Drawing inferences from clinical studies with missing values using genetic algorithm

Missing data problem degrades the statistical power of any analysis made in clinical studies. To infer valid results from such studies, suitable method is required to replace the missing values. There is no method which can be universally applicable for handling missing values and the main objective...

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Podrobná bibliografia
Vydané v:	International journal of bioinformatics research and applications Ročník 10; číslo 6; s. 613
Hlavní autori:	Priya, R Devi, Kuppuswami, S
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland 2014
Predmet:	Algorithms Bayes Theorem Clinical Trials as Topic - methods Computer Simulation Epidemiologic Research Design Models, Genetic Models, Statistical Research Design Sample Size Bayesian genetic algorithms MCAR discrete attributes bioinformatics clinical studies continuous attributes missing at random missing completely at random BGA MAR missing values
ISSN:	1744-5485
On-line prístup:	Zistit podrobnosti o prístupe
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