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Psychology: Research Design & Analysis > Final Exam Review > Flashcards

Final Exam Review Flashcards

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0
Q

Independent group designs
AKA?
What are they?
How are groups arranged?

A
  • Aka between subjects
  • Compare differences between groups while controlling for differences within groups
  • separate groups for each level of IV
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1
Q

Experimental methods

A

Establish causation if random assignment is used

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2
Q

An experiment is used to infer causality by using?

A

Manipulation of the IV

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3
Q

Control requires balanced samples. What does this mean and why is random assignment a good way to achieve this?

A

Controls for individual differences within groups providing for greater internal validity

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4
Q

Why is one group pre test post test design not an experiment?

A

No control

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5
Q

What is required to make a casual inference? Why does an experiment make this possible?

A

Covariation, time order relationship between IV and DV, elimination of alternative explanations

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6
Q

What does co variation mean?

A

The IV and DV are correlated; both events occurred around the same time

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7
Q

Time order relationship

A

IV changes, then DV changes

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8
Q

Internal validity
What is it?
Requirements?

A

Extent to which you can make a casual inference

Only occurs when all 3 aspects are met

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9
Q

External validity

A

Does intervention work in the real world?

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10
Q

Threats to internal validity;

A

Confounds
Extraneous variables
Systematic differences between groups

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11
Q

What are intact groups and why are they a problem?

A

Using pre existing groups

Results may have alternative explanation

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12
Q

Attrition

A

Loss of participants in a study

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13
Q

Mechanical loss

A

Factors external to participants

Not a big deal if infrequent

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14
Q

Selective subject loss
What is it?
How to control for it? (2 ways)

A

Internal factors
Can destroy comparable groups
Pretesting, drop one as another drops out

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15
Q

Participant and experimenter biases

A

Unethical manipulation of any part of an experiment that will aid in obtaining desired results

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16
Q

Double blind design
What is it?
Can control what?

A

Neither experimenter or participants know if they are in the control group or the treatment group
Can control experimenter effects

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17
Q

What is an independent groups design?

A

Between groups design

Separate group of participants for each level of the IV

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18
Q

What are between groups and within groups differences?

A

Q

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19
Q

Why can’t random assignment always be used?

A

Pre existing variables such as quasi experiments

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20
Q

Why can’t matched and natural groups designs not use random assignment?

A

No control because manipulation is not technically possible with pre disposed variables

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21
Q

3 types of independent groups?

A

Random
Natural
Matched

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22
Q

Random independent groups

A

Balance out individual differences

Randomly assign participants to level of IV

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23
Q

Natural independent groups
What is it?
True experiment?
Why or why not?

A

Naturally occurring IVs

Not true experiment (correlational because the already existing IV cannot technically be manipulated)

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24
Q

Matched independent groups
What is it?
When to use?

A

Instead of random assignment, groups formed on relative dimension
Works best w Smaller sample sizes

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25
Q

Repeated measures design
What is it?
How does it differ from an IGD?

A

Each participant completes all conditions of the experiment; participants serve as their own controls
Compares within group effects rather than between group effects

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26
Q

What are practice effects?

A

Change in participant’s responses over time due to learning a new task
Boredom, fatigue

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27
Q

What are anticipation effects?

A

Q

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28
Q

Purpose of counterbalancing?

A

To correct for

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29
Q

Advantages of the RMD

A

Participants are own controls, so less subjects are needed

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30
Q

Disadvantages of the RMD

A

Practice effects are possible if not properly counter balanced

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31
Q

Types of counterbalancing: complete

A

Block randomization

ABBA

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32
Q

Types of counterbalancing: incomplete

A

All possible orders
Latin square
Random starting order with rotation

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33
Q

Block randomization
What is it?
Size of blocks =?
Requires what?

A

Counterbalancing in which each block contains all conditions in random order
Size of block = number of cond
Requires many presentations to balance

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34
Q 
ABBA counterbalancing
What is it?
Conditions presented how?
Practice effects?
Can only be used when?
A

Conditions in one random sequence, then reversed
Presents conditions only a few times to each participant
Each condition has same amount of practice effects
Can only be used when practice effects are linear

35
Q

All possible orders
Best choice for which design?
What is it?
# of possible orders=?

A 
Best choice for incomplete design
Each participant randomly assigned to all possible orders 
# of possible orders = N! With N conditions
36
Q

Latin square
Uses what?
What is it?

A

Uses selected orders
Each condition appears in each ordinal position once
Each condition proceeds and follows each other condition only once

37
Q

Random starting order with rotation

A

Start with random order, then for each row, rotate one to the left

38
Q

What is differential transfer? Why is it problematic for RMD?

A

Performance on one condition is dependent on the condition that precedes it

39
Q

What is a complex design?

Why are they useful?

A

1 DV, 2 or more IVs

Interactions are the main advantage

40
Q

What is a mixed design?

A

A complex design which used IVs of both ind groups and repeated measures

41
Q

What types of effects are concerned within a complex design?
How do we know if each is present?

A

Main effect
Interactions
Simple main effect

42
Q

Main effects

A

An effect of a single IV alone

43
Q

Interactions
What are they?
Why are they important?

A

When the effect of an IV is different at different levels of another IV

44
Q

Simple main effects

A

The effect of an IV at a single level of another IV

45
Q

What are ceiling effects?

What are floor effects?

