1. Chapter 7: Control Techniques
October 23, 2012

2. Roadmap
• Discuss Reflection Assignment #2
– Due Nov. 1 via BlackBoard
• Coming Up: Exam #3 next Tuesday, Oct. 30
• Quick review
• Chapter 7

3. Factorial Designs
• When to use
• Main and interaction effects
• Effect patterns in data displays

4. Overview
Control Techniques
• Control at the beginning of experiment
– Random assignment Create equivalent
– Matching experimental groups
• Control during the experiment
– Counterbalancing Treat groups
the same
– Controlling for participant effects during the
– Controlling for experimenter effects experiment

5. Methods for Matching Participants
• Holding variables constant
• Building the extraneous variable into the
design
• Yoked control
• Equating participants

6. Matching by Holding Variables
Constant
• Hold extraneous variable constant for all
groups in the experiment
• All participants in each treatment group will
have same degree or type of extraneous
variable
• Requires selection criteria for participant
sample

7. Build Extraneous Variable into the
Research Design
• Especially useful if you are interested in:
– Differences produced by the levels of the
extraneous variable
– Interaction between levels of IV and levels of
extraneous variable
• Sound familiar?
– What kind of research design would this be?

8. Example: Effect of a study skills intervention
on grades in a Quantitative Methods course
Intensive tutoring program Study packets (usual)
But the literature suggests that learning style may affect how students
respond to different study skills training methods.
Learning style is a potential confounding extraneous variable….but we can
build it in to the design!
Learning Style
Visual Auditory Kinesthetic
Intervention
Intensive
tutoring
program
Study packets

9. Matching by Equating Participants
Precision control
• Match each participant in experimental group
with a participant in control group on
variable(s) of concern
• Example: Scholtz (1973) compared defense
styles in suicide attempt vs. no attempt

10. Matching by Yoked Control
• Match participants on the basis of the
sequence of administering an event
• Each control participant is “yoked” to an
experimental participant
• Controls for the possible influence of
participant-controlled events
• Example: Sklar & Anisan (1979)
– stress and immune response

11. www.xkcd.com
CONTROL DURING THE EXPERIMENT

12. Control During the Experiment
• Must treat the different groups in the same
way during the experiment, except for
administration of the IV
• Why is this important?

13. • Control during the experiment
– Counterbalancing within-participants designs
– Controlling for participant effects
– Controlling for experimenter effects

14. Counterbalancing
• Used to control for sequencing effects in a
repeated measures (aka within-subjects) design
• Sequencing effects occur when participants
participate in more than one condition
• Two types of sequencing effects
– Order effect
– Carryover effect

15. Counterbalancing
• Order effect
– “Arises from the order in which treatment
conditions are administered to participants”
– Treatment/experiment exposure can influence
performance on subsequent tasks and measures
– Most common:
• Practice effect
• fatigue

16. Counterbalancing
• Carryover effect
– Performance in one condition is affected by the
condition that precedes it
– Example: Participant receives active drug before
the placebo, and the residual effects are still
present during placebo condition
• One strategy: “wash-out” period

17. Counterbalancing Techniques
• Randomized counterbalancing individual
• Intrasubject counterbalancing
• Complete counterbalancing group
• Incomplete counterbalancing

18. Types of Counterbalancing
• Randomized counterbalancing
– Sequence order is randomly determined for each
individual
– Just like random assignment to conditions
– You do not decide the sequence, must use a random process to decide
order

19. Types of Counterbalancing
• Intrasubject Counterbalancing
– When each participant receives all levels of the IV
more than one time
– Have participants take conditions first in one
order, then again in the reverse order
– Disadvantage: Participant burden is increased
• Must complete each condition more than once

20. Types of Counterbalancing
• Complete and Incomplete counterbalancing
– Group counterbalancing
– Determine possible sequences
– Randomly assign to sequence such that sequences
are distributed across groups rather than
individuals

21. Participant Effects
• Demand characteristics
– Cues in the experiment that might influence
participant behavior
• Positive self-presentation
– Motivation for participants to present themselves
in a positive light

22. Control of Participant Effects
• Deception
– Giving participants a bogus rationale for the
experiment
• Can range from minor deceit to more
elaborate schemes
Classic example: Milgram studies

23. Control of Participant Interpretation
• Previously discussed methods provide good
control for demand characteristics of study
• But how do we know what participants’
perceptions of our study are?
– Ask them!

24. Control of Participant Interpretation
• Retrospective Verbal Reports: after experiment
– Disadvantage: Participants might forget
perceptions by the end of the study
• Concurrent Verbal Reports: during experiment
– Solomon’s Sacrifice Groups
– Concurrent probing
– Think-aloud technique

25. Control of Experimenter Effects
• Experimenter effects
– The biasing influence that can be exerted by the
experimenter
• Data Recording errors--control
– Be careful
– Multiple observers and data recorders
– Keep experimenter blind to participants’ conditions
– Electronic or mechanical data recording*

26. Control of Experimenter Effects
• Experimenter Attribute Errors
– Some experimenters, because of their attributes,
produce more of an effect than other
experimenters
• Control technique:
– Experimenters should run all conditions
– Experimenters same on characteristics that might
affect DV

27. Control of Experimenter Effects
• Experimenter Expectancy Errors
– Experimenter’s expectations about the study
influence participant responses
Control techniques:
• Blind technique
• Partial blind technique
• Automation

28. Ideal:
Control Participant AND Experimenter Effects
• Double-Blind Placebo Method
– Participant and experimenter blind to condition
– “Devise manipulations that appear essentially
identical to research participants in all conditions”
– Example: Compare drug to identical sugar pill
(placebo)