1. Why Psychologists Conduct Experiments
Multimethod approach
Compliments observational and survey research
Seek convergent validity for research findings across methods
Third goal of psychological research
Explanation
Examine the causes of behavior
Test
Hypotheses derived from theories
Effectiveness of treatments and programs 1

2. Experimental Research
A “true” experiment must include
Independent variable (IV)
Dependent variable (DV)
Independent Variable
Manipulated (controlled) by experimenter
At least 2 conditions (levels)
“Treatment” and “Control”
Dependent Variables
Measured by experimenter
Used to determine effect of IV
Typically researchers measure several dependent variables to assess effect of IV. 2

3. Experimental Control and Internal Validity
are able to confidently state that the independent variable caused differences between groups on the dependent variable (i.e., a causal inference).
must be able to rule out alternative explanations
For example: Pennebaker (1989) “inhibition theory”
students who write about emotional experiences
are healthier
more academically successful
compared to students who write about superficial experiences
How do we know the emotional writing caused them to be healthier and academically successful (i.e., a causal inference?)
What are some alternative explanations?
How does this differ from external validity?

4. Internal Validity
Differences in performance (DV) can be attributed unambiguously to effect of independent variable (IV)
Three conditions to make a causal inference:
Covariation:
must observe a relationship between the independent and dependent variables.
participants who write about emotional events have better health and academic outcomes than participants who write about superficial events
Time-order relationship:
cause precedes the effect
writing about emotional events comes before the beneficial health and academic outcomes
Elimination of plausible alternative causes:
Using control techniques to rule out other possible causes for the outcome.

5. Causal Inferences : Time-Order Relationship
Manipulation of IV can establish the time-order relationship between the IV and the DV
Establishing a time-order relationship can be tricky.
If participants in the emotional writing condition
were healthier before writing
more academically successful before writing
Then the effect precedes the cause
Need to assume the groups are equal before experimental manipulation is given
How can groups be made equal prior to manipulation?

6. Causal Inferences : Eliminating Alternatives
Elimination of plausible Reasonable Alternatives
Only alternatives that fit the research hypothesis
Confounding variables:
When the independent variable of interest and a different, potential independent variable are allowed to covary (go together), a confounding is present.
For example students who write about emotional experiences are also involved in an exercise program
Confounding variables represent alternative explanations for a study’s findings.
An experiment that has a confounding is not internally valid.
An experiment that is free of confoundings has internal validity.

7. Control Techniques To eliminate alternative explanations
Holding conditions constant
all other possible experiences to be constant across the groups
differ only in terms of the independent variable
same as not having any confoundings in the experiment
for example, what did Pennebaker and Francis do?
Balancing
characteristics of participants cannot be held constant
for example, some participants are healthier or smarter
on average, the participants in each condition are essentially the same before the experiment begins
the groups in the experiment are equally healthy, smart, motivated, conscientious, etc. prior to the independent variable manipulation
Proper use of control techniques increases internal validity

8. Independent Groups Designs(Between-Subjects)
Different individuals participate in each condition of the experiment.
No overlap of participants across conditions
Three types based on Techniques for Balancing
Random groups design
Matched groups design
Natural groups design 8

9. Individuals are randomly assigned to conditions “levels” of the IV.
Random Groups Designs
Individuals are randomly assigned to conditions “levels” of the IV.
Need at least two conditions but there can be many more.
Logic of causal inference
When groups are equivalent at the beginning of an experiment (through balancing)
conditions are held constant
any differences among groups on dependent variable are caused by the manipulated independent variable. 9

10. IV: version of picture book with 3 levels
Example: Body Image Among Young Girls (Dittmar, Halliwell, & Ives, 2006)
Research prediction
Young girls exposed to a very thin body image will experience greater body dissatisfaction than young girls who are exposed to realistic or neutral body images.
IV: version of picture book with 3 levels
Barbie (very thin body image)
Emme (realistic body image)
Neutral (no body images) 10

11. Body Image Among Young Girls, cont.
Dependent Variables
Several measures of body image and body dissatisfaction
Child Figure Rating Scale
Rate perceived actual body shape
Rate ideal body shape
Obtain difference score
Negative score: desire to be thinner 11

12. Holding conditions constant
Control Techniques
Manipulation
IV: participants in the conditions have different experiences
Example: Barbie, Emme, or neutral images
Holding conditions constant
IV is only factor that differs systematically across groups
Dittmar et al. (2006) held constant
All girls listened to same instructions and story
All completed the same questions after the story 12

13. Control Techniques, continued
Balancing
Random assignment to conditions balances subject characteristics, on average.
Groups are equivalent prior to IV manipulation.
All subject variables are balanced.
Body weight, number of Barbie dolls, preexisting levels of body dissatisfaction, etc. 13

14. Block Randomization
Block Randomization is a technique used to assign participants randomly to conditions.
A “block” is a random order of all conditions in the experiment.
For example, three conditions (A, B, and C) might be randomly ordered as B C A.
The first participant would be in condition B, the second in condition C, and the third in Condition A.
Generate another random order of the block (e.g. A C B).
Assign the next 3 participants to conditions A, C, and B, respectively.
Continue until the goal for number of participants in each condition are met (e.g., 10 participants in each condition).

