The minimum averaged mean squared error nonparametric adaptive weights use data from m possibly different populations to infer about one population of interest. The definition of these weights is based on the properties of the empirical distribution function. We use the Kaplan-Meier estimate to let the weights accommodate right-censored data and use them to define the weighted Kaplan-Meier esti...

Here, T is the time of an event and Z a p-dimensional vector of covariates, φ a square integrable function, and F(t | z) = P (T ≤ t | Z = z) and H( dz) = P (Z ∈ dz) denote the conditional survival distribution and the marginal law of Z , respectively. For example, θ(I {t > t∗}) is the marginal survival probability at time t∗, θ(I {t > t∗, z1 > z∗ 1}) the bivariate distribution at (t∗, z∗ 1) (Ak...

The Kaplan-Meier (KM) method is used to analyze 'time-to-event' data. The outcome in KM analysis often includes all-cause mortality, but could also include other outcomes such as the occurrence of a cardiovascular event. The purpose of this article is to explain the basic concepts of the KM method, to provide some guidance regarding the presentation of the KM results and to discuss some importa...

Mischa Meier, Geschichte der Völkerwanderung – Europa, Asien und Afrika vom 3. bis zum 8. Jahrhundert n. Chr. München: C.H. Beck 2019. 5/2020. 1532 S. mit 40 Abb. 38 Karten. ISBN 978-3-406-73959-0. Geb. € 58,–

The need for analyzing time to event data arises in a number of applied fields, such as epidemiology, public health and medicine [1]. ‘Time to event’ simply means the time from entry into a study until a subject has a particular outcome. The study that involves time to event can be a cohort study on a specific number of patients or participants which should be followed for a particular time per...