PSYC2017 - Exam 3

Define the ethical principles of the Belmont report.

• principle of respect for persons

• principle of beneficence 

• principle of justice

characteristics of principle of respect for persons

• informed consent

• consideration of (lack of) autonomy

  • groups w/ limited autonomy are entitled to special protection

  • can’t take advantage of people via some power differential

informed consent

consent based on being fully informed about the risks and benefits of participating in a research study

characteristics of principle of beneficence

• do good

• should be a balance between costs and benefits to participants

• includes protecting one’s anonymity and confidentiality

principle of justice

• who bears the risks 

• who bears the benefits

• should be a balance between those who participate in a study and those who benefit from it

Describe the ethical principles of the American Psychological Association (APA).

• principle of respect for persons

• principle of beneficence 

• principle of justice

• principle of fidelity and responsibility

• integrity

characteristics of principle of fidelity and responsibility

• establish relationships of trust

• accept responsibility for professional behavior

characteristics of principle of integrity

• strive to be accurate, truthful, and honest in one’s role as a researcher, teacher, or practitioner

Describe the procedures in place to protect human rights in research.

Describe the procedures in place to protect animal rights in research.

Articulate ways in which ethical decisions requires balancing priorities, such as research risk vs. societal benefits.

Institutional Review Board (IRB)

committee responsible for interpreting ethical principles and ensuring that research using human participants is conducted ethically

What are IRB panels composed of?

• scientist

• individual w/ academic interests outside the sciences

• community member w/ no ties to the institution

• prisoner advocates (in cases of a study w/ prisoners)

What is the IRB responsible for?

review proposals for research projects and determine the degree it conforms with ethical standards

When may consent not be required?

• naturalistic observation in low-risk public settings

• self-report of non-intrusive questions

deception by omission

withholding details of the studying from participants 

deception by commission

lying to participants

debriefing

description of the deception and explanation of why deception was used in the study

What are types of research misconduct?

• data fabrication

• plagiarism

• self-plagarism

data fabrication

researcher manipulates data to fit a hypothesis

plagiarism

representing another’s ideas as one’s own

self-plagiarism

potentially unethical practice of reusing one’s writings verbatim

replacement

researcher should find alternative to animals whenever possible

refinement

researcher must modify procedures to minimize animal distress

reduction

researcher must adopt designs that require the fewest animal subjects as possible

Apply the three criteria for establishing causation to experiments.

Explain why experiments can support causal claims.

• establish covariance

• establish temporal precedence

• establish internal validity

independent variable

manipulated variable controlled by the experimenter

dependent variable

measured variable affected by the independent variable

control variable

variable that is fixed to a certain level and held constant by the experimenter

How do experiments establish covariance?

manipulation of the IV introduces observable variance, which allows observations on how the DV varies

What characteristics help experiments establish covariance?

• comparison groups

• control groups

• treatment groups

comparison groups

individuals with different levels of the IV

control group

neutral level or non-level of the IV

treatment group

nonneutral level of the IV

How do experiments establish temporal precedence? 

manipulation of the IV occurs before the DV is measured

How do well-designed experiments establish internal validity?

rules out confounds

design confound

another variable that coincidentally varies along with the IV and provides an alternative explanation for the results

unsystematic variability

random effects that influence both or several comparison groups unrelated to confounds

between-group

• posttest-only design

• pre-post design

posttest-only design

exposed to one level of the IV and DV is measured once

pre-post design

DV is measured before and after exposure to IV level

Why might a research conduct a between-groups study?

• measures direction of change

• enhances statistical power

within-group

• repeated-measures design

• concurrent measures design

repeated-measures design

participants are exposed or assigned at each level of the IV and the DV is repeatedly measured at each level

concurrent-measures design

participants are exposed to all levels of the IV at roughly the same time and a single preference is the DV

Why might a research conduct a within-group study?

• participants are exposed to multiple IV levels

• allows participants to be their own controls and to be representative of each other

• increases statistical power

What are disadvantages of within-groups designs?

