Step 4

Analyzing Data

Chapter 25

Data Management

Overview

• Data management refers to the entire process of record keeping.

• After data are entered, the files need to be cleaned and perhaps recoded before beginning statistical analysis.

Codebooks

• A codebook specifies how the collected information will be entered into a computer database.

• The codebook also describes how anticipated data problems, such as missing data, will be handled.

FIGURE 25- 1

Example of

Codebook Entries

Data Entry

• Data are usually entered into a database program (like Microsoft Access) or a spreadsheet program (like Microsoft Excel).

• Both database and spreadsheet files can be uploaded into standard statistical software programs for analysis.

• It may be worth doing double-entry of at least some of the completed survey forms to check the accuracy of data entry.

Data Cleaning

• Data cleaning is the process of correcting any typographical or other errors in database files, such as extra spaces, typos, the use of lower-case instead of capital letters, or the presence of extremely unreasonable responses.

• Data cleaning should also ensure that duplicate entries are removed from the database and that the records are complete, with all data from all participants entered into the database.

FIGURE 25- 2 Example of Data Cleaning

Data Recoding

• The recoding of variables into new categories can be done either prior to or during data analysis.

• Never do any recoding until an original version of the cleaned data file is safely backed up elsewhere.

• Never replace the original values with the new recoded values.

Maintaining Confidentiality

It is essential to maintain the confidentiality of any information participants disclosed to researchers. •Store paper records in a locked and secure room.•Create secure password-protected computerized data files. •Do not include individually-identifying information in any electronic file containing other information about participants. •Only allow key research personnel to access records.