data_management - 1 Data Management Issues in Epidemiology...

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Center for Infectious Disease Preparedness UC Berkeley School of Public Health www.idready.org 1 Data Management Issues in Epidemiology Wayne Enanoria, PhD, MPH Public Health Epidemiologist Center for Infectious Disease Preparedness UC Berkeley School of Public Health Email: enanoria@berkeley.edu
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Center for Infectious Disease Preparedness UC Berkeley School of Public Health www.idready.org 2 Outline Steps of a Project: Defining new variables Format and range of permissible values Creating a database Creating a data dictionary Test data entry procedures Data entry Creating a dataset for analysis Backing up and archiving the dataset
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Center for Infectious Disease Preparedness UC Berkeley School of Public Health www.idready.org 3 ALERT: this lecture contains my biases for data management!
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Center for Infectious Disease Preparedness UC Berkeley School of Public Health www.idready.org 4 Defining New Variables Each variable should be identified and given a name. The name will be used to identify variables in the database and during the analysis. Ideal features of a name: Easily identifies the question on the form (if one is used) or type of information collected Understandable, consistent and short (some software programs only allow 8 characters!)
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Center for Infectious Disease Preparedness UC Berkeley School of Public Health www.idready.org 5 Additional Comments on Naming Variables Good idea to name all variables using lower case. Eliminates mistakes if software programs are case sensitive. Some measurements are not collected on data forms (eg, laboratory data). Such variables should be defined and described in the data dictionary (more on this in a minute).
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Center for Infectious Disease Preparedness UC Berkeley School of Public Health www.idready.org 6
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Center for Infectious Disease Preparedness UC Berkeley School of Public Health www.idready.org 7
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Center for Infectious Disease Preparedness UC Berkeley School of Public Health www.idready.org 8 Alternative Example: Laboratory Data idnum specimen0 specimen1 specimen2 specimen3 specimen4 1 Blood Sputum Blood Blood Blood 2 Blood Sputum Blood 3 Sputum Blood Blood Blood Blood 4 Blood Blood 5 Sputum
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Center for Infectious Disease Preparedness UC Berkeley School of Public Health www.idready.org 9 Laboratory Data as One Table idnum specimen 1 Blood 1 Sputum 1 Blood 1 Blood 1 Blood 2 Blood 2 Sputum 2 Blood 3 Sputum 3 Blood 3 Blood 3 Blood 3 Blood 4 Blood 4 Blood 5 Sputum
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UC Berkeley School of Public Health www.idready.org 10 Creating a Database A database turns disparate pieces of data into information. Before a database is created, be sure to have a clear goal and purpose for its existence. Who will use it? What are their needs?
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This note was uploaded on 12/08/2010 for the course USE 3425 taught by Professor Raman during the Spring '10 term at Punjab Engineering College.

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data_management - 1 Data Management Issues in Epidemiology...

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