We describe an approach to building models for data with random effects. The modeling includes both random location effects and random scale effects. The approach consists of a sequence of steps. In each step, model building tools based on certain statistics are used to study the structure of the data and identify or check an aspect of the model; the results of most of the steps are used explic...

Daylight Saving Time (DST) is currently implemented by more than seventy countries, yet we do not have a clear knowledge of how it affects individuals’ welfare. Using regression discontinuity design combined with differences-in-differences approach, find that the Spring DST causes significant decline in life satisfaction. By inducing reallocation time, transition into deteriorates sleep and inc...

Functional safety standards (ISO 26262, IEC 61508) require a safety life cycle which demands additional design and engineering tasks to be managed. This paper addresses how the existing FMEAs have to be extended and refocused to address and overview signal paths throughout the system. The safety standards require to classify signals with a SIL (Safety Integrity Level) and the higher the SIL the...

Reaction times (rts) are an important source of information in experimental psychology. Classical methodological considerations pertaining to the statistical analysis of rt data are optimized for analyses of aggregated data, based on subject or item means (c.f., Forster & Dickinson, 1976). Mixedeffects modeling (see, e.g., Baayen, Davidson, & Bates, 2008) does not require prior aggregation and ...

Rank-Based methods for iid linear models have been developed over the past 30 years. However, little work has been done in the area of mixed models. In this paper, we discuss a transformation approach to modeling a particular mixed model: one with an arbitrary number of fixed effects and covariates but only one random effect. Discussion of the asymptotic theory is given and the results of a sim...

This paper considers the problem of estimating fixed effects, random effects and variance components for the multi-variate random effects model with complete and incomplete data. It also considers making inference about the fixed and random effects, a problem which requires careful consideration of the choice of degrees of freedom to use in confidence intervals. This paper uses the EM algorithm...

Several organizations have developed online crowdsourcing platforms that tap into the “wisdom” (creative ideas for new products and services) of a large “crowd’ of non-experts (consumers). The crowdsourcing model seems very attractive because consumers are intrinsically motivated to freely contribute their creative ideas, but little is known about the effectiveness of these approaches. Two year...

Robust rank-based methods are proposed for the analysis of data from multi-center clinical trials using a mixed model (including covariates) in which the treatment effects are assumed to be fixed and the center effects are assumed to be random. These rankbased methods are developed under the usual mixed model structure but without the normality assumption of the random components in the model. ...