1 the experiment chapter 7. 2 experiments simple social experiments allow us to test targeted...
TRANSCRIPT
1
The ExperimentChapter 7
2
Experiments Simple social experiments allow us to test
targeted hypotheses about a specific social process
Experiments gives us clear evidence about a particular causal relationship
Social experiments in education, criminal justice, journalism, marketing, nursing, political science, psychological social work, and sociology use the same basic logic that guides natural science experiments
3
DOING EXPERIMENTS IN EVERYDAY LIFE
An experiment refers to two basic situations before-and-after comparison: you modify
something and then compare an outcome to what existed before the modification
side-by-side comparison: you have two similar things, and then you modify one but not the other and compare the two
4
You do three things in an experiment:
1) Start with a cause-effect hypothesis
2) Modify a situation or introduce a change
3) Compare outcomes with and without modification
5
WHAT QUESTIONS CAN YOU ANSWER WITH THE EXPERIMENTAL METHOD?
Research questions most appropriate for an experiment fit its strengths and limitations, which include: The experiment has a clear and simple logic It has the ability to isolate a causal mechanism It is targeted on two or three variables and is
narrow in scope It is limited by the practical and ethical aspects of
the situations you can impose on humans
6
Comparison is central to experiments
In experimental social research, you want to compare things that are fundamentally alike
To make a valid comparison, you want to compare participants who do not differ with regard to variables that could be alternative explanations to your hypothesis
7
WHY ASSIGN PEOPLE RANDOMLY?
Many experiments use randomization to ensure that participants are sorted into groups in an unbiased way random assignment: sort research participants
into two or more groups in a mathematically random process
8
Random sampling & random assignment When you randomly sample, you use a random
process to select a smaller subset of people (sample) from a larger pool (population)
When you randomly assign, you use a random process to sort a collection of participants into two or more groups
You can both randomly sample and randomly assign this is the ideal in social experiments
9
DO YOU SPEAK THE LANGUAGE OF EXPERIMENTAL DESIGN?
We can divide an experiment into 7 parts Independent variable Dependent variable Pretest Posttest Experimental group Control group Random assignment
10
The independent variable (IV) in experimental research In experiments, the IV is something a
researcher does or introduces, modifying or altering a condition e.g., giving participants different instructions,
showing them different situations, using different physical settings, staging contrived social situations
Also called: the treatment, manipulation, stimulus, or intervention
11
Researchers measure dependent variables (DVs) in many ways
e.g., response times, percent accurate scores, social behaviors, attitudes, feelings and beliefs
12
In many experiments, you measure the DV more than once – before introduction of IV (pretest) and after introduction of IV (posttest)
pretest: a measure of the dependent variable prior to introducing the independent variable in an experiment
posttest: a measure of the dependent variable after independent variable has been introduced in an experiment
13
When introducing an IV, you can use 2 or more groups or a single participant group
independent group design: experimental designs in which you use two or more groups and each gets a different level of the IV
repeated measures design: an experimental design with a single participant group that receives different levels of the independent variable See Example: Was it a Gun or a Tool?
14
Experimental and control groups experimental group: in an experiment with
multiple groups, a group of participants that receives the IV or a high level of it
control group: in an experiment with multiple groups, a group of participants that does not receive the IV or receives a very low level of it
15
Managing Experiments
You want to isolate the effects of the IV and eliminate alternative explanations Any aspect of an experiment that is not controlled may
become an alternative explanation for changes in the DV Sometimes, deception is used to manipulate how
participants define a situation, by misleading them w/ instructions, by staging settings, or by using helpers or confederates confederates: people who work for an experimenter and
mislead participants by pretending to be another participant or uninvolved bystander
16
Types of Experimental Design experimental design: how parts of an
experiment are arranged, often in one of the standard configurations
We can divide standard designs into three groups true experimental pre-experimental quasi-experimental
17
Variations on a simple example can show the standard experimental designs
Goal: Design experiment(s) to explain the size of tips To test whether servers receive bigger tips if
they introduce themselves by first name before taking an order and return 8-10 minutes after delivering food to ask “Is everything fine”?
