Efficient separate class of estimators of population mean in stratified random sampling

In this paper, efficient class of estimators for population mean using two auxiliary variates is suggested. It has been shown that the suggested estimator is more efficient than usual unbiased estimator in stratified random sampling, usual ratio and product-type estimators, Tailor and Lone (2012 Tailor, R. and Lone, H. A. (2012). Separate ratio-cum- product estimators of finite population mean using auxiliary information. J. Rajasthan Stat. Assoc. 1(2):94–102. [Google Scholar], 2014) estimators, and other considered estimators. The bias and mean-squared error of the suggested estimator are obtained up to the first degree of approximation. Conditions under which the suggested estimator is more efficient than other considered estimators are obtained. An empirical study has been carried out to demonstrate the performances of the suggested estimator.     

An Instrument for Assessing the Organizational Benefits of IS Projects

This paper reports the development of an instrument to measure the organizational benefits of IS projects. The basis for this instrument was a published framework that suggests three categories of such benefits: strategic, informational, and transactional. In a cross-sectional study of 178 IS projects proposed and approved for development, this framework was operationalized and empirically tested using the measurement model of LISREL. The analysis culminated in the validation and refinement of the these categories. The final instrument offers items under three separate subdimensions of strategic benefits: competitive advantage, alignment, and customer relations. Informational benefits are similarly comprised of information access, information quality, and information flexibility. Finally, transactional benefits are also shown to be of three types: communications efficiency, systems development efficiency, and business efficiency. Implications of this multidimensional instrument for IS practitioners and researchers are discussed.     

Interactive effects of urbanization and year on invasive and native ant diversity of sacred groves of South India

Urban Ecosystems - Urbanization is a major threat to native biodiversity. Invasion of tramp species is a major consequence of urbanization, which might threaten native species. Ants are established...     

Nonparametric Estimation of the Geometric Vitality Function

Recently, Nair and Rajesh (2000 Nair , K. R. M. , Rajesh , G. ( 2000 ). Geometric vitality function and its application to reliability . IAPQR Tran. 25 ( 1 ): 1 – 8 . [Google Scholar]) proposed a measure to describe the failure pattern of components/devices in terms of the geometric mean of the residual life. This measure find applications in modeling life time data. In the present work we provide a nonparametric kernel-type estimator for the geometric vitality function, both in the case of complete and censored samples. The properties of the estimator, under certain regularity conditions, are studied. The performance of the estimator is compared with the empirical estimator using a real data set and simulation studies are carried out using the Monte Carlo method.     

Detecting bliss synergy in in vivo combination studies with a tumor kinetic model

Linear models are generally reliable methods for analyzing tumor growth in vivo, with drug effectiveness being represented by the steepness of the regression slope. With immunotherapy, however, not all tumor growth follows a linear pattern, even after log transformation. Tumor kinetics models are mechanistic models that describe tumor proliferation and tumor killing macroscopically, through a set of differential equations. In drug combination studies, although an additional drug‐drug interaction term can be added to such models, however, the drug interactions suggested by tumor kinetics models cannot be translated directly into synergistic effects. We have developed a novel statistical approach that simultaneously models tumor growth in control, monotherapy, and combination therapy groups. This approach makes it possible to test for synergistic effects directly and to compare such effects among different studies.