%0 Journal Article
%T Decision-Making Using Efficient Confidence-Intervals with Meta-Analysis of Spatial Panel Data for Socioeconomic Development Project-Managers
%A Ashok Sahai
%A Clement K. Sankat
%A Koffka Khan
%J International Journal of Intelligent Systems and Applications
%D 2012
%I MECS Publisher
%X It is quite common to have access to geospatial (temporal/spatial) panel data generated by a set of similar data for analyses in a meta-data setup. Within this context, researchers often employ pooling methods to evaluate the efficacy of meta-data analysis. One of the simplest techniques used to combine individual-study results is the fixed-effects model, which assumes that a true-effect is equal for all studies. An alternative, and intuitively-more-appealing method, is the random-effects model. A paper was presented by the first author, and his co-authors addressing the efficient estimation problem, using this method in the aforesaid meta-data setup of the ¡®Geospatial Data¡¯ at hand, in Map World Forum meeting in 2007 at Hyderabad; INDIA. The purpose of this paper had been to address the estimation problem of the fixed-effects model and to present a simulation study of an efficient confidence-interval estimation of a mean true-effect using the panel-data and a random-effects model, too in order to establish appropriate ¡®confidence interval¡¯ estimation for being readily usable in a decision-makers¡¯ setup. The present paper continues the same perspective, and proposes a much more efficient estimation strategy furthering the gainful use of the ¡®Geospatial Panel-Data¡¯ in the Global/Continental/ Regional/National contexts of ¡°Socioeconomic & other Developmental Issues¡¯. The ¡®Statistical Efficient Confidence Interval Estimation Theme¡¯ of the paper(s) has a wider ambit than its applicability in the context of ¡®Socioeconomic Development¡¯ only. This ¡®Statistical Theme¡¯ is, as such, equally gainfully applicable to any area of application in the present world-order at large inasmuch as the ¡°Data-Mapping¡± in any context, for example, the issues in the topically significant area of ¡°Global Environmental Pollution-Mitigation for Arresting the Critical phenomenon of Global Warming¡±. Such similar issues are tackle-able more readily, as the impactful advances in the ¡°GIS & GPS¡± technologies have led to the concept of ¡°Managing Global Village¡± in terms of ¡®Geospatial Meta-Data¡¯. This last fact has been seminal to special zeal-n-motivation to the authors to have worked for this improved paper containing rather a much more efficient strategy of confidence-interval estimation for decision-making team of managers for any impugned area of application.
%K Geospatial
%K Meta-Data
%K Confidence Interval
%K Socioeconomic
%K Data Mapping
%U http://www.mecs-press.org/ijisa/ijisa-v4-n9/v4n9-12.html