Research Methods Flashcards

1
Q

Operationalisation

A

Turning a construct into an operational variable with an objective measure

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Reliability

A

the consistency and stability of a measure

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Validity

A

The measure measures the construct it’s supposed to measure

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Test-Retest Reliability

A

giving a participant the same test multiple times

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Interrater Reliability

A

Agreement amongst raters observing behaviour

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Internal Reliability

A

e.g. through split half reliability which splits items in measure randomly into two and calculates the scores for each half –> checks relationships between the two halves

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Cronbach’s alpha

A

Average of all possible split half reliability scores

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Internal validity

A

validity within the experiment

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

external validity

A

validity outwith the experiment, e.g. ecological, population, temporal

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Face validity

A

intuitive sense of the experiment

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

content validity

A

the measure reflects the conceptual definition of the construct from the literature represented in the experiment

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Criterion validity

A

the extent to which people’s scores on a measure are correlated with other variables that one would expect to be correlated with
including concurrent validity and predictive validity

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

concurrent validity

A

criterion and construct are measured simultaneously

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

predictive validity

A

the ability of a test or other measurement to predict a future outcome

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

convergent validity

A

correlates strongly with the measure of the same construct, different tests that measure the same thing

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

discriminant validity

A

correlates less with the measure of a different construct

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Within Subjects design

A

All participants are exposed to all levels of the IV at different times

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

Between subjects design

A

Different participants are exposed to different levels of the IV

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

extraneous variables

A

any variable other than the DV or IV that could affect your outcomes

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

confounding variable

A

an extraneous variable that varies systematically across levels of the IV

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Block randomisation

A

All the conditions occur once in the sequence before any of them is repeated

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Complete counterbalancing

A

equal number of participants complete each possible order of conditions

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Randomised control trial

A

experiments done in the field to investigate the effectiveness of a treatment/intervention

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

random counterbalancing: Latin square

A

each condition appears exactly once in each position

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Placebo effect

A

the mere expectation that there will be an improvement contributes to said improvement

22
Q

Internal validity

A

Is there a causal relationship between the variables - quality of the research design

23
Q

statistical validity

A

proper treatment of the data and the soundness of the researchers statistical conclusions

24
Q

external validity

A

generalisability of the findings

25
Q

mundane realism

A

participants and situation studied are similar to those the researchers want to generalise to

26
Q

psychological realism

A

same mental process is used in both the lab and the real world

27
Q

single factor two level design

A

studies the effect of only one IV on the response of a DV

28
Q

single factor multi level design

A

studies the effect of multiple IVs on the response of a DV

29
Q

Non-experimental design

A

looking at associations between variables with no random assignment, manipulation of IV or control group

30
Q

Observational Research

A

Systematic observations in a non-experimental design

31
Q

Naturalistic observation

A

field work, in the wild research
disguised: participants are unaware of being studied -> avoids experimenter effects, higher validity but ethical issues
undisguised: participants aware of researcher’s presence -> reactivity - different due to observation? more ethical?

32
Q

Participant observation

A

becoming part of the participants
disguised: infiltration of group
undisguised: disclosure of identity
can be inorganic due to researcher’s influence on group, and group’s influence on researcher,
high ecological validity, time consuming, ethical implications

33
Q

Structured/controlled observation

A

Observations made in an artificial environment to observe specific behaviours

34
Q

Behavioural coding

A

practice of formally and systematically defining overt (observable) behaviours

35
Q

time sampling

A

method of collecting data in which you watch research participants for a specific amount of time at specific time intervals and record behaviour

36
Q

event sampling

A

record each time a certain behaviour occurs

37
Q

Quasi experimental Research

A

involves manipulation of IV but no random assignment of groups

38
Q

Post test only design

A

IV is given to group and DV is measured afterwards

39
Q

Pre-test-post-test design

A

DV is measured before and after treatment

40
Q

Regression to the mean

A

extreme variables tend to level out if repeatedly measured
statistical phenomenon that makes natural variation in repeated data look like real change

41
Q

Non equivalent pre-test post-test design

A

different groups get different conditions

42
Q

interrupted time series design

A

data is measured at multiple time points before and after the introduction of an intervention to examine effect of the intervention

43
Q

Survey

A

Involves design, data collection (questionnaire or interview) and analysis and interpretation

can be experimental or non-experimental, non-experimental most of the time

44
Q

Stages of Survey construction

A

Aims and objectives of the survey, target group
Question style
Question Design (Brief Relevant Unambiguous Specific Objective)

45
Q

Double Barrelled questions

A

A question that asks more than one questions
e.g have you experienced depression AND anxiety in the last 2 weeks?

46
Q

Leading Questions

A

A question that prompts or encourages a specific answer

47
Q

Acquiescence Bias

A

Yay-saying (always agreeing)
Nay-saying (always disagreeing)
fence-sitting (always picking middle category)
-> fix through reverse scoring items, even numbered rating scale

48
Q

Piloting

A

testing an experiment on a small target population

49
Q

representative sample

A

a subset of people that portray similar characteristics of the population that you are aiming to investigate

50
Q

stratified random sampling

A

A population is divided into homogenous subpopulations, or strata, based on specific characteristics (race, gender, identity)
each group is randomly sample

51
Q

simple random sampling

A

every member of a population has an equal chance of being selected -> representative and unbiased
-> needs info of entire population

52
Q

cluster sampling

A

a population is divided into smaller groups or clusters and some clusters are selected randomly. used to study large population, usually pre-existing clusters (e.g. schools/cities)
can be biased if clusters aren’t representative

52
Q

quota sampling

A

sample represents estimated numerical composition population - not randomly selected
recruit until quota for subgroup is reached

52
Q

systematic sampling

A

select members of the population at a regular interval (k) determined in advance. time efficient, fixed interval reduces bias, not recommended for periodically ordered groups

52
Q

snowball sampling

A

start with a few participants and then continue to recruit people based on referrals from initial participants

52
Q

convenience sampling

A

sampling those who are easy to contact, volunteers

52
Q

purposive sampling

A

obtaining a sample with pre determined criteria, not meant to make statistical inference to whole population