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

Final Exam Review Flashcards

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
Matched independent groups What is it? When to use?
Instead of random assignment, groups formed on relative dimension Works best w Smaller sample sizes
25
Repeated measures design What is it? How does it differ from an IGD?
Each participant completes all conditions of the experiment; participants serve as their own controls Compares within group effects rather than between group effects
26
What are practice effects?
Change in participant's responses over time due to learning a new task Boredom, fatigue
27
What are anticipation effects?
Q
28
Purpose of counterbalancing?
To correct for
29
Advantages of the RMD
Participants are own controls, so less subjects are needed
30
Disadvantages of the RMD
Practice effects are possible if not properly counter balanced
31
Types of counterbalancing: complete
Block randomization | ABBA
32
Types of counterbalancing: incomplete
All possible orders Latin square Random starting order with rotation
33
Block randomization What is it? Size of blocks =? Requires what?
Counterbalancing in which each block contains all conditions in random order Size of block = number of cond Requires many presentations to balance
34
``` ABBA counterbalancing What is it? Conditions presented how? Practice effects? Can only be used when? ```
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
All possible orders Best choice for which design? What is it? # of possible orders=?
``` Best choice for incomplete design Each participant randomly assigned to all possible orders # of possible orders = N! With N conditions ```
36
Latin square Uses what? What is it?
Uses selected orders Each condition appears in each ordinal position once Each condition proceeds and follows each other condition only once
37
Random starting order with rotation
Start with random order, then for each row, rotate one to the left
38
What is differential transfer? Why is it problematic for RMD?
Performance on one condition is dependent on the condition that precedes it
39
What is a complex design? | Why are they useful?
1 DV, 2 or more IVs | Interactions are the main advantage
40
What is a mixed design?
A complex design which used IVs of both ind groups and repeated measures
41
What types of effects are concerned within a complex design? How do we know if each is present?
Main effect Interactions Simple main effect
42
Main effects
An effect of a single IV alone
43
Interactions What are they? Why are they important?
When the effect of an IV is different at different levels of another IV
44
Simple main effects
The effect of an IV at a single level of another IV
45
What are ceiling effects? | What are floor effects?
Ceiling: when performance reaches a maximum in any condition of an experiment Floor: performance reaches a minimum
46
Single case design What is it? Is it an experiment? Why or why not?
Studies one subject at a time IS an experiment Uses manipulation and control
47
Small n research
Small number of subjects
48
Difference between a case study and a single subject experiment?
Case study is not an experiment
49
Advantages/Disadvantages of single case design
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
Advantages/disadvantages of case studies
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
When would a researcher choose a case study?
When studying new or rare phenomena | When searching for counter evidence
52
Why can't casual inferences be made from a case study?
Not a true experiment; does not use manipulation and control
53
Ideographic approach
Intensive study of an individual
54
Nomethetic approach
Approach that serves to establish broad generalizations or laws that apply to large groups of individuals
55
Anecdotes What are they? Why are they not adequate support for a hypothesis?
A
56
Testimonials What are they? Why are they not adequate support for a hypothesis?
Q
57
Requirements for single subject experiment
Behavioral DV with stable baseline Potent IV that results in immediate change Controlled conditions
58
Types of designs?
ABAB Multiple baseline across individuals Behaviors Situations
59
Why is a stable baseline needed?
It allows us to detect a change
60
Concept of reversal | Why is it needed to infer causality in an ABAB design?
Behavior changes with implementation of the IV, then reverses back to original state with removal of IV
61
Quasi experimental designs
Resembles a true experiment of treatment/intervention performed in natural setting Lack of full control (no randomization)
62
Difference between a quasi design and a true experiment?
Lack of full control
63
When would a researcher choose to use a quasi experiment?
When randomization is not feasible, some hypothesis can't be tested in the real world
64
Threats to internal validity: 8
``` History Maturation Testing Instrumentation Regression to mean Attrition Selection Additive effects with selection ```
65
Threats to internal validity: history
Some non treatment produces change in participants behavior | Solution: control groups
66
Threats to internal validity: maturation
People change naturally over time | Solution: control group to compare performance
67
Threats to internal validity: testing
People get better when tested again | Solution: use equivalent but different measures
68
Threats to internal validity: instrumentation
Measure of your DV changes | Solution: ensure reliability and validity
69
Threats to internal validity: regression to the mean
People at extreme ends of a measure tend to move toward the middle over time Solution: don't choose samples of extreme individuals
70
Threats to internal validity: attrition
Participants lost over time | Solution: careful follow up procedures, statistically compare those who dropped out to those who teamin
71
Threats to internal validity: selection
One group systematically differs from the other in ways unrelated to the intervention Solution: randomization
72
Threats to internal validity: additive affects with selection
When any of the first 6 threats exists for one group but not the other Solution: randomization
73
5 threats to independent group designs (even true experiments)?
Contamination Experimenter expectancy Novelty Hawthorne Effect
74
Threats to IGD: contamination What is it? Examples?
When groups communicate with each other | Resentment, rivalry, control group seeking the treatment
75
Threats to IGD: experimenter expectancy effect What is it? Control through?
Unintentionally influencing results through observation, errors, etc. Control through double blindness
76
Threats to IGD: novelty effects
Newness of the tx has an effect rather than the tx itself
77
Threats to IGD: Hawthorne effect
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
3 types of quasi experimental designs?
- Nonequivalent control group - Interrupted time series - Time series with non equivalent control group
79
Nonequivalent control group Type of? What is it? Vulnerable to what?
Quasi experiment Groups that are truly comparable controls for many threats to internal validity Vulnerable to additive effects with selection
80
``` Interrupted time series What is it? What is often used? Compares what? 2 requirements? ```
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
Time series with Nonequivalent control group What is it? What kind of groups does it have? Rules out what effects?
Multiple pre and post tests Intervention and control group Rules out history and instrumentation effects
82
Descriptive methods
Do NOT manipulate IV | may establish correlation but not causation
83
#1 problem in quasi experiments? Why?
Additive effects with selection. Because of lack of randomization
84
Selection with maturation Selection with history Selection with instrumentation
- 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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