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PSYC 433 > Midterm > Flashcards

Midterm Flashcards

1
Q

Belmont Report

A

1) Beneficence: risk-benefit analysis of findings vs. harm
2) Autonomy: respect for participants and their decisions
3) Justice: fairness in accepting risk and receiving benefits

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2
Q

APA Code of Ethics

A

1) Beneficence: risk-benefit analysis of findings vs. harm
2) Fidelity and responsibility: maintaining trust and following through
3) Integrity: don’t lie, cheat, plagiarize, etc.
4) Justice: fairness in accepting risk and receiving benefits
5) Respect: respecting individual differences, respecting consent, being aware of own biases

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3
Q

Six steps of a research project

A

1) Ask a question stemming from a theory
2) Develop a specific and testable hypothesis
3) Select a method and design the study
4) Collect the data
5) Analyze data and draw conclusions
6) Report findings

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3
Q

How do we minimize harm?

A

1) Informed consent
2) Debriefing
3) IRB

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3
Q

What defines experimental design?

A

Must have manipulation of independent variables and random assignment

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4
Q

What is a quasi-experimental or subject variable?

A

A trait that cannot be changed about the participant, but participants can be grouped based on these traits (height, shoe size, age, eye color, etc.)

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5
Q

Internal validity

A

The extent to which causal conclusions can be substantiated

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6
Q

External validity

A

The extent to which results can be generalized

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7
Q

Construct validity

A

The degree to which variable operations accurately reflect the construct they’re designed to measure (free from systematic error)

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8
Q

Criteria for causality

A

1) Relationship between variables
2) Causal variable precedes affected variable
3) No possibility of a third variable affecting both (confounding)

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9
Q

What makes a true experiment?

A

A true experiment has internal validity

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10
Q

Reliability

A

The extent to which a measure is consistent (free from random error)

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11
Q

Ways to measure reliability

A

1) Test-retest reliability
2) Internal consistency
3) Inter-rater reliability

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12
Q

Test-retest reliability

A

If you measure the same individuals at two different points in time the results should be highly correlated

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13
Q

Internal consistency

A

Whether the individual items in a scale correlate well with each other – Cronbach’s Alpha assesses the correlation of each item with each other

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14
Q

Inter-rater reliability

A

The agreement of observations made by two or more judges

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15
Q

Ways to measure construct validity

A

1) Face validity
2) Content validity
3) Convergent validity
4) Discriminant validity
5) Predictive validity
6) Concurrent validity

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16
Q

Face validity

A

How obvious it is to the participant what the test is measuring

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17
Q

Content validity

A

Whether experts believe the measure relates to the concept being assessed

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18
Q

Convergent validity

A

The measure overlaps with a different measure that is intended to tap the same theoretical construct (the participant should be able to fill out two surveys and get correlating results)

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19
Q

Discriminant validity

A

The measure does not overlap with other measures that are intended to tap different or opposite theoretical constructs

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20
Q

Predictive validity

A

The measure’s ability to predict a future behavior or outcome

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21
Q

Concurrent validity

A

The extent to which the measure corresponds with another current behavior or outcome

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22
Q

Nominal scale

A

Numbers stand for categories but mean nothing themselves (male = 1, female = 2)

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23
Q

Ordinal scale

A

Numbers indicate rank order, indicating preference but not by how much (psych = 1, bio = 2, math = 3)

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24
Q

Interval scale

A

The distances between numbers on a scale are all equal in size, but zero is an arbitrary reference point (Likert scale)

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25
Q

Ratio scale

A

The only scale that measures a true amount of something. Zero means a non-existent amount of that variable, there cannot be negative numbers, and 4 is twice as much as 2

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26
Q

Close-ended question

A

Has a limited number of response alternatives, meaning higher specificity but less variety

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27
Q

Open-ended question

A

Allows respondents to generate their own answers, meaning more variety but less control and harder to analyze

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28
Q

Interview bias

A

The researcher may subtly suggest a desired response, interpret the response in the desired way, or probe open-ended questions to get the desired response

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29
Q

Respondent bias

A

Participants may act due to social desirability or response set (answering all questions similarly)

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30
Q

Ways to assess the construct validity of the independent variable

A

1) Pre-test
2) Manipulation check

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31
Q

Pre-test

A

Conducted before the actual study with a different set of participants and is meant to determine if the IV manipulation works as predicted

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32
Q

Manipulation check

A

Conducted during the study and assesses whether the manipulation of the IV had its intended effects

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33
Q

Ways to measure the dependent variable

A

1) Self-report
2) Behavioral
3) Physiological

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34
Q

Self-report

A

Asking participants about the behavior of interest; is easy and cheap, but is subject to bias

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35
Q

Behavioral report

A

Direct observations of participant behavior; is effective and direct, but can be expensive, time-consuming, and subject to reactivity

