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Psych 203 > Quiz 3 > Flashcards

Quiz 3 Flashcards

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1
Q

What is Statistical Conclusion Validity and relevance to psychology?

A
  • The validity with which we can infer that the IV and DV covary
  • Inferential statistics allow us to establish this type of validity
  • Small sample size is a threat to statistical conclusion validity (it can keep you from finding a relationship between the IV and DV when one really exists)

RELEVANCE:
- establishes if researchers inference about co variation is shown to be correct (statistically significant)

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2
Q

What is Construct Validity and relevance to psychology??

A
  • degree of agreement between theoretical concepts and specific measuring device or procedure.

RELEVANCE:
- if what you are testing and the procedure you are using is accurate in the outcome/ results of the experiment.

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3
Q

Participant reactivity to Experimental

A
  • the way the participant perceives the study

Ex: participant can be more sensitive or receptive to treatment.

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4
Q

Experimenter Effect

A
  • Pygmalion effect/ the phenomenon where higher expectations lead to an increase in performance.
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5
Q

Compensatory Rivalry

A
  • when the control group responds negatively because they found out that they were put in the control group which can lead to competiveness against the treatment group.
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6
Q

Internal validity

A
  • Refers to rigor with which study was conducted.

Ex: how well it was designed and how well the study works.

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7
Q

History

A
  • event occurring during study but before posttest/outcome measurement

EX: HIV/AIDS prevention & Magic Johnson

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8
Q

Differential History

A
  • event occurring during study not experienced by both groups.

EX: only one group experiences the event occurring

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9
Q

Maturation

A

Growing out of it. People’s opinion change

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10
Q

Instrumentation

A
  • Changes in way the DV is measured during the course of study.

EX: Autism/Autism Spectrum Disorder

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11
Q

Testing

A
  • Pre-test affects post-test scores.

EX: studying between tests increase positive outcomes.

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12
Q

Regression Effects

A
  • Pseudo effects assumed to be due to the IV but really due to regression to mean

EX: selecting one extreme aspect you are trying to study

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13
Q

Selection of Participants

A

Randomly selection

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14
Q

Attrition

A

People drop out!!!

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15
Q

Differential Attrition

A
  • cluster sampling, more men than women drop out/ uneven amount.
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16
Q

External Validity

A

-generalizing findings to people, setting, treatments, outcomes, time outside of study. It goes from specific to general

RELEVANCE: the principle goal of psychological research

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17
Q

Population

A
  • generalize from sample to larger population

RELEVANCE: knowing if you can transfer your collected date from the sample to the entire population.

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18
Q

Ecological

A
  • generalize across settings.

RELEVANCE: seeing if you can transfer data to different settings.

19
Q

Temporal

A
  • generalize across time/seasons.

RELEVANCE: Transferring the collected data throughout time and seasons to see the validity within.

20
Q

Treatment Variation

A
  • generalize across variables in treatment
21
Q

Outcome

A
  • generalize across related dependent variable.
22
Q

Weak Designs

A
  • design with no pretest

RELEVANCE: no starting point in psychological research.

23
Q

One-group post-test only

A
  • weak design because there is only one group so there’s nothing to compare to.
24
Q

One-group pretest-post-test

A
  • one single group experiences treatment and post treatment assessment

(Con: it cannot effectively evaluate effectiveness of treatment/intervention without pretest)

RELEVANCE: It is sometimes a necessity in health research
Posttest only with nonequivalent groups

25
Q

Non-equivalent groups

A
  • not the strongest design and both non-equivalent groups have no similarities/no connections.

Ex: stress induced test to social class experiment, it is a mistake because the lower class is always usually stressed.

(CON: no pretest and pretest will help in saying why these two groups are non-equivalent)

26
Q

Strong Experimental Designs

A
  • Between participant designs
  • Within participant designs
  • Mixed designs
  • Pretest-posttest control group design
27
Q

Between participant designs

A

comparing one or more experimental groups or comparing one or more experimental groups with the control group

(EX: compare students with classical vs. jazz background or classical, jazz, and white noise) (Pro: increases test performance)

28
Q

Within participant designs

A
  • repeated measure design/ one or more participant going through multiple trials and posttest after each trial.

(EX: healthy community study)

(PRO: control error factor/minimal error factor)

(CON: run the risk of something making the groups perform differently, being exposed repeatedly for intervention, using subject as own control group)

29
Q

Mixed designs

A
  • design format that includes both between-group design and within-participant design.

(EX: three neighborhoods: upper, middle, and lower and 16 stores)

(CON: everyone can have a different interpretation about the amount for each social class) (the between group would be the income and the within design would be the time/ Phase I: 2013-2014/ Phase II: 2014-2015

30
Q

Pretest-posttest control group design

A
  • Factorial designs
31
Q

Main Effects

A
  • influence of 1 independent variable on dependent variable
32
Q

Interaction effects

A
  • is there something that is changing the effect of the independent variable
33
Q

Row means

A
  • means from level of independent variable
34
Q

Cell Means

A
  • average of people in cells
35
Q

Two-way interactions

A
  • where the two lines of the graph intersect
36
Q

Within subject’s factorial with independent variables

A
  • All subjects get all conditions
37
Q

IRB: Institutional Review Board

A
  • the committee at your university that reviews research proposals in order to ensure adequate protection for the people that will be participating in the study.

RELEVANCE: ensuring that every research study conducted is ethical.

38
Q

Selecting samples

A
  • something that justifies who you are choosing and why
39
Q

Informed Consent

A
  • ensuring the research participant is aware of all potential risk and cost involved in a treatment or procedure.
  • Scheduling research participants
  • Determining sample size
  • Design and selection of instruments
  • Debriefing
40
Q

Threats to Construct Validity

A
  • Participants reactivity to the experimental situation
  • Research participants’ motives and tendencies that affect their perceptions of the situation and their responses on the dependent variable
  • Influenced by the demand characteristics
  • any of the cues available in an experiment, such as instructions, rumors, or setting characteristics that influence the responses of participants
  • primary motive— positive self-presentation (participants frequently want to respond in such a way as to present themselves in the best way possible; may try to guess what the experimenter “wants” and responds in that way)
  • Experimenter effects
  • actions and characteristics of researchers that influence the responses of participants
  • can be intentional and unintentional
  • Experimenter’s motive of supporting the study hypothesis can lead to bias
  • Ways experimenter may bias the study:
  • experimenter attributes
  • biasing experimenter effects attribute to the physical and psychological characteristics of the researcher
  • 3 categories
  • e.g., experimenter’s age, gender, race, religion
  • e.g., experimenter’s anxiety level, need for social approval, hostility
  • e.g., prior contact between experimenter and participant, is the experimenter naive or experienced
  • experimenter expectancies
  • biasing experimenter effects attributable to the researcher’s expectations about the outcome of the experiment
  • e.g., experimenter acts differently towards experimental vs. control group to influence study to support their hypothesis
41
Q

Threats to Internal Validity

A
  • History
  • Differential History
  • Maturation
  • Instrumentation
  • Testing
  • Regression Artifact
  • Attrition
  • Differential Attrition
  • Selection
  • Additive and interactive effects
42
Q

Quasi Experimental Design

A
  • Research procedure in which the scientist must select participants for different conditions from preexisting groups. Different from true experiment because you don’t have random assignment. You still have manipulation
43
Q

Problems with Quasi Experiment

A
  • preexisting differences b/w groups (You can pretest differences on DV and find out if they do differ significantly) IV and group membership (often a subject variable) confounded when participants assigned to conditions based on group membership

Psych 203 (1 decks)

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