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Psychology 242, Dr. McKirnan. Revised 9/11/13. Right click for “full Screen” or “end show”. Left click to proceed, . Lectures 3: Developing research questions and hypotheses. Basic experimental design & internal validity . Research questions, hypotheses & designs.

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Revised 9 11 13

Psychology 242, Dr. McKirnan

Revised 9/11/13

Right click for “full Screen” or “end show”. Left click to proceed,

Lectures 3:

Developing research questions and hypotheses.

Basic experimental design & internal validity.

Week 3; Experimental designs


Research questions hypotheses designs

Research questions, hypotheses & designs

  • How do social values affect science?

  • Where do research questions & hypotheses come from.

  • Variables in research

  • Basic experimental designs

  • True vs. Quasi- Experiments

Phenomenon

Theory

Hypothesis

Methods

& data

Results

Discussion &

Conclusions

Week 3; Experimental designs


The big picture introductory lectures

The big picture: Introductory lectures

  • How do social values affect science?

  • Where do research questions & hypotheses come from.

  • Variables in research

  • Basic experimental designs

  • True vs. Quasi- Experiments

Phenomenon

Theory

Hypothesis

Methods

& data

Results

Discussion &

Conclusions

Week 3; Experimental designs


Social values

Social Values…

Phenomenon

…affect what we choose as our research question…

Theory

Hypothesis

Methods

& data

Specific methods are more standard and objective

Results

Discussion &

Conclusions

…and our conclusions

Week 3; Experimental designs


Values theory and data in the scientific process

Values, theory and data in the scientific process.

Social values help define a scientific “problem” or question.

Norms, values (& data) determine what is credible / fundable.

Phenomenon

Theory

Theory is influenced by norms + empirical background of field.

Hypothesis

Science hinges on clear, objectively stated hypotheses.

Clear hypotheses lessen bias in interpreting results.

Methods

& data

Methods & analyses are most objective, but fields vary in methodological rigor.

Results

Discussion &

Conclusions

  • The “meaning” of a finding is influenced by cultural & social values or concerns.

    …for science and, particularly, for society.

Week 3; Experimental designs


Values and science the internet and sexual risk

Values and science: The internet and sexual risk.

Social values help define a scientific “problem” or question.

Norms, values (& data) determine what is credible / fundable.

Phenomenon

Theory

Sexual internet use became a large issue for gay/bisexual men in the 2000s

  • Internet use exploded, and became a sexual venue.

  • Men who have sex with Men [MSM] seemed particularly likely to be risky via internet sex.

  • The HIV prevention field needed to understand how this worked.

  • HIV made research on MSM a legitimate and important topic

Hypothesis

Methods

& data

Results

Discussion &

Conclusions

Week 3; Experimental designs


Values theory and data in the scientific process1

Values, theory and data in the scientific process.

Phenomenon

Theory

Theory is influenced by values & empirical background of field.

Hypothesis

Several theories may help us explain internet  sexual risk:

  • Theories of depression: a Ψ factor within the person may interfere with his decision making.

  • Social structure: The social environment of MSM may influence internet use & risk.

    Taking an individual v. social perspective can be a value choice.

Methods

& data

Results

Discussion &

Conclusions

Week 3; Experimental designs


Values and science climate change 1

Values and science: climate change, 1.

Phenomenon

Theory

Hypothesis

Science hinges on clear, objectively stated hypotheses.

Clear hypotheses lessen bias in interpreting results.

Methods

& data

  • Statistical tests of “mediation” can test relatively clear tests of hypotheses about depression and sexual risk

Results

Internet +sex

Depression

Risk

Discussion &

Conclusions

Week 3; Experimental designs


Values theory and data in the scientific process2

Values, theory and data in the scientific process.

Widely shared conventions make value judgments less important. However:

  • Behavioral sciences vary considerably in their rigor.

  • Choosing, e.g., quantitative vs. qualitative research can be a value choice.

  • Fields such as literary criticism, history or feminist studies may use substantially different methods.

Phenomenon

Theory

Hypothesis

Methods

& data

Methods & analyses are most objective, but fields vary in methodological rigor.

Results

Discussion &

Conclusions

Week 3; Experimental designs


Values theory and data in the scientific process3

Values, theory and data in the scientific process.

No scientific finding can completely answer a research question;

  • Its meaning is affected by existing theory and empirical findings.

  • Society may not be “ready” for certain findings: e.g., data showing that GLBT people are not “mentally ill” were rejected for many years.

