# Chapter Fourteen - PowerPoint PPT Presentation

PPT – Chapter Fourteen PowerPoint presentation | free to download - id: 560b48-OTI3O

The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
Title:

## Chapter Fourteen

Description:

### Title: Chapter Two Author: Instructional Design Last modified by: pe Created Date: 1/10/2003 6:41:18 AM Document presentation format: On-screen Show – PowerPoint PPT presentation

Number of Views:27
Avg rating:3.0/5.0
Slides: 28
Provided by: Instruction162
Category:
Tags:
Transcript and Presenter's Notes

Title: Chapter Fourteen

1
Chapter Fourteen
• Designing and Conducting Experiments with
Multiple Independent Variables

PowerPoint Presentation created by Dr. Susan R.
BurnsMorningside College
2
Experimental Design Doubling the Basic Building
Block
• A factorial design gives us the power we need to
devise an investigation of several factors (IVs)
in a single experiment.

3
Experimental Design Doubling the Basic Building
Block
• Factors
• Synonymous with IVs
• Independent variables (IVs)
• Stimuli or aspects of the environment that are
directly manipulated by the experimenter to
determine their influences on behavior.

4
Experimental Design Doubling the Basic Building
Block
• Factorial designs are the lifeblood of
experimental psychology because they allow us to
look at combinations of IVs at the same time, a
situation that is quite similar to the real
world.
• A factorial design is more like the real world
because there are probably few, if any,
situations in which your behavior is affected by
only a single factor at a time.

5
Experimental Design Doubling the Basic Building
Block
• This figure demonstrates a graphical display of
the simplest possible factorial design (2 x 2).
• This 2 X 2 shorthand notation tells us that we
are dealing with a design that has two factors
(IVs) because there are two digits given and
that each of the two factors has two levels
because each digit shown is a two.

6
How Many IVs?
• The factorial design gets its name because we
refer to each IV as a factor.
• Multiple IVs yield a factorial design.
• Theoretically, there is no limit to the number of
IVs that can be used in an experiment.
• Practically speaking, however, it is unlikely
that you would want to design an experiment with
more than two or three IVs.

7
How many Groups or Levels?
• Once you have two or more IVs, you will use a
factorial design.
• The number of levels of each factor is
unimportant at this point.

8
Experimental Design Doubling the Basic Building
Block
9
How many Groups or Levels?
• Various factors are often designated by letters,
so the first factor is labeled Factor A, the
second as Factor B, and so on.
• The levels within a factor are often designated
by the letter that corresponds to the factor and
a number to differentiate the different levels.
• Thus, the two levels within the first factor
would be labeled A1 and A2.

10
How many Groups or Levels?
• Main effect
• A main effect refers to the sole effect of one IV
in a factorial design.
• Interaction
• Another benefit that we get from doing an
factorial experiment is the ability to examine
potential interactions between the two IVs.
• Significant interactions are found when the
effects of one IV change as the level(s) of the
other IV changes. In other words, the effects of
one IV depend on the particular level of another
IV.
• A simple way to discern an interaction is to look
at your findings graphically. If the lines on the
graph are not parallel, then there likely is a
significant interaction.

11
Psychological Detective
• Can you interpret the main effects in the figure
below. Did customer hearing having an effect? Did
the salesclerk sex have any effect? Study the

12
Assigning Participants to Groups
• We have two options for this assignment
independent groups or correlated groups.
• Factorial designs in which both IVs involve
random assignment may be called between-subjects
factorial designs or completely randomized
designs.
• This decision is not as simple as in the
two-group and multiple-group designs, each of
• All IVs could have participants assigned
randomly or in a correlated fashion, or we could
have one IV with independent groups and one IV
with correlated groups. This possibility is
referred to as mixed assignment.

13
Assigning Participants to Groups
• Mixed assignment
• A factorial design that has a mixture of
independent groups for one IV and correlated
groups for another IV.
• In larger factorial designs, at least one IV has
independent groups and at least one has
correlated groups (also known as mixed groups).

14
Nonrandom Assignment to Groups
• In this section, we deal with factorial designs
in which participant groups for all IVs have
been formed through nonrandom assignment.
• We refer to such designs as completely
within-groups (or within-subjects) designs.
• We may want to resort to nonrandom assignment in
order to assure the equality of participant
groups before we conduct the experiment.

