Preparing Data for Analysis

1
Preparing Data for Analysis

• SPSS Training
• Thomas Joshua, MS
• July, 2008

2
Lecture Overview

• Why do we need the data management and data
  preparation for analysis
• Data preparation and general format in SPSS
• Introduction to SPSS and overview of SPSS for
  Windows

3
What is Data Management (DM)

• Collecting, entering, cleaning, and processing of
  information gathered during a research project.
• Is a work that involves the planning,
  development, implementation, and administration
  of systems for the acquisition, storage, and
  retrieval of data while protecting it by
  implementing high security levels.

4
Why need DM?

• Decision-making, strategic planning and program
  design should be data driven - Appropriate data
  is often available, but the process of analysis
  is daunting for many.
• Improving the communication
• Ensure that the data are transferred in the
  proper format for the proposed analyses.
• Help you understanding reality from data

5
Data Preparation

• We suggest a phased approach that produces
  analysis-ready data without destroying the
  original dataset.
• Also look at ways to document your dataset so
  that it will make sense when reviewed at a later
  point, or by other people.
• In general, SPSS, Microsoft Excel and Access are
  acceptable as long as it is appropriately
  formatted. We will use SPSS as the general
  example.

6
Main Steps for Data Preparation

• Create the data file.
• Original data
• Interim data
• Documentation
• Clean the data
• Process the data
• Create an analysis-ready copy of the data
• Document the data

7
Some critical points to format your data set

• Do not include header, trailer information,
  subtotals, or other extraneous information. For
  descriptive purposes you may include one row
  giving variable names.

8

• Format data so that each variable is in its own
  single column.
• For example,
• and better not
• and absolutely not

9

• Columns must be explicitly filled with data
• and not

10

• All columns must have the same number of rows and
  Missing data (empty cells) Use a blank space or a
  . to indicate missing data.
• - Missing value cannot be treated as 0.
• Keep an identical field, such the subject ID.

11

• If there are multiple data files, do not rely on
  the file names to carry variable information. For
  example, if separate files are used for the
  results of two treatments, include a column in
  each file containing the name of the treatment.

12
and Not
13

• Counted proportion data.
• If data consists of counted proportions,
• e.g. number of individuals responding out of
  total number of individuals,
• do not reduce the data to percentages or
  proportions beforehand.
• It is recommended that both numerator and
  denominator of the proportion be entered as
  separate columns.

14

• For example,
• Not
• It is easy to compute proportions during the
  analysis if they are required, but alternative
  analyses such as logistic regression may be
  precluded if original counts are unavailable.

15

• Polytomous data.
• If data consists of numbers falling into a
  number of mutually exclusive classes, do not
  reduce to proportions or percentages beforehand,
  but enter the integer counts.
• For example,
• not

16

• Each column has its own criteria or meaning.
• Narrow the definition for each variable means to
  create a new variable.
• For example,
• gender, age ? gt45 year-old male

17
Introduction to SPSS software

• SPSS is a software package used for conducting
  statistical analyses, manipulating data, and
  generating tables and graphs that summarize data.
  
• Statistical analyses range from basic descriptive
  statistics, such as averages and frequencies, to
  advanced inferential statistics, such as
  regression models, analysis of variance, and
  factor analysis.
• SPSS also contains several tools for manipulating
  data, including functions for recoding data and
  computing new variables, as well as for merging
  and aggregating datasets.

18
Overview of SPSS for Windows

• SPSS for Windows consists of five different
  windows, each of which is associated with a
  particular SPSS file type.
• Data Editor - the window that is open at start-up
  and is used to enter and store data in a
  spreadsheet format. Includes Data View and
  Variable View.
• Output Viewer opens automatically when you
  execute an analysis or create a graph using a
  dialog box or command syntax to execute a
  procedure. The Output Viewer contains the results
  of all statistical analyses and graphical
  displays of data. All output from these commands
  will appear in the Output Viewer.
• Syntax Editor - a text editor where you compose
  SPSS commands and submit them to the SPSS
  processor.
• This document focuses on the methods necessary
  for inputting, defining, and organizing data in
  SPSS.

19
The Data Editor (.sav)

• The Data Editor window displays the contents of
  the working dataset. It is arranged in a
  spreadsheet format that contains variables in
  columns and cases in rows.
• The Data View is the sheet that is visible when
  you first open the Data Editor this sheet
  contains the data.
• The Variable View is the sheet that contains
  information about the variables in the dataset.
• Datasets that are currently open are called
  working datasets all data manipulations,
  statistical functions, and other SPSS procedures
  operate on these datasets.

20

• From the menu in the Data Editor window, choose
  the following menu options
• File ? Open ? Data...
• The Open File dialog box should automatically
  open to the SPSS directory of example files.
  Choose Employee data.sav from the list and click
  Open. Your Data Editor should now look like this

21
The Syntax Editor (.sps)

• This SPSS training focuses on the use of dialog
  boxes to execute procedures however, there are
  at least two reasons why you should be aware of
  SPSS syntax, even if you plan to primarily use
  the dialog boxes.
• First, not all procedures are available through
  the dialog boxes. Therefore, you may occasionally
  have to submit commands from the Syntax Editor.
• Second, the Syntax Editor is a useful way to save
  a log of what you have done, and to re-run what
  you have done at a later date.

22
The dialog boxes

• The dialog boxes available through the pull-down
  menus have a button labeled Paste, which will
  print the syntax for the procedure you are
  running in the dialog box environment to the
  Syntax Editor. Thus, you can easily generate SPSS
  syntax without typing in the Syntax Editor.
• The following dialog box is used to generate
  descriptive statistics. You can also get this
  dialog box by choosing Analyze ? Descriptive
  Statistics? Descriptives
• then clicking over the two variables using the
  arrow button.

23

• By clicking on the Paste button, the procedure
  that the above dialog box is prepared to run will
  be written in the form of SPSS syntax to the
  Syntax Editor. Thus, clicking the Paste button in
  the above example would produce the following
  syntax
• DESCRIPTIVES   VARIABLESsalbegin salary  
  /STATISTICSMEAN STDDEV MIN MAX .

24
The Output Viewer (.spo)
25

• The left frame of the Output Viewer an outline
  of the objects contained in the window.
• Descriptives in the outline refers to objects
  associated with the descriptive statistics.
• The Title object refers to the bold title
  Descriptives in the output.
• The Active Dataset object refers to the line in
  the output that designates which dataset was used
  to run the analysis.
• The Descriptive Statistics refers to the table
  containing descriptive statistics.
• The Notes icon has no referent in the above
  example, but it would refer to any notes that
  appeared between the title and the table.

26
Control the Ouput the Edit menu and Options
menu
27
references

• Categorical Data Analysis Using the SAS System,
  2nd edition SAS Institute, 2000, M.E Stokes, C.
  S. Davis, G.G Koch ISBN 1580257107
• Basic and clinical Biostatistics
• ISBN-139780071410175
  
• ISBN 0071410171
• An Introduction to Categorical Data Analysis, 2nd
  edition by A. Agresti (John Wiley Sons) 2007
  ISBN 0471-22618-1
• SPSS for windows step by step A simple guide and
  reference,13.0 update.
• ISBN-13 9780205480715

28
Thank you!!