Statistics: Principles and Methods, 7th Edition [Book]Kundurjiev, T. The present article deals with the theme of efficiency in healthcare and especially technical efficiency in psyaciatric hospital care. We used the method of data envelopment analysis DEA , which finds increasing application in many spheres of public life, including healthcare. We subdivided the treatment facilities in the current study in three groups and estimated technical efficiency for each group. We present a possible assesment method, which provides an opportunity for improving efficiency in the sector. Methodology and Applications Kluwer Academic Publishers; Chang H, Determinants of hospital efficiency: the case of central government- owned hospitals in Taiwan.
Statistical Concepts And Methods
Youngseok Kim added it Jul 03, In: Dror M. Leisch F. A non-mathematical introductory statistics text that combines clear explanation of concepts, and numerous illustrations with live data from diverse fields.Return to Book Page. Refresh and try again. A non-mathematical introductory statistics text that combines clear explanation of concepts, and numerous illustrations with live data from diverse fields. This is a dummy description.
The algorithms used by these methods solely use the gene expression profiles and are not guided by any outcome data. This is the latest version of this item. Quick calculation for sample size while controlling false discovery rate with application to microarray analysis. In experiments with few analytic features, one can incorporate internal controls to ensure that the measurements are properly normalized.
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Gouri K. Bhattacharyya. John Wiley & Sons Each statistical concept or method is motivated by setting out its goal and then focusing on an . knife.sujohnson) Contains interesting data sets used in the text but that can be used to.
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To this end, User lists Similar Items. Adheala Nathasya marked it as to-read Sep 20, class discovery methods have been found to be very useful! When evaluating the operating characteristic of a statistical model, one has to take into account accuracy and precision.
What is important to research is for the software to be flexible and extensible so as to allow the user to determine the analysis method thought to be best suited to ;df the scientific questions at hand. Andrew Davis added it Mar 16, Find a copy online Links to this item Table of contents Table of contents Table of contents. Your rating has been recorded.Permutation resampling can be used to generate the sampling distribution of the gene set statistics while properly accounting for coregulation among genes and for multiple testing. In due course, we will an the flaw in evaluating a model using this approach known as error resubstitution see e. These issues have not been adequately addressed in the literature and deserve greater attention? Modern Applied Statistics with S.
Monica marked it as to-read Oct 22. Error rating book? A mismatch probe is bhattacharryya as a control to each PM probe. This is the latest version of this item.
A non--mathematical introductory statistics text that combines clear explanation of concepts, an extensive coverage of useful statistical techniques, and numerous illustrations with live data from diverse fields. Emphasizes assumptions and limitations of the statistical methods so that violations of assumptions can be avoided. Read more Table of contents. Please choose whether or not you want other users to be able to see on your profile that this library is a favorite of yours. Finding libraries that hold this item You may have already requested this item.
Ruta marked it as to-read Aug 31, Making best use of model evaluations to compute sensitivity indices? Goodreads helps you keep track of books you want to read. Welcome back?
Microarray technologies enable the simultaneous interrogation of expressions from thousands of genes from a biospecimen sample taken from a patient. This large set of expressions generates a genetic profile of the patient that may be used to identify potential prognostic or predictive genes or genetic models for clinical outcomes. The aim of this article is to provide a broad overview of some of the major statistical considerations for the design and analysis of microarrays experiments conducted as correlative science studies to clinical trials. An emphasis will be placed on how the lack of understanding and improper use of statistical concepts and methods will lead to noise discovery and misinterpretation of experimental results. Clin Trans Sci ; Volume 4: —
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Please select Ok if you would like to proceed with this request anyway. Predictive Models The statistical inference methods for association testing are concerned with finding prognostic or predictive features for a given outcome. Aditya Wibowo marked it as to-read Sep 03.