Research Methods Final

Front 1

When the independent variable is manipulated and tested between subjects

Back 1

Independent groups design

Front 2

When the independent variable is manipulated in a between subjects design and equivalent groups are made through random assignment

Back 2

Matched groups design

Front 3

Groups are formed because of their already existing subject characteristics

Back 3

Nonequivalent groups design or
Ex post facto

Front 4

When the independent variable is tested within subjects

Back 4

Repeated-measures design

Front 5

Different levels of the IV are administered to different groups of participants
Each participant has only one DV score, so they are not varied within each participant

Back 5

Between-subjects

Front 6

Different levels of the IV are administered to each participant
Each participant has as many DV scores as there are levels
Can vary both within and between subjects

Back 6

Within-subjects

Front 7

What test do you use when you have 2 separate groups of participants and you want to compare means from these groups?

Back 7

Independent samples t-test

Front 8

What test would you use when you have one group of participants being tested 2 times and you want to compare the means at the 2 different times?

Back 8

Dependent samples t-test
Within-subjects and or matched groups

Front 9

The variability of each of the sets of scores being compared ought to be similar
One of the assumptions in analyzing 2 level designs

Back 9

Homogeneity of variance

Front 10

Single factor--two levels, between subject design

Back 10

Independent Samples t-test

Front 11

Single factor--two levels, within-subject design

Back 11

Dependent samples t-test

Front 12

Single factor--more than two levels, between-subject design

Back 12

Regular One-Way ANOVA

Front 13

Single factor--more than two levels, within-subject design

Back 13

Repeated Measures One-Way ANOVA

Front 14

A variable for which a number of intermediate values exist
Ex.: dosage level of a drug
What type of graph is best to use?

Back 14

Continuous variables
Line graphs - estimate in-between effects

Front 15

A variable in which each level represents a distinct category and no intermediate points can occur
What is the appropriate graph to use?

Back 15

Discrete variable
Bar graph

Front 16

These members are led to believe they are receiving some treatment when in fact they aren't
Only measures the psychological effects

Back 16

Placebo control group

Front 17

These are often used in research designed to assess effectiveness of some program or psychotherapy
They are experiencing the problem, but not the program designed to alleviate it
They will receive treatment after

Back 17

Waiting list control groups

Front 18

They experience the same events as the experimental group except for one slight difference
Each member is matched to a member of the experimental, so time spent on events is constant

Back 18

Yoked control groups

Front 19

Indicate the amount of variability that occurred in each condition
Shown on bar graphs

Back 19

Error bars

Front 20

This test deals with nominal categories and the differences between observed and expected

Back 20

Chi Square

Front 21

This design involves any study with more than one IV

Back 21

Factorial Design

Front 22

The term "levels" refers to what in the factor?

Back 22

The number of levels of the independent variable

Front 23

How many conditions are in a 2 x 3 design?

Back 23

6

Front 24

When the row means or column means do not equal each other
Requires combining all of the data for each of the levels of that factor

Back 24

Main effect

Front 25

Occurs when the effect of one IV differs/depends on the level of another IV

Back 25

Interaction

Front 26

When there are both types of between-subjects and a within-subjects variable present
At least one must be tested between and one within subjects

Back 26

Mixed factorial design

Front 27

When a between-subjects factorial include both a manipulated IV and a subject variable
They can yield an interaction between the type of person and the environment

Back 27

P x E designs

Front 28

When a P x E design includes both a between-subjects and a within-subjects factor

Back 28

mixed P x E factorial

Front 29

Used to prevent confounding order effects

Back 29

Counterbalancing

Front 30

Variables that consist of some already existing attribute of a person (gender, age, trait)
Aren't really manipulated, but are of interest
Unable to draw causal inferences

Back 30

Subject variables

Front 31

Example of a P x E design, which measures both the nonmanipulated subject and manipulated environment
Interaction is the most interesting
Ex. Females performance on math problems in groups of females or a minority

Back 31

ATI (Aptitude-Treatment Interaction) designs

Front 32

There is no manipulation, so there can be no causation

Back 32

Correlation

Front 33

Both variables change in the same direction
High score on one relates to a high score on the other

Back 33

Positive correlation

Front 34

Variables change in opposite directions
It is an inverse relationship

Back 34

Negative correlation

Front 35

This correlation is used when both variables are interval or ratio

Back 35

Pearson's r

Front 36

This correlation is used when the variables are both ordinal

Back 36

Spearman's rho

Front 37

Provides a visual representation of the relationship shown by a correlation

Back 37

Scatterplot

Front 38

This weakens the correlation when this happens to one or both of the measured variables

Back 38

Restricting the range

Front 39

A portion of variability in one of the variables in the correlation that can be accounted for by variability in the second variable
Always positive
Found by squaring Pearson's r

Back 39

Coefficient of determination r squared

Front 40

Indicates the linear relationship between variables

Back 40

Line of best fit

Front 41

What are some caveats of correlations?