  • Many important findings – e.g., from economics – have little affect on social policy if they contradict a widely shared ideology.

Phenomenon

Theory

Hypothesis

Methods

& data

Results

Discussion &

Conclusions

  • The “meaning” of a finding is influenced by cultural & social values or concerns.

    …for science and, particularly, for society.

Week 3; Experimental designs


The big picture introductory lectures1

The big picture: Introductory lectures

  • How do social values affect science?

  • Where do research questions & hypotheses come from.

  • Variables in research

  • Basic experimental designs

  • True vs. Quasi- Experiments

Phenomenon

Theory

Hypothesis

Methods

& data

Results

Discussion &

Conclusions

Week 3; Experimental designs


R esearch questions

Research questions

Where do research questions come from?

  • Practical questions

  • Unanswered questions from previous research

  • Testing theories.

Week 3; Experimental designs


Sources of research questions

Sources of research questions

Practical / applied questions

  • Describe or explain an important social process

  • Evaluate an intervention or policy change

Chicago school closings and reassignment are predicted to result in better scores.

Do they over 5 years of follow-up?

E X A MP L E

Week 3; Experimental designs


Sources of research questions1

Sources of research questions

Unanswered questions from previous research

  • Clarify conflicting / unclear findings

    • Who actually uses the internet to meet people…

  • Do previous findings generalize to…

    • …different groups

      • Many Social Psychology studies enroll middle(+) classWhite female undergraduates in research labs.

    • …different research areas

      • Can interventions to increase healthy behavior generalize to recycling and energy conservation?

    • …different research approaches

      • Do controlled lab studies generalize to less controlled field research?

  • Practical / applied questions

    Week 3; Experimental designs


    Theories

    Theories

    Practical / applied questions

    • Use existing theory to explain a new phenomenon

      • “Sensation seeking” personality is associated with drug use. Might it also explain unsafe sex in adolescents or gay men?

    • Test contrasting theories of a phenomenon

      • How much is adolescent problem behavior controlled by psychological variables (depression) vs. peer influence?

    • Develop new / expanded theory

      • We discriminate among very subtle differences in smell. Might olfactory cues affect who we are attracted to?

    Unanswered questions from previous research

    Testing theories

    Week 3; Experimental designs


    Revised 9 11 13

    Theories

    How do we go from a research question to an actual study?

    • Phenomenon

    • Theory

    • Hypothesis

    • Methods

    Key Terms:

    • Hypothetical Construct

    • Operational Definition

    Week 3; Experimental designs


    The research process

    The research process

    Phenomenon

    Overall issue or question;

    What controls emotional states?

    Why are some people vulnerable to depression?

    Theory

    Possible explanation: “How it works” statement

    Several theories may help explain the phenomenon

    Theory 1

    Emotional stability requires secure emotional attachments.

    Theory 2

    Some brains are genetically disposed to serotonin depletion during stress

    Week 3; Experimental designs


    Research process 2

    Research process, 2

    Theory 1

    Emotional attachment  emotional stability.

    A theory can lead to several hypotheses

    Hypothesis 1

    Fewer parent – child interactions  vulnerability to depression.

    Hypothesis 2

    Emotional support during stress  less depression

    A given hypotheses can be tested in several ways

    Methods 1

    Survey measurement: assess # of “family meals” per week, correlate it with self-reported depression.

    Methods 2

    Experiment: ½ have structured parent / child interactions, ½ do not, induce stress to both groups, assess depression

    Week 3; Experimental designs


    Research process 3

    Research process, 3

    Theory 1

    Emotional attachment  emotional stability.

    Hypothesis 1

    Family interactions  depression.

    Hypothesis 2

    (Non)Support + stress  depression

    Some hypotheses are best tested in a measurement approach, and some with experimental designs

    Best tested by a measurementstudy

    • Family interactions are difficult to bring into the lab,

    • Possible ethical problems.

    Can be tested in an experiment:

    Both support and stress can be controlled or manipulated in the lab.

    Week 3; Experimental designs


    Research process the big picture

    Research process: The Big Picture

    Phenomenon

    Big picture question.

    Theory 1

    Possible explanation, invoking one set of hypothetical constructs.

    Theory 2

    Alternate explanation, invoking other hypothetical constructs.

    Hypothesis 1

    A prediction that logically flows from – and tests – the theory.

    Hypothesis 2

    Another prediction that tests the same theory.