IV=server behavior / DV = size of tip received
18
Example Using Classical Experimental Design
Month 1 Month 2 Group 1 PretestServe food w/o (amount of
tips)
intro or check-in
Group 2 PretestServe food w/o (amount of
tips)
intro or check-in
IV Present Posttest
Self-intro & (amount of tips)
check-in
IV Absent Posttest
Serve food w/o (amount of tips)
intro or check-in
19
Ex. w/ 2-Group Posttest-Only Experimental Design
Month 1 Month 2
Group 1 Serve food w/o
intro or check-in
Group 2 Serve food w/o
intro or check-in
IV Present Posttest
Self-intro & (amount of tips)
check-in
IV Absent Posttest
Continue to serve (amount of tips)
w/o intro or check-in
20
Ex. w/Solomon 4-Group Experimental Design
Month 1 Month 2
Group 1 PretestServe food w/o (amount of
tips)intro or check-in
Group 2 PretestServe food w/o (amount of
tips)intro or check-in
Group 3 Serve food with intro or check-in
Group 4Serve food w/o intro or check-in
IV Present PosttestSelf-intro & (amount of tips)check-in
IV Absent PosttestContinue serving (amount of tips)w/o intro or check-in
IV Present PosttestContinue self- (amount of
tips)intro & check-in IV Absent PosttestServe food w/o (amount of
tips)intro or check-in
21
Factorial designs Some research questions suggest you look
at the simultaneous effects of multiple IVs factorial design: an experimental design in which
you examine the impact of combinations of two or more independent variable conditions
22
Main vs. Interaction Effects main effects: the effect of a single
independent variable on a dependent variable
interaction effects: the effect of two or more independent variables in combination on a dependent variable that is beyond or different from the effect that each has alone
23
Fig 7.7: Blame, Resistance, and Schema: Interaction Effect
Fights Submits
BLAME
Victim tries to fight off the Rapist (Resistance)
Sex schema
Power schema
24
Experimental Validity
internal validity: the ability to state that the IV was the one sure cause that produced a change in the DV
external validity: the ability to generalize experimental findings to events and settings beyond the experimental setting itself
25
Pre-experimental designs pre-experimental designs: experimental
designs that lack one or more parts of the classical experimental design, e.g., One-Shot Case Study Design One-Group Pretest-Posttest Design Static Group Comparison
26
Quasi-Experimental Designs quasi-experimental designs: experimental
designs that approximate the strengths of the classical experimental design, but do not contain all of its parts, e.g., Interrupted Time Series Equivalent Time Series
27
Threats to internal validity
1. Selection bias
2. History
3. Maturation
4. Testing
5. Experimental mortality
6. Contamination or diffusion of treatment
7. Experimenter expectancy
28
Experimenter expectancy Experimenter expectancy refers to how researchers may
accidently and indirectly communicate the desired findings to participants This is not purposeful, unethical behavior
Researchers control experimenter expectancy by using double-blind experiments double-blind experiments: an experimental design to control
experimenter expectancy in which the researcher does not have direct contact with participants. All contact is through assistants from whom some details are withheld.
placebo: a false or noneffective independent variable given to mislead participants
29
Threats to External Validity Participants are not representative Artificial setting Artificial treatment Reactivity
30
Reactivity Research participants respond differently
than they would in real life situations b/c they’re aware they’re part of a study reactivity: a threat to external validity due to
participants modifying their behavior because they are aware that they are in a study
Hawthorne effect: a type of experimental reactivity in which participants change due to their awareness of being in a study and the attention they receive from researchers
31
Field Experiments The amount of control researchers have
over an experiment varies, from tightly-controlled laboratory experiments in specialized settings to field experiments field experiment: an experiment that takes place
in a natural setting and over which experimenters have limited control
32
Natural experiments Unlike intentional, planned experiments, natural
experiments, or ex post facto (after the fact) control group comparisons, are field experiments that people did not internationally plan as an experiment but had features of an experiment
natural experiments: events that were not initially planned to be experiments but permitted measures and comparisons that allowed the use of an experimental logic
33
HOW TO BE ETHICAL IN CONDUCTING EXPERIMENTS Some researchers use deception, misleading or
lying to participants While dishonesty is never condoned, deception
may be acceptable under limited conditions If it is the only way to achieve a clear research goal The amount and type of deception do not go beyond what
is minimally necessary Participants are debriefed as soon as possible debrief: an interview or talk with participants after an
experiment ends in which you remove deception if used and try to learn how they understood the experimental situation