research methods in relationship science

Question 1

what is the most important aspect of the scientific approach in relationship science?

Answer 1

operationalization
We have to turn constructs into something we can study —–
Ex. Attraction
○ Behavioural: exchanging phone numbers, smiling
○ Self report
○ Physiological measures: heart rate, brain activity

But its hard to actually measure the real thing

Question 2

construct validity

Answer 2

(extent to which an operationalization adequately captures the psychological construct of interest)

Question 3

interrator reliability

Answer 3

extent to which doers agree on whether a specific behaviour has or has not occured

Question 4

criteria for causation

Answer 4

(1) two variables have to be correlated
(2) one variable must precede the other
(3) there must be no reasonable alternative explanations for the pattern of correlation

Question 5

cross sectional data vs longitudinal data

Answer 5

CROSS SECTIONAL DATA: data collected at one single point in time
LONGITUDINAL DATA: data collected from the same participants on multiple occasions - allows us to examine change over time

Question 6

intervals for longitudinal research

Answer 6

• Sometimes need to follow participants for months, years, decades
  
  • Or more frequent assessments over a shorter period of time

Question 7

attrition bias

Answer 7

when participants that drop out are systematically different than the participants that remain in the study

Question 8

pros and cons of longitudinal study

Answer 8

Pros of longitudinal study:
- Captures change over time
- Can examine processes that would be impossible/unethical to cause
- Less subject to retrospective bias

Cons:
- Expensive
Time and labour intensive

Question 9

experimental design

Answer 9

Is the only design that allows us to make causal inferences (if we go about it right)

need a good control!!* we want the control condition to match the experimental condition as closely as possible minus the key difference (need to avoid CONFOUNDING VARIABLE)

Question 10

dyadic data

Answer 10

data from both members of couple
Assumption of regression (independence)is violated

Question 11

actor partner interdependence

Answer 11

allows us to examine how individual outcomes are affected by both ones own characteristics (actor effect) and partners characteristics (partner effect)

Question 12

problems with diadic data

Answer 12

Often want to get dyadic data to examine dyadic processes….but are dyadic samples representative of the population or unique?

What is the difference between partners who participate together vs people who participate without their partners:
- greater attachment, satisfaction, commitment, more secure attachment

Couples who agreed to participate together less likely to experience breakup
Means that dyadic samples are systematically different than other types of data