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Psyc 357 ch 3.docx

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Simon Fraser University
PSYC 357
Dagmar Bernstein

Psyc 357 ch 3: The study of adult development and aging: Research methods • Variables in developmental research: o Variable=characteristics that “varies” from indiv to indiv  Dependent variable= variable on which ppl differ  Independent variable=variable that explains/causes range of scores in the DV • Tx age as IV but it’s not technically something you can manipulate o Experimental design= manipulation of an IV followed by the measurement of scores on the DV  Ppl randomly assigned to tx and ctrl groups o Quasi-experimental design= groups compared on predetermined characteristics  Can’t conclude that predetermined characteristics caused variations in DV but can describe difs b/w groups • Descriptive research designs: o Major challenge is to separate effect of aging from effects of time  3 variables in process are age, cohort and time of measurement (influence jointly the indiv’s performance on any given psycholigcal measure at any point in life) • Age=chronological, cohort= year of period of birth, time of measurement=time of testing o Age, cohort and time measurement:  Time of measurement= year or period when testing happens, convenient way of representing social and historical influences on person • Linked to cohort in taht ppl of certain age being tested at particular time must be from same cohort  2 types of descriptive research= longitudinal and cross sectional o Longitudinal design= goal to see what happens to ppl over time by observing  Tho hard to know what caused changes (age, environment, other), can’ remove indiv from environment to see what would happen w/dif set of circumstances • Take a long time, patience and solid budget, results take a long time to come • Subject attrition= lose subjects over time b/c as numbers dwindle it’s harder to compelte statistical analysis on data • Special characteristics of those who survive? • Practice effects= know the tests, tests become outdated so change them o Cross sectional designs= compares performance of ppl selected on basis of age at ONE point in time  Goal= describe age differences, assumes that performance differences bb/w agre groups the result of aging process • Attempt to ctrl for cohort difs that might obscure/exaggerate effects of age • How do you decide on age spans for dif samples? Some use young, middle aged and older adults o Also be sensitive of how dif age groups will react differently to test materials (ie using a computer) o Also be careful that dif cohorts react differently to measures of personality and social attitudes o Relatively quick and cheap compared to longitudinal, can use latest technology, provide descriptions of difs b/w groups of varying ages  The more effort investing in ctrling for difs other than age, the better • Sequential research designs: o Virtually impossible to design the perfect study on aging b/c age can never be a true IV so can’t manuplate it  Age also linked w/time and so personal aging always linked w/social aging o Sequential designs= several dif combinations of variables of age, cohort and time of measurement  Involves “sequence” of studies (ie cross sectional study carried out twice over 10 years)  Sequential nature makes them superior to truly descriptive designs o Most efficient design=  K. Warner Schaie outlined Most Efficient Design (set of 3 designs manipulating variables of age, cohort and time of measurement) • Organize data in table that combines (ie) year of birth (cohort) w/year of testing (time of measurement) o Time sequential design (age by time of measurement) , cohort sequential (cohort by age) and cross-sequential design (cohort by time of measurement) • Correlational designs= observe rlnshps among variables as they exist in the world o Make no attempt to divide participants into groups or to manipulate variables o Simple correlational designs:  +1.0 to -1.0 correlation value (r) • Greater than zero indicates positive rlnshp so as one value increases, so does the other, negative correlation (as one increases, the other decreases), 0 correlation= no rlnshp  Advantage of correlational design for study of age is that it can be treated as a continuous variable so there’s no loss of info owing to the necessity of collapsing ppl into age groups • In experimental design by maniupating values of IV researcher has caued ppl to differ on DV o In correlational study researcher makes no assumptions about what caused what, no I and D variables  Also no direction or causality o Often that there’s a third variable accounting for rlnshp o Multivariate correlational des
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