In this paper, we propose a method for the evaluation of relative and impact external efficiency of university studies as effects of education on the long-term income of graduates. In order to evaluate the “ceteris paribus” levels and growth we applied a multilevel longitudinal model with random effects. The variables used in our analysis refer to Human Capital studies. The Bank of Italy has co...

Most studies on optimal crossover designs are based on models that assume subject effects to be fixed effects. In this article we identify and study optimal and efficient designs for a model with random subject effects. With the number of periods not exceeding the number of treatments, we find that totally balanced designs are universally optimal for treatment effects in a large subclass of com...

T paper proposes a new methodology to infer investors’ expectations about the speed of leverage adjustment implicit in the prices of credit instruments. On average, the credit markets imply a fairly rapid annual speed of adjustment of 26% toward a firm’s predicted leverage. The speed varies considerably across partitions formed by the differential implications of the pecking order, market timin...

Widely used approaches to modeling random effects and extracting random parameters in matching-critical circuits are based upon models derived under the widely accepted premise that distributed parameter devices can be modeled with lumped parameter models. In this paper, a new stochastic approach based upon a distributed parameter model is presented that offers improvement in predicting the eff...

The UK National Student Survey (NSS) represents a major resource, never previously used in the economics literature, for understanding how the market signal of quality in higher education works. In this study, we examine the determinants of the NSS overall student satisfaction score across eleven subject areas for 121 UK universities between 2007 and 2010. Using a unique panel data set and esti...

Linear mixed models are popular models for use with clustered and longitudinal data due to their ability to model variation at different levels of clustering. A Monte Carlo study was used to explore the impact of assumption violations on the bias of parameter estimates and the empirical type I error rates. Simulated conditions included in this study are: simulated serial correlation structure, ...

In process robustness studies, it is desirable to minimize the influence of noise factors on the system and simultaneously determine the levels of controllable factors optimizing the overall response or outcome. In the cases when a random effects model is applicable and a fixed effects model is assumed instead, an increase in the variance of the coefficient vector should be expected. In this pa...

Records on 65,536 Landrace pigs collected between 1985 and 1999 in herds on the National Swine Registry STAGES program were used to estimate additive genetic (animal), common environmental (litter), and residual variances and covariances for days to 250 lb, backfat, loin eye area, and lean growth rate. Analysis was by the REMLf90 program of I. Misztal using a multiple-trait animal model with fi...

Random effect analysis has been introduced into fMRI research in order to generalize findings from the study group to the whole population. Generalizing findings is obviously harder than detecting activation within the study group since in order to be significant, an activation has to be larger than the inter-subject variability. Indeed, detected regions are smaller when using random effect ana...

Tensor product smooths provide the natural way of representing smooth interaction terms in regression models because they are invariant to the units in which the covariates are measured, hence avoiding the need for arbitrary decisions about relative scaling of variables. They would also be the natural way to represent smooth interactions in mixed regression models, but for the fact that the ten...