Chapter 14: Generalizing Results
Issues of generalizing results to other population; problem with college students as participants.
Issues of generalizing result to other cultures and ethnic groups.
Problem of generalizing to other experimenters and possible solutions.
Importance of replications, distinguishing between exact replications and conceptual replications.
Narrative literature reviews and meta-analyses.
Recall: Internal validity—ability to infer a causal relationship exist between the variables.
External validity—extent to which findings may be generalized.
Generalizing to other populations of research participants
Rarely are participants randomly selected from the general population, usually they are selected because
they are available: college students! So can we really generalize the results beyond that group?
College students (and rats)
High % (70%) of studies published used college student as participant.
Potential problem is that such studies use a highly restricted population.
College students: young, late adolescence—sense of self-identity still developing, social and
political attitudes in flux, high need for peer approval, unstable peer relationships. Intelligent.
Research shows those students groups are more homogeneous than non-student samples.
Rats are hardy, cheap, easy to rear, well adapted to lab, just like first year students and
sophomores, easy to obtain on a campus and readily available.
External validity of findings may also be limited, volunteers tend to be: more highly educated,
higher socioeconomic status, and more in need of approval, more social.
Different kinds of people volunteer for different kinds of experiments (based on the Title).
Asking people on internet to volunteer for a survey: but the internet use is still more common in a
particular demographic: urban/suburban area, college educated, younger, higher income.
Sometimes one sex is used because convenient, or the procedures seem better suited to a gender.
Gender bias: confounding gender with age or job status, selecting response measures that are
*Include both & recognize ways that they might differentially interpret variable manipulations.
Location that participants are recruited from: found even personality traits like extraversion and
openness can vary across geographic areas. Generalization as a statistical interaction
Think of the problem of generalization as an interaction in a factorial design:
-An interaction occurs when a relationship between variables exists under 1 condition but not
another; when nature of relationship is different in one condition than in another.
Ex: study used only males, perhaps an interaction between gender and independent variable.
Perhaps can’t generalize the result to females.
Ex: study on aggression and crowding in both sexes.
-Graph C+D shows interaction between gender and crowding.
In defense of college students (and rats)
Criticism of study using only college students should be backed with good reasons that a
relationship would not be found with other types of subject.
1. Student bodies are increasingly diverse and representative of society as a whole.
2. Replication provides safeguard against limited external validity of a single study. (applying to
other populations such as children, aging adults, other countries).
*Internet samples are often used as a complement based on college student samples.
Rats: we can applies findings to humans: bio bases of memory, food preferences, sexual behavior,
choice behavior, drug addictions.
Cross culture generalization, critic—Psychology is built on study of WEIRD (western, educated,
industrialized, rich, democratic) people.
-Ex: theories of self concept: in western society – self means people are independent, self-enhancement
comes from individual achievements.
In other cultures: self is a collective concept, self-esteem derived from relationships
with others. Japanese engage in self-criticism which is seen as relationship-maintaining.
-Many are different and low generalization, ex: self. Same is: waist-hip ratio! Generalized across culture. Generalizing to other experimenters
Experimenters are another source of external validity problems: often just one experimenter.
Main goal is to ensure that any influence they has on subjects is constant throughout experiment.