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- 2005022331 contributor B10130776.
- 2005022331 created "c2006.".
- 2005022331 date "2006".
- 2005022331 date "c2006.".
- 2005022331 dateCopyrighted "c2006.".
- 2005022331 description "Includes bibliographical references.".
- 2005022331 description "Paper-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.".
- 2005022331 extent "p. ;".
- 2005022331 identifier "0727918702 (pbk.)".
- 2005022331 identifier "9780727918703 (pbk.)".
- 2005022331 identifier 2005022331-b.html.
- 2005022331 identifier 2005022331-d.html.
- 2005022331 identifier 2005022331.html.
- 2005022331 issued "2006".
- 2005022331 issued "c2006.".
- 2005022331 language "eng".
- 2005022331 publisher "Malden, Mass. : Blackwell Pub.,".
- 2005022331 subject "618.92/01/0285 22".
- 2005022331 subject "Database Management Systems Infant, Newborn.".
- 2005022331 subject "Medical Records Infant, Newborn.".
- 2005022331 subject "Medical records Data processing.".
- 2005022331 subject "Models, Statistical.".
- 2005022331 subject "Neonatology Databases.".
- 2005022331 subject "Neonatology Statistical methods.".
- 2005022331 subject "Neonatology methods.".
- 2005022331 subject "RJ253 .S375 2006".
- 2005022331 subject "WS 26.5 S386m 2006".
- 2005022331 tableOfContents "Paper-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.".
- 2005022331 title "Managing your patients' data in the neonatal and pediatric ICU : an introduction to databases and statistical analysis / Joseph Schulman.".
- 2005022331 type "text".