experiments, multiple replicates or treatments should be designed; for observational experiments, multiple representative samples should be drawn, and even a single sample can be used if sufficient sample size is ensured. It is necessary to implement the whole process control for every procedures from sampling to statistical analysis. Cross-comparison and validation of confidence interval analysis results with other multi-source results should be conducted to obtain the most reliable conclusions. Finally, in addition to writing, publishing and adopting new statistical works and teaching materials as soon as possible, it is imperative to revise and distribute various statistical software in new editions based on new statistics for use.
Confidence Intervals for Ratios: Econometric Examples with Stata
Social Science Research Network, 2018
Ratios of parameter estimates are often used in econometric applications. However, the test of these ratios when estimated can cause difficulties since the ratio of asymptotically normally distributed random variables have a Cauchy distribution for which there are no finite moments. This paper presents a method for the estimation of confidence intervals based on the Fieller approach that has been shown to be preferable to the usual Delta method. Using example applications in both Stata and R, we demonstrate that a few extra steps in the examination of the estimate of the ratio may provide a confidence interval with superior coverage.
Request for Confidence Intervals for Proportions
Stata Technical Bulletin, 1992
Submissions to the STB, including submissions to the supporting files (programs, datasets, and help files), are on a nonexclusive, free-use basis. In particular, the author grants to StataCorp the nonexclusive right to copyright and distribute the material in accordance with the Copyright Statement below. The author also grants to StataCorp the right to freely use the ideas, including communication of the ideas to other parties, even if the material is never published in the STB. Submissions should be addressed to the Editor. Submission guidelines can be obtained from either the editor or StataCorp. Copyright Statement. The Stata Technical Bulletin (STB) and the contents of the supporting files (programs, datasets, and help files) are copyright c by StataCorp. The contents of the supporting files (programs, datasets, and help files), may be copied or reproduced by any means whatsoever, in whole or in part, as long as any copy or reproduction includes attribution to both (1) the author and (2) the STB. The insertions appearing in the STB may be copied or reproduced as printed copies, in whole or in part, as long as any copy or reproduction includes attribution to both (1) the author and (2) the STB. Written permission must be obtained from Stata Corporation if you wish to make electronic copies of the insertions. Users of any of the software, ideas, data, or other materials published in the STB or the supporting files understand that such use is made without warranty of any kind, either by the STB, the author, or Stata Corporation. In particular, there is no warranty of fitness of purpose or merchantability, nor for special, incidental, or consequential damages such as loss of profits. The purpose of the STB is to promote free communication among Stata users.
2003
1. Statistics Netherlands has developed a software package called MacroView that enables an efficient development of custom-tailored macro-editing tools. Generic functionalities of macro-editing tools are implemented in MacroView. These functionalities are in fact the building blocks of all macroediting tools developed in MacroView. To actually build such a custom-tailored macro-editing tool using these building blocks, a script language can be used. Scripts specify which building blocks are combined in a macro-editing tool and how. Macro-editing tools developed in MacroView are currently being used in the redesigned Dutch Structural Business Statistics and Road Statistics. At the moment MacroView scripts are developed and tested for the redesigned Short term Statistics.