A

Ceiling: when performance reaches a maximum in any condition of an experiment
Floor: performance reaches a minimum

46
Q

Single case design
What is it?
Is it an experiment?
Why or why not?

A

Studies one subject at a time
IS an experiment
Uses manipulation and control

47
Q

Small n research

A

Small number of subjects

48
Q

Difference between a case study and a single subject experiment?

A

Case study is not an experiment

49
Q

Advantages/Disadvantages of single case design

A

A: high internal validity
Useful in dismantling other studies
D: limited to interventions w immediate/specific effect
Limited when examining behaviors with high variability (no stable baseline)

50
Q

Advantages/disadvantages of case studies

A

A: provides rich description of individual
New or rare phenomena
Provides counter evidence
D: 1 person not enough empirical evidence
Can’t make causal inferences
Bias
Threats to external validity

51
Q

When would a researcher choose a case study?

A

When studying new or rare phenomena

When searching for counter evidence

52
Q

Why can’t casual inferences be made from a case study?

A

Not a true experiment; does not use manipulation and control

53
Q

Ideographic approach

A

Intensive study of an individual

54
Q

Nomethetic approach

A

Approach that serves to establish broad generalizations or laws that apply to large groups of individuals

55
Q

Anecdotes
What are they?
Why are they not adequate support for a hypothesis?

A

A

56
Q

Testimonials
What are they?
Why are they not adequate support for a hypothesis?

A

Q

57
Q

Requirements for single subject experiment

A

Behavioral DV with stable baseline
Potent IV that results in immediate change
Controlled conditions

58
Q

Types of designs?

A

ABAB
Multiple baseline across individuals
Behaviors
Situations

59
Q

Why is a stable baseline needed?

A

It allows us to detect a change

60
Q

Concept of reversal

Why is it needed to infer causality in an ABAB design?

A

Behavior changes with implementation of the IV, then reverses back to original state with removal of IV

61
Q

Quasi experimental designs

A

Resembles a true experiment of treatment/intervention performed in natural setting
Lack of full control (no randomization)

62
Q

Difference between a quasi design and a true experiment?

A

Lack of full control

63
Q

When would a researcher choose to use a quasi experiment?

A

When randomization is not feasible, some hypothesis can’t be tested in the real world

64
Q

Threats to internal validity: 8

A 
History
Maturation
Testing
Instrumentation
Regression to mean
Attrition
Selection 
Additive effects with selection
65
Q

Threats to internal validity: history

A

Some non treatment produces change in participants behavior

Solution: control groups

66
Q

Threats to internal validity: maturation

A

People change naturally over time

Solution: control group to compare performance

67
Q

Threats to internal validity: testing

A

People get better when tested again

Solution: use equivalent but different measures

68
Q

Threats to internal validity: instrumentation

A

Measure of your DV changes

Solution: ensure reliability and validity

69
Q

Threats to internal validity: regression to the mean

A

People at extreme ends of a measure tend to move toward the middle over time
Solution: don’t choose samples of extreme individuals

70
Q

Threats to internal validity: attrition

A

Participants lost over time

Solution: careful follow up procedures, statistically compare those who dropped out to those who teamin

71
Q

Threats to internal validity: selection

A

One group systematically differs from the other in ways unrelated to the intervention
Solution: randomization

72
Q

Threats to internal validity: additive affects with selection

A

When any of the first 6 threats exists for one group but not the other
Solution: randomization

73
Q

5 threats to independent group designs (even true experiments)?

A

Contamination
Experimenter expectancy
Novelty
Hawthorne Effect

74
Q

Threats to IGD: contamination
What is it?
Examples?

A

When groups communicate with each other

Resentment, rivalry, control group seeking the treatment

75
Q

Threats to IGD: experimenter expectancy effect
What is it?
Control through?

A

Unintentionally influencing results through observation, errors, etc.
Control through double blindness

76
Q

Threats to IGD: novelty effects

A

Newness of the tx has an effect rather than the tx itself

77
Q

Threats to IGD: Hawthorne effect

A

Behavior changes simply because someone is interested in the participants
(They care; they’re judging me)
Control through having same effect in control group

78
Q

3 types of quasi experimental designs?

A
  • Nonequivalent control group
  • Interrupted time series
  • Time series with non equivalent control group
79
Q

Nonequivalent control group
Type of?
What is it?
Vulnerable to what?

A

Quasi experiment
Groups that are truly comparable controls for many threats to internal validity
Vulnerable to additive effects with selection

80
Q 
Interrupted time series 
What is it?
What is often used?
Compares what?
2 requirements?
A

No control group, multiple observations before intervention (baseline)
Archival data often used
Compares baseline before and after intervention
Requirements: must be abrupt, evidence of effect

81
Q

Time series with Nonequivalent control group
What is it?
What kind of groups does it have?
Rules out what effects?

A

Multiple pre and post tests
Intervention and control group
Rules out history and instrumentation effects

82
Q

Descriptive methods

A

Do NOT manipulate IV

may establish correlation but not causation

83
Q

1 problem in quasi experiments? Why?

A

Additive effects with selection. Because of lack of randomization

84
Q

Selection with maturation
Selection with history
Selection with instrumentation

A
  • participants mature at different rates in the different groups
  • participants experience different events that affect their responses
  • instrument is more or less sensitive to change in one group vs another

Psychology: Research Design & Analysis (4 decks)

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