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36
Q

Physiological report

A

Directly recording responses of the body; is objective and measures strength of the reaction, but does not always capture valence and is subject to reactivity

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37
Q

Ways to control for participant expectations

A

1) Cover story: provides rationale
2) Filler items: reduces face validity
3) Placebo group: level of IV that shows role of expectations

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38
Q

Experimenter bias

A

When an experimenter might subtly suggest how they hope the participant will respond

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39
Q

Ways to reduce experimenter bias

A

1) Double-blind study: experimenter is blind to IV group of the participant
2) Blind to hypothesis: experimenter does not know the hypothesis of the study
3) Automated scripts and computers
4) Running participants in groups

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40
Q

Post-test only design

A

Participants are randomly assigned to one level of the IV and then measured

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41
Q

Pre-test Post-test design

A

Participants are given a pre-test and then randomly assigned to one level of the IV and measured

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42
Q

What is the purpose of a pre-test?

A

The pre-test gives a baseline measure of the DV before any IV manipulation in order to…
- ensure that groups are similar to start
- identify certain characteristics of participants
- measure the amount of change
- understand mortality

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43
Q

Between participants/independent groups

A

Each participant is randomly assigned to one level of the IV

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44
Q

Within participants/repeated measures

A

Each participant is assigned to all of the levels of the IV

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45
Q

What are the advantages of a repeated measures design?

A
  • Participants are used more efficiently
  • Can control for individual differences as each participant is their own control
46
Q

What are the disadvantages of a repeated measures design?

A
  • Could give away the nature of the study
  • The order of presenting IV levels can impact results (control by counterbalancing and increasing time intervals)
47
Q

Mixed factorial design

A

Combination of between participants and within participants

48
Q

Matched pairs design

A

Order participants based on the independent variable, pair them in order, and randomly assign each pair to different groups

49
Q

Factorial Design

A

Any experimental design with more than one IV

Need to consider main effects and interactions

50
Q

Main effect

A

The direct effect of an IV on a DV. There is the potential for up to as many main effects as there are IVs

51
Q

Interaction

A

When the effect of an IV on a DV depends on the level of another IV. There is a possible interaction for every combination of IVs

52
Q

Moderator

A

An IV that affects the direction and/or strength of the relationship between another IV and the DV

Help us understand when an IV will impact a DV

Moderation exists when an interaction exists

“The effect of IV-1 on DV is moderated by IV-2”

53
Q

Mediator

A

Represents the mechanism by which an IV influences the DV

Usually another DV that offers a deeper explanation for how the IV causes the main DV

IV –> mediator –> DV

54
Q

Descriptive statistics

A

Statistics that describe the sample data
- measure of central tendency
- measures of variability
- distribution
- frequency
- correlation
- regression
- effect size

55
Q

Distribution

A

General name for any organized set of data

56
Q

Frequency

A

How often a score occurs

57
Q

N

A

Sample size (# of data points)

58
Q

Frequency distribution

A

Shows the number of times a score occurs in a set of data

Usually in a frequency distribution table

59
Q

Bar graph

A

Used to demonstrate frequency of nominal or ordinal data

60
Q

Histogram

A

Used to demonstrate frequency of interval or ratio data

61
Q

Frequency polygon

A

Identical to histogram (frequency of interval or ratio data) but uses connected data points instead of bars

62
Q

Mode

A

Most frequent score

Indicates central tendency with all scales including nominal scales

63
Q

Median

A

Score than divides the group in have with 50% scoring above and 50% scoring below

Indicates central tendency with ordinal, interval, and ratio scales

64
Q

Mean

A

Found by adding all the scores and dividing by the number of scores

Indicates central tendency with interval or ratio scales

65
Q

Range

A

Largest value minus the smallest value in the sample – often inaccurate measure due to outliers

66
Q

Standard deviation

A

Average deviation of the scores from the mean – more accurate since it uses every score

67
Q

Variance

A

The standard deviation squared

68
Q

Correlation plots

A

Measure the strength and direction of the relationship between two variables

69
Q

Effect size

A

Refers to the strength of association between variables; provides a scale of values that is consistent across all types of studies (for example, Pearson’s r)

70
Q

Pearson’s r

A

r = 0.15 –> small effect size
r = 0.3 –> medium effect size
r = 0.4 –> large effect size

71
Q

r squared

A

Transforms Pearson’s r into a percentage of variance in one variable that can be accounted for by the other variable

72
Q

Cohen’s d

A

Measures the standardized difference between two means

d = 0.5 –> the means are half of a standard deviation apart (medium effect size)

73
Q

Simple regression

A

Predicts a score on one variable when the score on another variable is already known

Linear line of best fit through a scatterplot

74
Q

Multiple regression

A

Used to combine a number of predictor variables to increase the accuracy of prediction of a given criterion or outcome variable (R)

