Showing 1 - 10 of 428
Persistent link: https://www.econbiz.de/10011729239
Risk difference is an important measure of effect size in biostatistics, for both randomised and observational studies. The natural way to adjust risk differences for potential confounders is to use an additive binomial model, which is a binomial generalised linear model with an identity link...
Persistent link: https://www.econbiz.de/10010906924
Persistent link: https://www.econbiz.de/10008533850
In this article, we explain how to calculate adjusted risk ratios and risk differences when reporting results from logit, probit, and related nonlinear models. Building on Stata’s margins command, we create a new postestimation command, adjrr, that calculates adjusted risk ratios and adjusted...
Persistent link: https://www.econbiz.de/10010691932
Persistent link: https://www.econbiz.de/10014437441
Summary We consider estimation for a multivariate location family. Between all confidence regions with volume less than a fixed value L , we find the equivariant confidence region with the biggest coverage probability. This region maximizes the infimum of the coverage probability over all...
Persistent link: https://www.econbiz.de/10014621339
E-collaboration researchers usually employ P values for hypothesis testing, a common practice in a variety of other fields. This is also customary in many methodological contexts, such as analyses of path models with or without latent variables, as well as simpler tests that can be seen as...
Persistent link: https://www.econbiz.de/10012048790
Abstract The Fetal–Infant mortality rate (FIMR) is the basic surveillance statistic in perinatal periods of risk (PPOR) analyses. This paper presents a model for the FIMR as the ratio of two Poisson random variables. From this model, expressions for estimators of variance, standard error, and...
Persistent link: https://www.econbiz.de/10014590651
Abstract This paper employs a Monte Carlo study to compare the performance of equal-tailed bootstrap percentile- t , symmetric bootstrap percentile- t , bootstrap percentile, and standard asymptotic confidence intervals in two distinct heteroscedastic regression models. Bootstrap confidence...
Persistent link: https://www.econbiz.de/10014612565
Abstract We propose a new approach to statistical inference on parameters that depend on population parameters in a non-standard way. As examples we consider a parameter that is interval identified and a parameter that is the maximum (or minimum) of population parameters. In both examples we...
Persistent link: https://www.econbiz.de/10014612567