15
Nonrandom Assignment to Groups
• Matched Pairs or Sets
• Matching can take place in either pairs or sets
because factorial designs can use IVs with two
or more levels.
• The more levels an IV has, the more work matching
for that variable takes.
• The more precise the match that is necessary, the
more difficult matching becomes.

16
Nonrandom Assignment to Groups
• Repeated Measures
• In a completely within-groups experiment using
repeated measures, participants would take part
fully and completely.
• Participants take part in every possible
treatment combination.
• This requirement makes it difficult or impossible
to conduct an experiment with repeated measures
on multiple IVs.
• The smaller the design, the more feasible it is
to include all participants in all conditions of
the experiment.

17
Nonrandom Assignment to Groups
• Natural Pairs or Sets
• Using natural groups in a totally within-subjects
design has the same difficulties as the matched
pairs or sets variation of this design, but it
would be even harder.
• The difficulty lies in being able to find an

18
Nonrandom Assignment to Groups
• Mixed Assignment to Groups.
• Mixed assignment designs involve a combination of
random and nonrandom assignment, with at least
one IV using each type of assignment to groups.
• In a two-IV factorial design, mixed assignment
involves one IV with random assignment and one IV
with nonrandom assignment.
• In such designs, the use of repeated measures is
probably more likely than other types of
nonrandom assignment.
• Mixed designs combine the advantages of the two
types of designs.
• The conservation of participants through the use
of repeated measures for a between-subjects
variable makes for a popular and powerful design.

19
Comparing the Factorial Design to Two-Group and
Multiple-Group Designs
• Two-group designs are ideal for a preliminary
investigation of a particular IV in a
presence-absence format.
• The multiple-group design may be used to conduct
more in-depth investigations of an IV that
interests us.
• We took the basic two-group design and extended
it to include more levels of our IV.
• We can make the same type of extension with
factorial designs.
• Just as with the multiple-group design, there is
no limit to the number of levels for any IV in a
factorial design.
• The number of levels of the IVs can be equal or
unequal.
• Interaction effects must be interpreted in
factorial designs but not in two-group or
multiple-group designs.
• A good rule of thumb to follow is to choose the
simplest research design that will adequately

20
Experimental Questions
• Factorial designs provide considerable
flexibility in devising an experiment to answer
• The number of questions we can ask in a factorial
experiment increases dramatically, but.
certain that the questions coordinate with each
otherexperimental questions should not clash.
• (e.g., it would not make sense to propose an
experiment to examine the effects of self-esteem
and eye color on test performance)

21
Control Issues
• We need to consider independent versus correlated
groups in factorial designs.
• A complicating factor for factorial designs is
that we need to make this decision (independent
vs. correlated groups) for each IV we include in
an experiment.

22
Practical Considerations
the bare minimum necessary to answer the
question(s) that most interest(s) you.
• Bear in mind that you are complicating matters
when you add IVs and levels.
• Remember the principle of parsimony mentioned in
Chapter 10 and the KISS principle (Keep It Simple
Stupid).

23
Variations on Factorial Designs
• Comparing Different Amounts of an IV
• When you add a level to an IV in a factorial
design, you add several groups to your
experiment because each new level must be added
under each level of your other independent
variable(s).

24
Comparing Different Amounts of an IV
• When you add a level to an IV in a factorial
design, you add several groups to your
experiment because each new level must be added
under each level of your other independent
variable(s).
• For example, expanding a 2 X 2 to a 3 X 2 design
requires 6 groups rather than 4.
groups in a multiplicative fashion.

25
Using Measured IVs
• Ex post facto research
• A research approach in which the experimenter
cannot directly manipulate the IV but can only
classify, categorize, or measure the IV because
it is predetermined in the participants (e.g., IV
sex).

26
Using Measured IVs
• Using a measured rather than a manipulated IV
results in ex post facto research.
• Without the control that comes from directly
causing an IV to vary, we must exercise extreme
caution in drawing conclusions from such studies.
• We can develop an experiment that uses one
manipulated IV and one measured IV at the same
time.

27
Dealing with More than Two IVs
• Designing an experiment with more than two IVs
is probably the most important variation of the
factorial design.
• The simplest possible factorial design with three
IVs (often referred to as a three-way design)
has three IVs, each with two levels.
• This design represents a 2 X 2 X 2 experiment.
• This design would require eight different groups
if it is planned as a completely between-groups
design.