Understanding the Basics of Experiments in Social Sciences
Delve into the world of experiments in social sciences with a focus on experimental designs, ethical considerations, and intriguing questions like predicting helping behavior in emergencies. Explore how studying helping behavior in experiments can shed light on complex human interactions and behaviors.
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LABORATORY LABORATORY Stephen Benard Department of Sociology Indiana University EXPERIMENTS IN THE EXPERIMENTS IN THE SOCIAL SCIENCES: SOCIAL SCIENCES: AN INTRODUCTION AN INTRODUCTION
OVERVIEW A sample question What is an experiment? Basics of experimental design What can we learn from experiments? Ethics of experiments
AN (ENCOURAGING) DISCLAIMER Just a small sample of the: Questions Experimental designs Independent and dependent variables Many, many possibilities
SAMPLE QUESTION: WHAT PREDICTS HELPING IN AN EMERGENCY? If we notice someone in need: Are we more likely to help when alone, or in the presence of others? Diffusion of responsibility
ARE PEOPLE LESS LIKELY TO HELP OTHERS WHEN IN A GROUP? Challenging to study through observation Emergency events are rare and hard to predict May vary in countless ways Many alternative explanations People in groups less likely to notice More groups at busier times of the day less time Unhelpful people more likely to travel in groups
STUDYING HELPING IN AN EXPERIMENT Would be useful to repeatedly observe responses to the same emergency under different condition E.g., when many or few people observe the emergency Could be staged in a laboratory (Darley and Latane 1968 in JPSP) Laboratory discussion group One person appears to have a seizure Manipulate number of people present Measure proportion who helped, speed
A FEW MORE EXAMPLES Does violent media make people aggressive, or do aggressive people prefer violent media (Bandura, Ross, and Ross 1961)? Does intergroup contact reduce or exacerbate intergroup conflict (Sherif 1958)? Does positive mood make people more altruistic, or are more altruistic people happier (Isen et al 1978)? Do our attitudes determine our behavior, or does our behavior determine our attitudes (Festinger and Carlsmith 1959)? Does the gender/race/age/criminal record/other characteristic of a job applicant affect the likelihood of being hired (e.g., Pager 2003)? Is support for a policy determined by the content of the policy, or the identity of the party supporting it (Cohen 2003)? Does lack of control over our environment turn us into conspiracy theorists (Whitson and Galinsky 2008)? Does the status of an author s institution affect their chances of having an article accepted (Peters and Ceci 1982)?
WHY CONDUCT AN EXPERIMENT? Identifying causes Addressing alternative explanations Identifying moderators and mediators Examining hard-to-observe or rare events
WHAT IS AN EXPERIMENT? THREE PRINCIPLES Manipulation of the independent variable Random assignment to condition Controlled measurement
MANIPULATION In experiments you must manipulate an independent variable (IV) This creates 2 (or more) levels of the IV The levels of the IV are called conditions Conditions identical except for the manipulated IV E.g., number of people present when an emergency occurs
RANDOM ASSIGNMENT How do we distinguish the effects of our IV from extraneous variables? Perhaps personal interest in helping others confounded with group size Experimenter places people into experimental conditions by chance Equal likelihood of being in each condition Individual differences cancel out
RANDOM ASSIGNMENT Colors symbolize any differentiating attribute among the individuals (e.g., personal interest in helping others) Before Random Assignment R After Random Assignment Small crowd Large crowd Experimental Groups
WHAT IF PEOPLE CHOSE THEIR CONDITION? Colors symbolize any differentiating attribute among the individuals (e.g., personal interest in helping others) Before choosing C Systematic error Small crowd Large crowd Self-selected Groups
CONTROLLED MEASUREMENT Systematically observe changes in the dependent variable as a function of changes in the independent variable Important to avoid bias in recording the DM Participant blind to hypotheses Experimenter blind to hypotheses Experimenter blind to condition
A SIMPLIFIED HELPING STUDY (BASED ON DARLEY AND LATANE 1968) Experimental setting: a laboratory discussion group Simulate an emergency (seizure) Manipulate number of other people present in group E.g., zero vs. three Randomly assign participants to the alone condition or the group condition Measure proportion helping, time to help
EXPERIMENTAL DESIGN Two condition, treatment-control design Similar to medical study with placebo Simplest possible design Often very effective, but also limited Additional treatment conditions Factorial designs
ADDITIONAL TREATMENT CONDITIONS Perhaps group size has a non-linear effect Add additional condition with 6 total group members Sometimes it is useful to have a baseline condition E.g., a study of whether a text is evaluated more positively when the author is a man vs. a woman May wish to compare to a condition with no author information Is it that men receive a boost relative to the baseline, or women receive a penalty?