15. Block Randomization with five levels “conditions” of an independent variable

16. Random Groups Designs, continued
Block randomization
Advantages of block randomization:
Creates groups of equal size for each condition
Controls for time-related events that occur during the course of an experiment:
Natural changes in experimental conditions, experimenters, and participants that occur over time are balanced across the conditions of the experiment.
Some experiments may take several months to complete
As with all random assignments, block randomization balances subject characteristics across the conditions of the experiment. 16

17. Threats to Internal Validity
The internal validity of an experiment
the ability to make a causal inference about the effect of an independent variable on a dependent variable
is threatened when:
intact groups are used,
extraneous variables are not controlled,
selective subject loss occurs, and
demand characteristics and experimenter effects are not controlled.

18. Threats to Internal Validity
Intact Groups
Intact groups are formed prior to the start of an experiment
Examples:
Different sections of introductory psychology
why are students in the 8:30 vs 10:30 section
children in different classrooms
different departments within an organization
Individuals are not randomly assigned to intact groups. As a result, individual differences among groups threaten the validity of the experiment.
When groups, rather than individuals, are randomly assigned to conditions, subject characteristics are not balanced.

19. Threats to Internal Validity
Extraneous Variables
Practical considerations when conducting an experiment may confound an experiment — these are referred to a extraneous variables.
Examples: number of participants in each session, different experimenters, different rooms in which an experiment is conducted
Extraneous variables are controlled using balancing or holding conditions constant.
Balancing occurs when the two experimenters conduct each condition but are randomly assigned to administer a condition at any particular time.
Holding conditions constant would involve using only one of the experimenters. This experimenter would test participants in both the treatment and control conditions.

20. Threats to Internal Validity
Subject Loss (Attrition)
Subject loss occurs when participants fail to complete an experiment.
Selective subject loss occurs when
(1) Participants are lost differentially across the conditions of the experiment (e.g., more participants are lost in the treatment condition compared to the control condition), for example exercise to reduce weight
(2) When some characteristic of the participant is responsible for the loss (e.g., subject characteristics such as personality, intelligence, physical characteristics), and
(3) The subject characteristic is related to the dependent variable in the experiment.
This challenges the internal validity of an experiment if the equivalent groups formed at the beginning of an experiment are no longer equivalent at the end of the experiment because of attrition.

21. Threats to Internal Validity
Subject Loss (Attrition)
Example: Suppose a treatment for depression is compared to a control condition (no treatment).
Selective subject loss might occur if participants are more likely to drop out of the control condition than the treatment condition (or vice versa).
Any differences in depression symptoms (the dependent variable) at the end of the experiment might be due to the treatment or to selective subject loss in the experiment.
Mechanical subject loss occurs when equipment failure or experimenter error results in a participant’s inability to complete the experiment.
Often, mechanical subject loss occurs due to chance factors and is likely to occur equally across the conditions of an experiment.

22. Threats to Internal Validity
Demand characteristics are the cues and other information that participants use to guide their behavior in a psychological study.
Example: In a drug-treatment study, demand characteristics suggest to participants that they will improve as a result of the drug.
Thus, participants may expect to improve when given the treatment.
These expectancies (rather than the drug) may cause participants to improve.
A placebo control group is used to assess whether participants’ expectancies contribute to the outcome of an experiment.
Participants who receive a placebo may believe they are receiving an effective drug treatment; this controls for their expectations regarding the effectiveness of treatment.
If participants who receive the actual drug improve to a greater extent than participants who receive a placebo, we can be more confident that the drug produced the beneficial outcomes rather than participants’ expectancies.

23. Threats to Internal Validity
Experimenter effects
refer to potential biases that occur when experimenters’ expectancies regarding the outcome of the experiment influence their behavior toward participants in different conditions.
can be controlled by keeping experimenters and observers unaware of the hypotheses or expected results
this is referred to as keeping experimenters “blind.”
A double-blind experiment
refers to procedures in which both the participants and the experimenters/observers are unaware of which condition is being administered.
control for both demand characteristics and experimenter effects.
allow researchers to rule out participants’ and experimenters’ expectancies as alternative explanations for a study’s outcome.