• practice/fatigue effect

• carryover effect

• demand characteristic

practice/fatigue effect

participants get better or worse at a task from practice/fatigue

demand characteristic

something about the study that leads participants to guess the study goals and change their behavior accordingly

carryover effect

effect carrying over from one condition to the next

full counterbalance

all possible order combinations are available

partial counterbalance

some of all possible order combinations are available

types of design confounds

• selection effects

selection effects

occurs when participants in one group of the IV are systematically different than participants in the other level of the IV

random assignment

assign participants to different conditions of the IV

matched groups

participants in different conditions are matched based on some individual characteristic, then randomly assign matched individuals to condition groups

order effects

How do experimenters avoid design confounds?

How do experimenters avoid selection effects?

• random assignment

• match groups

How do experimenters avoid order effects?

• counterbalancing

Interrogate an experimental design using the four validities.

How might construct validity interrogate an experimental design?

• extent to which the operational variables in a study are a good approximation of the conceptual variable

• with respect to reliability and validity

How might external validity interrogate an experimental design?

• extent to which a study generalizes the population or other contexts

• with respect to sampling method and building a representative sample

Describe how researchers can design studies to prevent internal validity threats.

Interrogate an experiment with a null result to decide whether the study design obscured an effect or whether there truly is no effect to find.

Describe how researchers can design studies to minimize possible obscuring factors.

confounds

• third or additional variable that could explain empirical findings

• threatens the internal validity of a study

threats to internal validity (more specific to pre-post and repeated-measure designs)

• maturation

• history

• regression to the mean

• attrition

• testing

• instrumentation

threats to internal validity applicable in any experiment

• observer bias

• demand characteristics

• placebo effects

maturation threat

changes in the variable that emerge spontaneously over time

history threat

when some external or real-world event affects members of one of the experimental groups

How are maturation and history threats countermeasured?

include a control group

regression (to the mean)

statistical concept when an extreme level in an observed variable is likely to return to the mean level in the future

attrition threat

reduction in participants from pre- to post-test, especially if systematic

How is attrition threat countermeasured?

• remove extreme data points from attritting participants

• investigate why participants drop-out and adapt incentives

• use statistical methods that can handle missing data

testing threat

change in a participant’s response on the DV as a result of experiencing the DV more than once

How is testing threat countermeasured?

• include a control group

• use different tests or instruments

instrumentation threats

when an instrument or measurement tool changes over time

How is intrumentation threat countermeasured?

• rigorous training of raters

• use post-test only design

What can null effects be resulted from?

• not enough between variance

• too much within variance

What are the interrogating null effects due to not enough between variance?

• insensitive measures

• ceiling and floor effects

• weak manipulations

• insufficient power

insensitive measures

• measure hasn’t been operationalized in a way to distinguish differences in the conceptual variable

• precision problem

ceiling and floor effects

• questions are too easy or too hard

• items are too agreeable or too disagreeable

• insufficient variability

• boundary problem

weak manipulation

• manipulation of the IV did not have an effect or change on the thing that wanted to change

• insufficient variability in the IV

What are the interrogating null effects due to not enough within variance?

• measurement error

• individual differences

• situation noise

• insufficient power

measurement error

can be countered by using reliable and valid measures

individual differences

• participants have their personal differencies

• can account for difference with a within-groups or pre-post design

situation noise

• any kind of external distraction that could cause variability within-groups that obscure between-groups differences

• can be minimized by controlling surroundings of an experiment

insufficient power

the lower the statistical power, the higher the probability of making a Type II error (retaining the null hypothesis when that hypothesis is false)

What are ways to maximize power?

• have a large sample size

• use strong experimental manipulations

• study theoretically plausible phenomenon

• reduce erroneous causes of variability

Articulate how a factorial design works.

What are reasons to use a factorial design?

• test theories

• test limits

  • external validity

Interpret interaction effects with words.

Interpret interaction effects with tables.

Interpret interaction effects with graphs.

Given a factorial notation, identify the number of independent variables.

Given a factorial notation, identify the number of levels of each variable.

Given a factorial notation, identify the number of cells in the design.

Given a factorial notation, identify the number of main effects.