FACTORIAL DESIGNS Multiple IVs Every combination of every level of IV Interaction effects Predict an interaction Or evaluate generality Similarity Similarity to to Similar No help Victim Victim Not No help No help Group Large Size Small Help A 2 x 2 Factorial Design
BETWEEN VS. WITHIN-SUBJECTS DESIGNS Between-subjects design: Each participant is exposed to one level of the independent variable E.g., study of helping
BETWEEN VS. WITHIN-SUBJECTS DESIGNS Within-subjects design: Each participant exposed to multiple levels of the dependent variable E.g. Text evaluation study More efficient But possibly easier to guess hypotheses Requires counterbalancing Rarely possible in high-impact designs
INDEPENDENT VARIABLES How do we know operational independent variable accurately measures theoretical dependent variable? E.g., positive mood How do we know the manipulation had the expected effect on participants? Manipulation Checks
DEPENDENT VARIABLES (AND SOME BROAD GENERALIZATIONS) Examples Examples Difficulty/ Difficulty/ Cost Cost Sensitivity to Sensitivity to Social Social Desirability Desirability Participant Participant Engagement Engagement Useful Useful for/When for/When Reported attitudes & emotions, vignettes Low High Low Goal is measure internal state Verbal Help victim, donate to charity High Low High Goal is predict behavior Behavioral Choose partner, agree to something Moderate Moderate High (pre- decision) Commitment of more interest than behavior Behavioroid fMRI, cortisol, heart rate Very High Very Low High (but possible discomfort) Biological mediators/ moderators Physiological
WHAT CAN WE LEARN FROM EXPERIMENTS? High degree of control provides high internal validity Experiments provide the strongest possible evidence for causality But, external validity of laboratory experiments is often criticized Settings don t always resemble real world Participants don t resemble other populations Samples are generally non-random Small samples, at least by survey data standards Participants are often college undergraduates Participants are often WEIRD: Western, educated, industrialized, rich, democratic
MUNDANE VS EXPERIMENTAL REALISM Mundane Realism: the extent to which an experiment looks like the real world Experimental realism: the extent to which experience is psychologically real and important to participants Rarely come to a lab for a group discussion
GENERALIZING FROM? Should not generalize directly from an experiment to a real world situation Experiments test theories Theory bridges empirical studies and the real world See Zelditch, 1969, Can you really study an army in the laboratory Theory Complex phenomena to be explained Provide evidence for or against a theory Provide explanation for real world phenomena Real World Experiment
SCOPE CONDITIONS Criticism that findings won t generalize Often explicitly or implicitly signal possible scope conditions These can be tested to further refine the theory Example: College students discriminate against women in hiring simulation Maybe more than real managers: less experience Maybe less than real managers: more egalitarian
CONVERGENT VALIDITY Useful to think of different methods as complementary, not competing Survey data May have high external validity, but limited ability to show causality Experiments High internal validity, but limited generality
EXPERIMENTAL ETHICS: Three core principles for all research Respect Beneficience Justice Deception Necessary to test some hypotheses But should be used only as a last resort And fully explained to participants Debriefing
SUMMARY Experiments are excellent for answering questions about causality, exploring alternative explanations, and examining rare or hard to observe events Many different types and approaches to experiments, can (must) be tailored to the research question Facilitate systematic replication and theory development Strengths/weaknesses complement other methods
Stephen Benard Department of Sociology Indiana University THANK YOU!
