PSYC 2020 Lecture 7: PSYC 2020 Lecture 7 Notes
PSYC 2020 Lecture 7 Notes
Introduction
Cohort Effects
• An important advantage of the cross-sectional design is that the investigator can collect
data from children of different ages over a short time.
• For example, Coates and Hartup did not have to wait three years for their 4- to 5-year-
olds to become 7 to 8 year olds to test their developmental hypotheses.
• They merely sampled from two age groups and tested both samples simultaneously.
• Yet there are two important limitations of cross-sectional research.
• Recall as we noted above that in cross-sectional research, participants at each age level
are different people.
• That is, they come from different cohorts.
• The fact that cross-sectional comparisons always involve different cohorts presents us
with a thorny interpretive problem
• Any age differences that are found in the study may not always be due to age or
development but, rather, may reflect other cultural or historical factors that distinguish
members of different cohorts.
• Stated another way, cross-sectional comparisons confound age and cohort effects.
• An example should clarify the issue.
• For years, cross-sectional research had consistently indicated that young adults score
slightly higher on intelligence tests than middle-aged adults, who, in turn, score much
higher than the elderly.
• But does intelligence decline with age, as these findings would seem to indicate? Not
necessarily.
• Later research Schaie, 99 revealed that individuals’ intelligence test scores remain
relatively stable over the years and that the earlier studies were really measuring
something quite different: age differences in education.
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