24. Establishing the External Validity of Experiments
Conclusions from an experiment
Can they be generalized beyond a specific experiment to other
Individuals
Settings
Conditions
Any individual experiment has limited external validity because
Control from holding constant increases internal validity but can reduce the external validity
However reduced external validity is OK when there is good internal validity

25. External Validity of Experiments
For Example: Research with college student on cognitive mechanisms of decision making
Would this produce low external validity?
Are college students all that different from other people?
The answer to this question likely depends on the research question.

26. Establishing external validity of experiments
Generalize beyond the scope of a specific experiment
Example: Do insults provoke aggression
Across several experiments include characteristics of the
Situations: in private, in public
Settings: in classroom, at a bar
Populations: young children, adolescents, adults
Compare findings from a series of experiments
Do different situations, settings or population produce the similar results?
The goals is not to have external validity but to identify the extend of external validity
We do not expect some behaviors such as aggression to be similar across all situations, settings or populations.
This the partial replication approach

27. Establishing External Validity of Experiments
External validity of findings are established when the findings are replicated
Field experiments are a way to increase the external validity of laboratory findings by replicating an experiment in a real-world setting.
Partial replications are common: Research findings generalize when a similar result occurs when slightly different experimental procedures are used in a subsequent experiment.
Psychologists also make use of conceptual replications.
We are more interested in relationships among variables considered at the conceptual level rather than in specific conditions, settings, and participants.
Different operational definitions for concepts may be used in replications to fit the particular population or setting.

28. Additional Independent Groups Designs
Random assignment requires large samples (10-15 per group) to balance participants’ characteristics across the conditions of the experiment.
When only small samples are available, a researcher may choose the matched groups design.
select the one or two individual differences variables related to the research question for matching.
participants should be matched on
dependent variables
or variables very similar to the dependent variable
matching variables are the characteristics that definitely should be equivalent before the experiment
matched pairs of participants are randomly assigned to conditions

29. Matched Groups Design
Example: Effects of a relaxation treatment for high blood pressure
Independent Variable: Treatment vs. Placebo
Dependent Variable: Blood pressure
Suppose you don’t have enough participants for random assignment to create equivalent groups (only 16 participants).
What would you want to match? That is, what feature or characteristic of participants in the two groups should be equivalent before the experiment begins?
Blood pressure.
Why blood pressure?
Suppose that participants in the treatment group had lower blood pressure before they start the experiment.
Any differences in blood pressure (DV) between the treatment and the placebo group at the end of the experiment might be due to the different blood pressures at the beginning of the experiment.

30. Matching Participants: Example
Beginning
Name Blood Pressure
Susan 160 / 110
Janet 150 / 120
Philip 160 / 110
Barbara 180 / 130
John 180 / 130
Benjamin 170 / 120
Catherine 150 / 120
William 170 / 120
Assignment to conditions:
Treatment matched to Control
Philip Susan
Janet Catherine
Barbara John
William Benjamin
Average Blood Pressure:
Treatment Control
165 / / 120

31. Important points about matching:
Matched Groups Design
Important points about matching:
participants are matched only on some variables
the groups may differ on other important variables.
These differences may be alternative explanations for the study’s results.
Can use more then one variable for matching
However, the more characteristics you try to match on, the harder it will be to match participants.

32. Natural Groups Designs
Psychologists’ research questions often ask how individuals differ, and how these individual differences are related to important outcomes.
Individual differences variables (subject variables) refer to characteristics or traits that vary across individuals. Examples:
Physical Characteristics: sex, race
Social (Demographic) Characteristics: ethnicity, religious affiliation, marital status
Personality Characteristics: extraversion, emotional stability, intelligence
Mental Health Characteristics: depression, anxiety, substance abuse, disordered thinking

33. Natural Groups Designs
For example,
do men and women differ in what they seek in intimate relationships?
Researchers can not randomly assign participants to these groups (male/female).
When a researcher investigates an independent variable in which the groups (conditions) are formed naturally, we say a “natural groups design” is used.

34. Natural Groups Designs
For example,
Suppose we want to compare occupational functioning of schizophrenics and normal controls (non-schizophrenics).
What is the independent variable?
Natural groups variable: schizophrenic vs. non-schizophrenic participants
What is the dependent variable?
Occupational functioning

35. Natural Groups Designs
Causal inferences and natural groups designs:
Researchers can’t make a causal inference when a natural groups design is used.
For example, suppose schizophrenics have poorer occupational functioning than the normal participants.
Can we say that schizophrenia caused this poorer occupational functioning?
What part of causal inference is missing ?