1. 7
Control Techniques in Experimental Research

2. Introduction Points to note
random selection rarely used – researchers focus on the independent variable
purposive and convenience samples typically used
external validity increased by replication
For the rest of this chapter, assume the researcher already has a sample and our focus will be on control techniques

3. Introduction

4. Goal of Experimentation
Identify the causal effect of the independent variable (IV) on the dependent variable (DV)
must have internal validity to do this
requires control of extraneous variables
eliminate differential influence – confounds

5. Random Assignment A control technique to equate groups of participants
accomplished by ensuring that every member has an equal chance of being assigned to any group
Provides maximum insurance that groups are equal
Eliminates systematic differences between groups
Doesn’t eliminate extraneous variables, but randomly distributes them across groups
The most important and powerful control technique

6. Random Assignment Example

7. Matching
Use of any of a variety of techniques to equate participants in the treatment groups on specific variables
should be done with variables thought to be related to the IV or may confound IV
e.g., intelligence, age, gender
Advantages of matching
controls for the variables on which participants are matched
increases the sensitivity of the experiment

8. Matching Techniques Holding variables constant example disadvantages
gender and conformity study – using only females
disadvantages
restricts the population size
restricts generalization to the type of participants in the study

9. Matching Techniques
Building the extraneous variable into the research design (blocking)
make the extraneous variable another IV in the study
should be used only when you are interested in the effect of the extraneous variable

10. Matching Techniques Yoked control
matches participants on the basis of the temporal sequence of administering an event
Example
research question – a researcher wants to know the effect of students having the freedom to choose snack breaks on their classroom productivity
each control participant is “yoked” to an experimental participant
experimental participant takes a self-chosen snack break
the control “yoked” participant is given a snack break by the teacher

11. Matching Techniques Matching by equating participants
individual matching
match case by case then randomly assign to groups
advantage
groups equated on potential extraneous variable
disadvantages
identifying the variables on which to match
matching participants increases as the number of variables on which to match increases
some variables difficult to match
decrease in generalizability of results

12. Individual Matching Example

13. Individual Matching Example
Name IQ
Sara 110
Jane 95
Donald 120
Debbie 105
Jake 120
Jody 105
Kathy 95
Brian 110
Random Assignment to conditions:
Treatment Control
Brian Sara
Jane Kathy
Debbie Jody
Jake Donald
Average IQ by group: 13

14. Counterbalancing
Used only with repeated measures (within participants) designs
All participants receive all treatment conditions

15. Counterbalancing Used to control sequencing effects
two types of sequencing effects
order effects
a sequencing effect arising from the order in which the treatment conditions are administered to participants
e.g., practice, fatigue
carryover effects
a sequencing effect that occurs when performance in one treatment condition affects performance in another treatment condition
e.g., effects of treatment A still affecting participant when engaged in treatment B

16. Counterbalancing Counterbalancing procedures
randomized counterbalancing
sequence of conditions is randomly determined for each participant
example:
IV with three levels
six possible sequences (ABC, ACB, BAC, BCA, CAB, CBA)
each participant randomly assigned to one sequence
can use randomizer.org or a random table of numbers

17. Counterbalancing Counterbalancing procedures
intrasubject counterbalancing
participants take treatments in more than one order
may not be feasible with long treatment sequences
example:
IV with three levels
six possible sequences (ABC, ACB, BAC, BCA, CAB, CBA)
each participant is exposed to all sequences

18. Counterbalancing Counterbalancing procedures complete counterbalancing
all possible sequences of treatment conditions are used
participants randomly assigned to sequence
N! = N multiplied by each number below it
examples:
2! = 2 x 1 = 2
AB, BA
3! = 3 x 2 x 1 = 6
ABC, ACB, BAC, BCA, CAB, CBA
4! = 4 x 3 x 2 x 1 = 24
rarely used with more than 3 conditions because number of possible sequences (N!) is too large

19. Counterbalancing Counterbalancing procedures
incomplete counterbalancing
most commonly used technique
not all possible sequences are used
criteria – for sequences enumerated
each treatment condition must appear an equal number of times in each ordinal position and
each treatment condition must precede and be followed by every other condition an equal number of times
sequences determined by formula
1, 2, n, 3, (n-1), 4, (n- 2), 5

20. Incomplete Counterbalancing Example

21. Counterbalancing Differential carryover
a treatment condition affects participants’ performance in a later condition in one way and in another way when followed by a different condition
example
the carryover from treatment A is 4 units when it is immediately followed by treatment B, but the carryover from treatment A is 2 units when it is immediately followed by treatment C
if suspected, don’t use repeated measures

22. Control of Participant Effects
Double-blind placebo method
neither the experimenter nor the research participant is aware of the treatment condition administered to the participant
Deception
omission of or altering the truth of information given to the participant during a research study
used when there is no other way to gain the knowledge and risk does not outweigh the benefit of the information
must keep the false information constant for all participants

23. Control of Participant Effects
Control of participant interpretation
techniques used to gain insight into participants’ perceptions of experiment
retrospective verbal report
an oral report in which the participant retrospectively recalls aspects of the experiment
questions to ask
what did the participant think the experiment was about?
what did he or she think the experimenter expected to find?
what type of response did the participant attempt to give, and why?
how does the participant think others will respond in this situation?

24. Control of Participant Effects
Control of participant interpretation
concurrent verbal reports
a participant’s oral report of the experiment, which is obtained as the experiment is being performed
sacrifice groups
groups of participants who are stopped and interviewed at different stages of the experiment
concurrent probing
obtaining a participant’s perceptions of the experiment after completion of each trial
think-aloud technique
a method that requires participants to verbalize their thoughts as they are performing the experiment

25. Control of Experimenter Effects
Control of recording errors
make researchers aware of making careful observations
may require training of researcher before data collection
use multiple data recorders (e.g., video cameras, computers) or observers
have participants make responses on a computer
Control of attribute errors
referring to attributes of the experimenter
use the same experimenter in all treatment conditions unless the treatment condition interacts with attributes

26. Control of Experimenter Expectancy
Control of experimenter expectancies
blind technique
a method whereby knowledge of each research participant’s treatment condition is kept from the experimenter
e.g., double-blind procedure
partial blind technique
a method whereby knowledge of each research participant’s treatment condition is kept from the experimenter through as many stages of the experiment as possible
automation
the technique of totally automating the experimental procedures, so that no experimenter-participant interaction is required