Search

The Fay–Herriot model is a linear mixed model that plays a relevant role in small area estimation (SAE). Under the SAE set-up, tools for selecting an adequate model are required. Applied statisticians are often interested on deciding if it is worthwhile to use a mixed effect model instead of a simpler fixed-effect model. This problem is not standard because under the null hypothesis the random effect variance is on the boundary of the parameter space. The likelihood ratio test and the residual likelihood ratio test are proposed and their finite sample distributions are derived. Finally, we analyse their behaviour under simulated scenarios and we also apply them to real data. [ABSTRACT FROM AUTHOR]

Problems of goodness-of-fit to a given distribution can usually be reduced to test uniformity. The uniform distribution appears due to natural random events or due to the application of methods for transforming samples from any other distribution to the samples with values uniformly distributed in the interval (0, 1). Thus, one can solve the problem of testing if a sample comes from a given distribution by testing whether its transformed sample is distributed according to the uniform distribution. For this reason, the methods of testing for goodness-of-fit to a uniform distribution have been widely investigated. In this paper, a comparative power analysis of a selected set of statistics is performed in order to give suggestions on which one to use for testing uniformity against the families of alternatives proposed by Stephens [Stephens, M.A., 1974, EDF statistics for goodness of fit and some comparisons. Journal of the American Statistical Association, 69, 730–737.]. Definition and some relevant features of the considered test statistics are given in section 1. Implemented numerical processes to calculate percentage points of every considered statistic are described in section 2. Finally, a Monte Carlo simulation experiment has been carried out to fulfill the mentioned target of this paper. [ABSTRACT FROM AUTHOR]

Objective: To evaluate occurrence of the inappropriate prescriptions in a psychiatric department., Methodology: In this prospective survey over a two-month period, the medical orders were analysed. Inappropriate prescription was defined as any discrepancy with summary of product characteristics (SPC) or our hospital treatment guidelines., Results: One hundred inpatients (72 women, mean age 37.5+/-15 years) were included. We reviewed 495 medication orders, which represent 1875 prescribed drugs. We found 2636 discrepancies with SPC or our hospital treatment guidelines. The proportion of discrepancies related to legal informations was 21.28% and them related to pharmacotherapy was 55.04%. The proportion of discrepancy per patient was estimated to 4.93%., Conclusion: Our study shows a high proportion of inappropriate prescriptions, none of them having induced adverse-drug effects.