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Abstract This paper discusses regression analysis of incomplete event history studies with a focus on simultaneous estimation and variable selection. Such studies are commonly performed in areas such as medical studies and social sciences, and a great deal of literature has been devoted to their analysis except for the problem considered here (Sun and Zhao, 2013). We develop a new method, which will be referred to as a broken adaptive ridge regression approach. We establish its asymptotic properties, including the oracle property and clustering effect. We also report simulation results which indicate that the proposed method performs well, and better than the existing methods, in practice. In addition, an application is provided. [ABSTRACT FROM AUTHOR]

Abstract Repeated measures designs are frequently used for planning experiments in the life or social sciences. Typical examples include the comparison of different treatments over time, where both factor levels may possess an additional structure. For such designs, the statistical analysis typically consists of several steps. If the global null is rejected, multiple comparisons are performed. Usually, general factorial repeated measures designs are inferred by classical linear mixed models. Common underlying assumptions, such as normality or variance homogeneity are, however, often not met in practice. Furthermore, when dealing with, e.g., ordinal or ordered categorical data, means are no longer meaningful to describe an effect and other effect sizes should be used. To this end, we developmultiple contrast tests for nonparametric treatment effects in general factorial repeated measures designs within this paper and equip them with a novel, asymptotically correct wild bootstrap approach. Because regulatory authorities require the calculation of confidence intervals, this work also provides simultaneous confidence intervals for linear contrasts and for the ratio of different contrasts in meaningful effects. Extensive simulations are conducted to foster the theoretical findings. Finally, the analysis of two datasets exemplify the applicability of the novel procedures. [ABSTRACT FROM AUTHOR]