75
Q

Partial correlations

A

The correlation between two variables of interest with the influence of a third variable removed

76
Q

Inferential statistics

A

Used to determine whether a sample of scores is likely to represent a certain population of scores

Based on the probability that the difference between means reflects random error versus real difference

77
Q

Criterion

A

A value that tells us when we are going to decide a sample is too unlikely to have occurred through chance alone (alpha = 0.05)

78
Q

Sampling error

A

A sample statistic that differs from the population parameter it represents due to chance factors

79
Q

Type I error

A

The researcher rejects the null hypothesis when the null is actually true

80
Q

Type II error

A

The researcher fails to reject the null hypothesis when the null is actually false (alternative is true)

81
Q

Experimental realism

A

The extent to which experimental procedures have an impact on participants

82
Q

Mundane realism

A

The extent to which experimental events in the controlled laboratory setting are similar to events which occur in the real world

83
Q

Exact replication

A

An attempt to replicate precisely the procedures of a study to see whether the same results are obtained

84
Q

Conceptual replication

A

Attempting to replicate the relationship between conceptual variables from the original study, but operationalizing these variables in a different way

85
Q

Constructive replication

A

The replication wants to affirm the original research by fixing some methodological problems

86
Q

Destructive replication

A

The replication wants to prove that the original research was wrong due to methodological problems

87
Q

Advantages of meta-analysis

A
  • precision
  • objectivity
  • replicability
  • ability to make corrections
88
Q

Disadvantages of meta-analysis

A
  • statistics over reason
  • objectivity and replicability can vary
  • significant vs. practical
89
Q

Experimental research

A

Explaining behavior by determining cause and effect relationships among variables

90
Q

Correlational research

A

Looking for relationships among variables

91
Q

Descriptive research

A

Making observations that describe behavior

92
Q

Advantages of descriptive research

A
  • higher external validity
  • higher construct validity
  • higher mundane realism
93
Q

Disadvantages of descriptive research

A
  • lower internal validity
  • lower reliability
  • lower experimental realism
  • potential for observer bias
94
Q

Observational research

A

Describing behavior

Naturalistic or systematic

95
Q

Naturalistic observational research

A

The researcher makes observations in a natural, social setting

Qualitative: a small sample described in great depth (consider participant or nonparticipant and concealed purpose or not)

Inductive: begins with observations and generates hypotheses

96
Q

Systematic observational research

A

The selection, recording, and encoding of natural behaviors

Quantitative: operationalize construct, determine setting and mode of observation, select sampling strategy, and train observers

Deductive: have a theory from which we generate hypotheses and use data to test hypotheses

97
Q

Archival research

A

Using previously compiled information to answer research questions (statistical records, survey archives, written records)

98
Q

Advantages of archival research

A
  • free or cheap data
  • abundance of data
  • span of time periods
  • look at reactions to natural events
99
Q

Disadvantages of archival research

A
  • low internal validity
  • low reliability
  • biases/errors
  • no ability to gather extra information
100
Q

Confidence interval

A

The range of scores around the sample results within which you have confidence that the true population value lies (allows generalization)

101
Q

Probability sampling

A

Each member of the population has a specified probability of being included in the sample
- simple random sampling
- stratified random sampling

102
Q

Simple random sampling

A

Every member has an equal chance of inclusion in the sample

103
Q

Stratified random sampling

A

Subgroups are chosen and then random sampling occurs within those subgroups

104
Q

Non-probability sampling

A

We don’t try to accurately represent the entire population within our sample
- convenience sampling
- quota sampling

105
Q

Convenience sampling

A

Using the most convenient participants for your sample

106
Q

Quota sampling

A

Choose subgroups and then use convenience sampling within the subgroups

107
Q

Quasi-experimental designs

A
  • one-group pretest-posttest design
  • nonequivalent control group design without pretest
  • nonequivalent control group design with pretest
108
Q

One-group pretest-posttest design

A

Participants are tested on a quasi-experimental DV before and after the application of the IV (only one level of IV)

109
Q

Nonequivalent control group design (without pretest)

A

Participants are assigned to an IV level based on an established variable, undergo application of IV, and then have the DV measured

110
Q

Nonequivalent control group design (with pretest)

A

Participants are assigned to IV levels based on an established variable, pretested on the DV, undergo application of the IV, and then posttested on the DV

111
Q

Interrupted time-series design

A

Multiple measurements of the DV occur before and after treatment

112
Q

Interrupted time-series design with nonequivalent control group design

A

Two interrupted time-series designs are conducted with one group receiving a treatment and one group not receiving a treatment

113
Q

Developmental research designs

A
  • cross-sectional method
  • longitudinal method
114
Q

Cross-sectional method

A

Persons of different ages are studied at one point in time

115
Q

Longitudinal method

A

The same people are studied at different points in time as they age

PSYC 433 (1 decks)

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