Back 41

Only applicable for linear relationships between variables
May be misleading if the range is restricted

Front 42

Have to be careful of this problem in correlations, for causation cannot be explained

Back 42

Third variable problem

Front 43

These attempt to statistically control for the third variable

Back 43

post facto or partial correlations

Front 44

Used to predict one variable based on the other

Back 44

Regression

Front 45

What is the equation for a regression line?

Back 45

y = mx + b
y = bx + a

Front 46

The variable that is being predicted in a regression (Y)

Back 46

Criterion variable or predictor variable

Front 47

The existence of the correlation by itself does not allow one to decide about the direction of causality

Back 47

Directionality problem

Front 48

Using this increases confidence about directionality in a correlation
Investigates correlations at several points in time

Back 48

Cross-lagged panel correlation

Front 49

Correlating between the items from two halves of a subtest
Should be high if test is reliable

Back 49

Split-half reliability

Front 50

Correlation between scores of test taken at two different times on the same measure

Back 50

Test-retest reliability

Front 51

The ability of a test to predict some future event
Tests what it is designed to measure

Back 51

Criterion validity

Front 52

Involves one criterion variable and a minimum of two predictor variables

Back 52

Multiple regression

Front 53

A multivariate technique where a large number of variables is measured and correlated with each other

Back 53

Factor analysis

Front 54

What differentiates true experiments from quasi experiments?

Back 54

Degree of control
True experiments have random assignment of particular conditions and manipulated IVs while Quasi may have measured or manipulated IVs and probably lack random assignment

Front 55

These exist whenever causal conclusions cannot be drawn because there is less than complete control over the variables in the study, usually because random assignment is not feasible

Back 55

Quasi-experiments

Front 56

Design where groups are not equal to each other at the start of the study and they also experience different events in the study itself
They are effective for evaluating treatments where random assignment is impossible

Back 56

Nonequivalent control group design

Front 57

Measures are taken for an extended period before and after the event expected to influence behavior
OOOOOTOOOOO

Back 57

Interrupted time series design
where T is the interruption

Front 58

What is the main advantage of a time series design?

Back 58

It allows researchers to evaluate trends over time

Front 59

Predictable patterns of events that occur with the passing of time

Back 59

Trends

Front 60

What are two ways to vary an interrupted time series design?

Back 60

OOOOOTOOOOO
OOOOO OOOOO-- Combining the features of a nonequivalent control group design (control group) with the interrupted time series design (long-term trend analysis) OR
OOOTOOOOOOO
OOOOOOOOTOO
Interrupted time series with switching replications

Front 61

The treatment is introduced at two different points in time for the two different groups
More confident in generality

Back 61

Interrupted time series with switching replications

Front 62

Refers to information that has already been gathered for some reason aside from the research project at hand
Educational, hospital or commercial records
No problem with reactivity for it requires no consent

Back 62

Archival data

Front 63

Systematic examination of qualitative information in terms of predefined categories
Some archival information needs to undergo this

Back 63

Content analysis

Front 64

What are some problems with archival research?

Back 64

Information on some part of the population may be missing
Experimenter bias - only selecting supporting records

Front 65

What are some advantages of archival research?

Back 65

The amount of information available is virtually unlimited
No reactivity

Front 66

Knowledge that their behavior is being observed can influence their behavior in ways that yield a distorted result

Back 66

Reactivity

Front 67

Why is archival research quasi-experimental?

Back 67

It does not allow for random assignment in between-subject designs

Front 68

Applied research that attempts to assess the effectiveness and value of policies or specially designed programs

Back 68

Program evaluation

Front 69

A set of procedures for predicting whether a population of sufficient size exists that would benefit from the proposed program, whether that program could solve a clearly defined problem, and whether people would use it

Back 69

Needs analysis

Front 70

Someone in the community who has a great deal of experience and specialized knowledge about the problem at hand that is otherwise unavailable to the researcher

Back 70

Key informant

Front 71

Small group of individuals who respond to a set of open-ended questions about some topic, such as the need for a particular program

Back 71

Focus group

Front 72

Aimed at improvement and monitors the progress of some program and how people are responding

Back 72

Formative evaluation

Front 73

Overall assessments of program effectiveness
More threatening

Back 73

Summative evaluation

Front 74

The actual costs of a program are monitored in relation to those costs to the effectiveness of the program's outcomes

