Research Design

Front 1

What is the difference between a Research Design and Methodology?

Back 1

Research Design refers to your PLAN, Methodology refers to your PRACTICES.

Front 2

T/F: Findings always prove or disprove the hypothesis

Back 2

False! Findings do not necessarily prove the hypothesis

Front 3

T/F: Data may be taken as proof

Back 3

False! Data can only be taken as proof if no alternative hypotheses can account for your findings

Front 4

Parsimony

Back 4

The simplest explanation that can account for the findings and is most likely

Front 5

Plausible Rival Hypothesis

Back 5

Alternative explanations for your findings, whether parsimonious or not

Front 6

Findings

Back 6

The hard data you found

Front 7

Conclusions

Back 7

The explanations of your findings, they should adhere closely to findings

Front 8

T/F: Tentativeness and ambiguity of research findings can be eliminated if the study is good enough

Back 8

False, they can never be eliminated

Front 9

Internal validity

Back 9

The extent to which a study rules out alternative explanations of the findings

Front 10

Threats to internal validity

Back 10

Factors other than the IV that can influence the results

Front 11

Maturation

Back 11

The process of changing over time, such as growing older, tired, or bored

Front 12

Instrumentation

Back 12

Changes in the measuring instrument or procedure over time

Front 13

Response shift

Back 13

Changes in a person's standards, values, or perspective that lead to evaluating the same things in different ways

Front 14

External validity

Back 14

The extent to which the results of a study can be generalized beyond the study and to other populations

Front 15

Internal Validity

Back 15

To what extent can the intervention account for the results

Front 16

External validity

Back 16

To what extent can results be generalized

Front 17

Construct validity

Back 17

What specific part of the intervention was the causal agent

Front 18

Statistical conclusion validity

Back 18

To what extent is a relation shown and how well can we detect it's effects

Front 19

True or False: statistical regression is a threat to internal validity

Back 19

True

Front 20

What is Diffusion/Imitation

Back 20

When information given to one group leaks to some or all other groups (talking between groups)

Front 21

How do you prevent Reactivity of experimental Arrangements?

Back 21

Blind randomization so participants don't know if they're being watched or not

Front 22

Why would we not want to tell people they're in a study?

Back 22

Hawthorn effect

Front 23

How to prevent interference from multiple treatments?

Back 23

Stagger the order of treatments across groups

Front 24

How to prevent reactions to being assessed?

Back 24

Throw in some "red herring" measures so they don't know what you're trying to measure

Front 25

Confound

Back 25

A factor that occurred with the intervention that could account for the results

Front 26

How to prevent attention/contact with subjects providing intervention

Back 26

Blind and double blind studies

Front 27

Demand characteristic

Back 27

Information conveyed to participants, like a man in a white lab coat = authority

Front 28

Alpha

Back 28

The probability of rejecting a hypothesis when that hypothesis is true (type 1 error)

Front 29

Beta

Back 29

The probability of accepting a hypothesis when it is false (type 2 error)

Front 30

Power

Back 30

The probability of finding differences between conditions when there are really differences present

Front 31

Why is subject heterogeneity a threat to statistical conclusion validity?

Back 31

It makes it more difficult to detect differences due to your intervention

Front 32

Experimenter expectancies

Back 32

When the researchers expectancies and desires influences subjects

Front 33

Single operattions/narrow stimulus sampling

Back 33

When something seemingly irrelevant influences the results

Front 34

Cues of experimental situation

Back 34

Factors associated with the intervention actually contribute to results

Front 35

Grounded theory approach to qualitative research

Back 35

Using observations to form theories (e.g. from clinical work)

Front 36

True experiment

Back 36

The design allows for maximum control over the IV (randomized control trials)

Front 37

Quasi-experiments

Back 37

The conditions of true experiments are approximate - can't control everything

Front 38

Case-control designs

Back 38

The variable is studied by selecting participants who vary in that variable

Front 39

When are restricted samples fine?

Back 39

When studying a small specific area of study (video game violence won't apply to middle aged women)

Front 40

Cons of a 2x2 factorial design

Back 40

It isn't practical because it can get big and complicated fast and is expensive and it can be difficult to interpret

Front 41

Non equivalent pretest-posttest control group design

Back 41

Same as a normal pretest-posttest but without randomization

Front 42

Sequence effect

Back 42

When the order participants received Tx was responsible for results rather than Tx itself

Front 43

Order effect

Back 43

When treatment occurred led to results rather than results itself

Front 44

Pros and cons of No-Treatment Control Group

Back 44

Sets baseline for Tx group, but ethical problem of them not getting Tx

Front 45

Why No-contact control groups are bad

Back 45

Violates informed consent and poses as potential for harm, and using data without asking

Front 46

Benefits of nonspecific-treatment or attention placebo control group

Back 46

Addresses threats to internal/construct validity by highlighting the effects of your "active ingredient"

Front 47

Cons of nonspecific-treatment or attention placebo control group

Back 47

Difficult to make the control group non-therapeutic AND credible.

Front 48

Advantages of routine or Standard Treatment

Back 48

All participants get Tx, less attrition, clinically relevant (want to know if Tx B > Tx C)

Front 49

Yoked control group

Back 49

Matching control subjects to either other controls or Tx people to equilize groups on a particular variable

Front 50

Nonrandomly assigned or nonequivalent control group

Back 50

Adding groups and not RAing and yoking to assess for history, maturation, and testing

Front 51

Dismantling-treatment strategy

Back 51

Analyzes components of a treatment by isolating them. Requires 2 or more treatment groups

Front 52

Constructive-treatment strategies

Back 52

Opposite if dismantling. Adds components to enhance outcomes - "what can be added to make it more effective"

Front 53

Parametric treatment strategy

Back 53

When we know the "what" but not "how" it works. Changing process of your methods rather than content of Tx

Front 54

Comparative Treatment strategy

Back 54

Contrast 2 treatments and see which is better (TF-CBT vs TAU)

Front 55

Treatment Moderator Strategy

Back 55

Examines factors that may moderate Tx effects

Front 56

Treatment mediator strategy

Back 56

Explores mechanisms of change in therapy