Chemotherapy medication errors may lead to potentially harmful consequences while most of them could be preventable. This study aims to determine the incidence and type of drug handling and administration errors among the nurses and to identify possible contributing factors. Setting of the study was a teaching hospital affiliated to Shahid Beheshti University of Medic...

the development of the information and communication technology is considered as an effective step that has considerably changed in the educational goals, plans, and teaching procedures and improved educational effectiveness.  introducing ‘the software for assessing and teaching core vocabularies to non-persian speakers’, the present study aims to accentuate the role of technology in the educat...

The errors ei in (1.1) are assumed to be independent and identically distributed, but are not necessarily normal and may be heavy-tailed. Assume for convenience that β is one dimensional. Then (1.1) is a simple linear regression. However, most of the following extends more-or-less easily to higher-dimensional β, in which case (1.1) is a multiple regression. Given β, define Ri(β) as the rank (or...

Recently, in this journal, there has been revised attention on estimating the parameters of the errors in variables, linear structural model. For example, O’Driscoll and Ramirez (2011) used a geometric approach to give insight into the performance of various slope estimators for the linear structural model as introduced by the present author. This paper aims to provide a unified method of momen...

A method is proposed which simplifies estimation of all parameters in the functional measurement error model with no error in the equation under the assumption that the error covariance for the explanatory variables is known and the model variance is unknown. The proposed method is shown to produce the same estimates given for the structural model in Schneeweiss (1976) and Fuller(1987) .

A measurement error model is a regression model with (substantial) measurement errors in the variables. Disregarding these measurement errors in estimating the regression parameters results in asymptotically biased estimators. Several methods have been proposed to eliminate, or at least to reduce, this bias, and the relative efficiency and robustness of these methods have been compared. The pap...

A measurement error model is a regression model with (substantial) measurement errors in the variables. Disregarding these measurement errors in estimating the regression parameters results in asymptotically biased estimators. Several methods have been proposed to eliminate, or at least to reduce, this bias, and the relative efficiency and robustness of these methods have been compared. The pap...

We consider the nonparametric estimation of the regression functions for dependent data. Suppose that the covariates are observed with additive errors in the data and we employ nonparametric deconvolution kernel techniques to estimate the regression functions in this paper. We investigate how the strength of time dependence affects the asymptotic properties of the local constant and linear esti...

The paper is a survey of recent investigations by the authors and others into the relative efficiencies of structural and functional estimators of the regression parameters in a measurement error model. While structural methods, in particular the quasi-score (QS) method, take advantage of the knowledge of the regressor distribution (if available), functional methods, in particular the corrected...