Transcript Probability - University of Central Missouri

EXPERIMENTAL DESIGNS
 Criteria
for Experiments
 Independent, Dependent, and
Confounding Variables
 Types of Experimental Designs
 Threats to Internal Validity
 Threats to External Validity
Criteria For Experimental Designs
Cause: experimenter manipulates a
variable
 Comparison: more than one condition
 Control: extraneous variables are
eliminated

Independent Variable
 variable


manipulated by the experimenter
levels
conditions
Dependent Variable
 variable
measured to assess the effect
of the independent variable
Confounding Variable
variable other than IV and DV which
changes between conditions
 control variable: potential confounding
variable that is controlled

Types of Experiments



between subjects
matched groups
within subjects
Threats to Internal Validity:
Individual Differences
 Systematic
differences between
individuals in different groups
 Strategies



random assignment
matched groups
within subjects design
History
 Events
outside the experiment
 Most likely when conditions are measured
at different times with long delays
 Strategies


Decrease time between conditions
Add a control group measured at same times
Maturation
Physical changes related to aging
 Particular problem for within-subjects
designs
 Strategies



decrease time between measurements
add a control group measured at same times
Instrumentation
Changes in the measuring instrument or
equipment
 Strategy


Use standardized administration
Attrition
 Participants
drop out of the study at
different rates for the different conditions
 Strategies


Check attrition rates across groups
Compare participants who drop out to those
who stay in
Diffusion of Treatment
 Information
about the purpose of the study
is shared with future participants
 Strategies


Short time span between participants
Use debriefing to request that participants do
not share information about the study
Demand Characteristics
Cues from the experimenter or research
procedure about what behavior is desired
 Strategy


Single-blind procedure
Experimenter Effects
Experimenter’s expectations affect
measurements
 Strategy


Double-blind procedure
Floor and Ceiling Effects

Measuring instrument is not sensitive
enough


Floor effects
Ceiling effects
 Strategy

Check sensitivity of instrument prior to
experiment
Regression to the Mean
 When
measured twice, scores on the
second testing tend to be closer to the
mean
 Statistical phenomenon due to chance
 Strategy


Don’t select participants for groups based on
extreme scores
Use an equivalently selected control group
that does not get the treatment
Order Effects
 Also
called Testing or Repeated Testing
 Effects of repeated measurements



Fatigue effects
Practice effects
Carryover effects
 Strategy

Counterbalance order of conditions
How Counterbalancing Works
 Change
the order of conditions
 Order effects will still exist but will affect
all conditions equally
 This prevents order effects from being
confounding
Complete Counterbalancing
Each possible order of conditions is
used for an equal number of subjects
 If your conditions are A,B, and C, 1/6 of
participants will get each order:

ABC
ACB
BAC
CAB
CBA
BCA
Latin Square Counterbalancing
Each condition is presented in each
position for an equal number of subjects
 Controls for practice and fatigue effects

Example Latin Square
1/4 get
1/4 get
1/4 get
1/4 get
1st
A
B
C
D
2nd
B
C
D
A
3rd
C
D
A
B
4th
D
A
B
C
Balanced Latin Square
Latin square with additional requirement
that each condition precedes and follows
every other condition equally often
 Controls practice and fatigue effects
 Controls simple carryover effects
(involving effect of a single condition)

Balanced Latin Square
1/4 get
1/4 get
1/4 get
1/4 get
1st
A
B
C
D
2nd
B
C
D
A
3rd
D
A
B
C
4th
C
D
A
B
Randomized Counterbalancing
 Used
when there are multiple stimuli
tested for each condition
 Put the stimuli in random order for each
participant
Threats to External Validity

Unrepresentative Sample



use random or stratified random sampling
do exact or systematic replications
Artificiality


use a more realistic setting
do systematic or conceptual replications