Back 74

Cost-effectiveness analysis

Front 75

How people perform and especially interface with equipment

Back 75

Ergonomics

Front 76

Name 5 categories of human error

Back 76

Omission
Commission
Due to extraneous acts (distractions/ interruptions)
Sequential errors - wrong order
Time errors

Front 77

Know a lot about the program and are closer to the problem but can be biased

Back 77

In-house auditors

Front 78

Are in need of the details about a specific program, but are free of local pressures

Back 78

Outside auditors

Front 79

Deals with developing theory
Broad explanations of behavior that can be generalized

Back 79

Basic research

Front 80

The goal is to use this to solve real-world problems

Back 80

Applied research

Front 81

Examines a small number of participants, in some cases only one

Back 81

Small N designs

Front 82

The extent to which the findings for the group apply to an individual

Back 82

Individual-subject validity

Front 83

What do small-N designs provide that large-Ns don't

Back 83

Individual-subject validity

Front 84

What are some practical problems with large-N designs?

Back 84

Too expensive
Too many people
Too much time
Not needed to draw conclusions

Front 85

Any procedure that uses behavioral, especially operant, principles to solve real-life problems

Back 85

Applied behavior analysis

Front 86

How are single-subject designs carried out?

Back 86

No control group
The subject is compared to him/herself
ABAB design with baseline measure/withdrawal (A) and treatment (B)

Front 87

Provides an in-depth look at a representative situation
Adds reality and meaning

Back 87

Case studies

Front 88

Baseline measures are established and then treatment is introduced at different times

Back 88

Multiple baseline design

Front 89

A behavior is developed by reinforcing successive approximations to the desired behavior

Back 89

Shaping

Front 90

In this design, the target behavior is too difficult for the person to accomplish all at once so it must be shaped in small increments
Establish baseline, then criterion is made increasingly stringent
Good for health-related behaviors such as exercise

Back 90

Changing criterion design

Front 91

Refers to whether a particular applied behavior analysis program has value for improving society, whether its value is perceived as such by the study's participants and the extent to which the program is actually used by participants

Back 91

Social validity

Front 92

Used when comparing the effectiveness of more than one type of treatment for the same individual
The treatments are given in random order to avoid any potentially biasing order effects

Back 92

Alternating treatments design

Front 93

Studies the behaviors of people or animals as they act in their everyday environments

Back 93

Naturalistic observation

Front 94

Characteristics of doing research in the real world

Back 94

Greater validity, generalizability
Less control for extraneous variables
Less ability to differentiate IVs
Absence of control
Observer reactivity

Front 95

What are some characteristics of doing research in the lab?

Back 95

Greater ability to structure and control the experiment/extraneous variables
Problems with the contrived setting
Ability to control participant selection
Problems with generalizability

Front 96

The researcher joins the group being observed, or at least make their presence known

Back 96

Participant observation

Front 97

Having preconceived ideas about what will be observed and having those ideas color one's observations

Back 97

Observer bias

Front 98

Predefined behaviors that observers are trained to spot

Back 98

Behavior checklists

Front 99

Measured in terms of the percentage of times that observers agree
Helps reduce bias

Back 99

Interobserver reliability

Front 100

Behavior is sampled at predefined times and only at those times

Back 100

Time sampling

Front 101

Only a specific set of events are recorded for observations

Back 101

Event sampling

Front 102

Measures taken of behavior, either indirectly or directly, when the subject is unaware of the measurement being made
Can reduce reactivity

Back 102

Unobtrusive measures

Front 103

Structured set of questions or statements given to a group of people to measure their attitudes, beliefs, values, or tendencies to act

Back 103

Survey

Front 104

Good surveys require what type of sampling and not this type of sampling?

Back 104

Probability
Convenience

Front 105

Each member of the population has some definable probability of being selected for the sample

Back 105

Probability sampling

Front 106

The proportions of important subgroups in the population are represented precisely in the sample

Back 106

Stratified sample

Front 107

What is the best feature of interviews?

Back 107

It yields highly detailed one-on-one information

Front 108

What is a big problem with written surveys?

Back 108

Since they are sent by mail, the return rates are often low
Those who have strong opinions on the issue will most likely respond

Front 109

A tendency to agree with statements
Can be biased if all items are worded favorably

Back 109

Response acquiescense

Front 110

A question that is structured so that it is likely to produce an answer desired by the asker

Back 110

Leading question

Front 111

When the question is asking two different things, but it is impossible to answer differently between them

Back 111

Double-barreled question

Front 112

The complete list of individuals from whom the sample will be drawn

Back 112

Sample frame