An Interactive Tutorial for SPSS 10.0 for Windows©
Analysis of Covariance
(Regression Approach)
by
Julia Hartman
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© Copyright 2000, Julia Hartman
1
ANCOVA (Regression Approach):
Introduction
Analysis of Covariance (ANCOVA) is used:
• To assess the joint significance of predictors on a
continuous outcome (GLM approach)
• To generate prediction equations for various levels
of a categorical predictor (regression approach)
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© Copyright 2000, Julia Hartman
2
ANCOVA (Regression Approach):
Introduction
This tutorial uses the regression approach to
ANCOVA to determine if type of
undergraduate major and year of matriculation
can be used to predict MCAT scores.
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© Copyright 2000, Julia Hartman
3
ANCOVA (Regression Approach):
Introduction
• Dependent variable
 nmtot1: MCAT total, 1992-present, most recent)
• Independent variables
 matyr: Year of matriculation
 Indicator (dummy) variables computed for
undergraduate major
 dmajor1
 dmajor2
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© Copyright 2000, Julia Hartman
4
ANCOVA (Regression Approach):
Introduction
To correctly use the regression approach to ANCOVA
requires computing indicator (dummy) variables for different
values of categorical variables.
Variables can be computed by using:
• Transform procedure (see Computing Variables tutorial)
• SPSS syntax (see Using Command Syntax tutorial)
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© Copyright 2000, Julia Hartman
5
ANCOVA (Regression Approach):
Introduction
This tutorial uses the dummy variables shown below
to represent the three types of undergraduate majors.
Type of Major
Value of
dmajor1
Value of
dmajor2
Biology/Chemistry
1
0
Other science, health
0
1
Other (non-science)
0
0
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© Copyright 2000, Julia Hartman
6
ANCOVA (Regression Approach):
Starting the Procedure
• In the menu, click
Analyze
© Copyright 2000, Julia Hartman
7
ANCOVA (Regression Approach):
Starting the Procedure
• In the menu, click on
Analyze
• Point to
Regression
© Copyright 2000, Julia Hartman
8
ANCOVA (Regression Approach):
Starting the Procedure
• In the menu, click on
Analyze
• Point to
Regression
• Point to Linear…
© Copyright 2000, Julia Hartman
9
ANCOVA (Regression Approach):
Starting the Procedure
• In the menu, click on
Analyze
• Point to
Regression
• Point to Linear…
… and click.
© Copyright 2000, Julia Hartman
10
ANCOVA (Regression Approach):
Selecting Variables
Choose the variables for
analysis from the list in
the variable box.
Move MATRICULATON
DATE - YEAR, which is
already highlighted, to the
box labeled
Independent(s) by clicking
the arrow.
© Copyright 2000, Julia Hartman
11
ANCOVA (Regression Approach):
Selecting Variables
Scroll down the
variable list,
© Copyright 2000, Julia Hartman
12
ANCOVA (Regression Approach):
Selecting Variables
Scroll down the
variable list, point to
the variable labeled
MCAT TOTAL 1992PRESENT, MOST
RECENT [nmtot1]
© Copyright 2000, Julia Hartman
13
ANCOVA (Regression Approach):
Selecting Variables
Scroll down the
variable list, point to
the variable labeled
MCAT TOTAL 1992PRESENT, MOST
RECENT [nmtot1]
…and click.
© Copyright 2000, Julia Hartman
14
ANCOVA (Regression Approach):
Selecting Variables
Move nmtot1 to the
Dependent box
by clicking the arrow.
© Copyright 2000, Julia Hartman
15
ANCOVA (Regression Approach):
Selecting Variables
Scroll to the bottom
of the list,
© Copyright 2000, Julia Hartman
16
ANCOVA (Regression Approach):
Selecting Variables
Scroll to the bottom
of the list, and click
the dummy variable
dmajor1.
© Copyright 2000, Julia Hartman
17
ANCOVA (Regression Approach):
Selecting Variables
Select both dummy
variables by holding
down the Shift key
and clicking dmajor2.
© Copyright 2000, Julia Hartman
18
ANCOVA (Regression Approach):
Selecting Variables
Move both dummy
variables (dmajor1
and dmajor2) to the
box labeled
Independent(s): by
clicking the arrow.
© Copyright 2000, Julia Hartman
19
ANCOVA (Regression Approach):
Run the Analysis
Click the OK button to
run the ANCOVA
(regression approach).
© Copyright 2000, Julia Hartman
20
ANCOVA (Regression Approach) Output:
Variables Entered
The labels and
format of your
output may be
somewhat different.
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© Copyright 2000, Julia Hartman
21
ANCOVA (Regression Approach) Output:
Model Summary
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© Copyright 2000, Julia Hartman
22
ANCOVA (Regression Approach) Output:
ANOVA
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© Copyright 2000, Julia Hartman
23
ANCOVA (Regression Approach) Output:
Coefficients
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© Copyright 2000, Julia Hartman
24
An Interactive Tutorial for
SPSS 10.0 for Windows©:
ANCOVA (Regression Approach)
Click one of the following:
• Repeat this tutorial
• Return to the list of tutorials
© Copyright 2000, Julia Hartman
25
An Interactive Tutorial for
SPSS 10.0 for Windows©:
ANCOVA (GLM)
Click one of the following:
• Repeat this tutorial
• Return to the list of tutorials
© Copyright 2000, Julia Hartman
26
An Interactive Tutorial for
SPSS 10.0 for Windows©:
ANCOVA (Regression Approach)
Click one of the following:
• Repeat this tutorial
• Return to the list of tutorials
© Copyright 2000, Julia Hartman
27