MARC Record from Scriblio

LEADER: 03462cam 22003738a 4500
001 2005022331
003 DLC
005 20050919181333.0
008 050801s2006 mau b 000 0 eng
010 $a 2005022331
020 $a9780727918703 (pbk.)
020 $a0727918702 (pbk.)
035 $a(DNLM)101254119
040 $aDNLM/DLC$cDLC$dDLC
042 $apcc
050 00 $aRJ253$b.S375 2006
060 10 $aWS 26.5$bS386m 2006
082 00 $a618.92/01/0285$222
100 1 $aSchulman, Joseph,$d1950-
245 10 $aManaging your patients' data in the neonatal and pediatric ICU :$ban introduction to databases and statistical analysis /$cJoseph Schulman.
260 $aMalden, Mass. :$bBlackwell Pub.,$cc2006.
263 $a0603
300 $ap. ;$ccm.
500 $a"Includes eNICU software for the neonatal intensive care unit, which may be modified for local use or other clinical settings."
504 $aIncludes bibliographical references.
505 0 $aPaper-based patient records -- Computer-based patient records -- Aims of a patient data management process -- Data, information, and knowledge -- Single tables and their limitations -- Multiple tables: where to put the data; relationships among tables; creating a database -- Relational database management systems: normalization; Codd's rules -- From data model to database software -- Integrity: anticipating and preventing problems with data accuracy -- Queries, forms, and reports -- Programming for greater software control -- Turning ideas into a useful tool: eNICU point of care database software for the NICU -- Making eNICU serve your own needs -- Single vs. multiple user -- Backup: assuring your data persists -- Security: controlling access and protecting patient confidentiality -- Crafting a conceptual framework and testable hypothesis -- Stata: a software tool to analyze data and produce graphical displays -- Preparing to analyze data -- Variable types -- Measurement values vary: describing their distribution and summarizing them quantitatively -- Data from all or some: populations and samples -- Estimating population parameters; confidence intervals -- Comparing two sample means; statistical significance and clinical significance -- Type I and type II error in a hypothesis test; power; sample size -- Comparing proportions; introduction to rates and odds -- Stratifying the analysis of dichotomous outcomes; confounders and effect modifiers; multiple 2 x 2 tables: the Mantel-Haenszel method -- Ways to measure and compare the frequency of outcomes; standardization -- Comparing the means of more than two samples -- Assuming little about the data: non-parametric methods of hypothesis testing -- Correlation: measuring the relationship between two continuous variables -- Predicting continuous outcomes: univariate and multivariate linear regression -- Predicting dichotomous outcomes: logistic regression; receiver operating characteristic (ROC) -- Predicting outcomes over time: survival analysis -- Choosing variables and hypotheses: practical considerations.
650 0 $aNeonatology$xDatabases.
650 0 $aNeonatology$xStatistical methods.
650 0 $aMedical records$xData processing.
650 12 $aDatabase Management Systems$xInfant, Newborn.
650 22 $aMedical Records$xInfant, Newborn.
650 22 $aModels, Statistical.
650 22 $aNeonatology$xmethods.
856 41 $3Table of contents$uhttp://www.loc.gov/catdir/toc/ecip0517/2005022331.html