    Methods 1

    Operationally define the variables & test the hypothesis.

    Methods 2

    An alternate operational definition & way of testing the hypothesis.

    Week 3; Experimental designs


    Question 1

    Question 1

    A hypothetical construct is…

    A = A specific prediction about the outcome of an experiment

    B = A little known band from Muncie Indiana

    C = A general ψ process that underlies our observations

    D = A central element in a theory

    Week 3; Experimental designs


    Question 2

    Question 2

    To be testable, a hypothesis…

    Must rest on operational definitions.

    A = true

    B = False

    C = I don’t know

    Week 3; Experimental designs


    Question 21

    Question 2

    An operational definition is

    A = The procedure(s) we use to measure a study variable

    B = The way we define our theory

    C = The procedure(s) we use to manipulate a study variable

    D = What we use to derive our hypothesis

    Week 3; Experimental designs


    Question 3

    Question 3

    To be testable, a hypothesis…

    Must potentially be found to be false.

    A = true

    B = false

    C = I don’t know

    Week 3; Experimental designs


    Question 11

    Question 1

    A theory…

    A = Leads to one specific hypothesis

    B = May be one of several ways to explain something

    C = Is not as important as simply collecting data

    D = Is what you make up to explain why you forgot your boy/girl friend’s birthday

    E = Is not really affected by social or personal values

    Week 3; Experimental designs


    The big picture introductory lectures2

    The big picture: Introductory lectures

    • How do social values affect science?

    • Where do research questions & hypotheses come from.

    • Variables in research

    • Basic experimental designs

    • True vs. Quasi- Experiments

    Phenomenon

    Theory

    Hypothesis

    Methods

    & data

    Results

    Discussion &

    Conclusions

    Week 3; Experimental designs


    Revised 9 11 13

    Theories

    Types and uses of variables in research:

    • Experiments

      • Independent vs. Dependent variables

    • Measurement / field studies

      • “Predictor” vs. “Criterion”

    • Forming variables:

      • Direct manipulation

      • Indirect manipulation

      • Measurement

    Week 3; Experimental designs


    Types of variables experimental designs

    Types of Variables:Experimental designs

    Independent VariableDependent Variable

    Defines the “contrast space”

    Models the phenomenon

    What is compared to what

    e.g., drug v. placebo

    • What is being explained;

      e.g., task performance

    Hypothetical “cause”

    • “Effect”

    Imposed by researcher as experimental conditions

    • Measured

      as the outcome

    Categorical

    • Continuous

    Week 3; Experimental designs


    Types of variables measurement studies

    Types of Variables:Measurement Studies

    PredictorCriterionorOutcome

    Defines the “contrast space”

    Models the phenomenon

    What predicts the outcome?

    e.g., age, education, gender

    • What is being explained;

      e.g., political attitude

    Hypothetical “Cause”

    • “Effect”

    Measured

    not imposed by researcher

    • Measured

      as the outcome

    Continuous

    • Continuous

    Week 3; Experimental designs


    Revised 9 11 13

    Experimental v. Measurement designs

    Experimental designs

    • Manipulating the Independent Variable:

      • Enhances internal validity

      • May lessen external validity

    • Participants randomly assigned to experimental v. control groups

    Measurement (or correlational)designs

    • Measurement “in the field”

      • May enhance external validity

      • Typically lessens internal validity

    • Sampling very important

    Week 3; Experimental designs


    Creating independent variables ivs

    Creating independent variables [IVs]

    1. Direct experimental manipulation

    • Most typical of “true” experiments

    • Maximum control over IV

      2. Indirect manipulation via experimental or research conditions

    • Less direct control over IV

      3. Quasi-Independent variables: forming groups using a measured variable.

    • Experiments without complete control over variables

    • Used in measurement studies

    Week 3; Experimental designs


    Forming variables

    Forming Variables

    1.Direct experimental manipulations

    • Drug or biomedical intervention

    • Behavioral intervention or treatment

    • Focused experimental study of, e.g., specific stimuli

    • System-wide “treatment” (e.g., policy change, school-based)

    • Simple presence v. absence of the treatment or stimulus

  • Single v. multiple treatment doses

  • Type of treatment or stimulus

    • Structurethe IV

      vis-à-vis:

    Week 3; Experimental designs


    Direct experimental manipulation

    Direct experimental manipulation

    • Hypothesis: words presented in a semantic context are recalled better than when presented randomly.

    Independent Variable

    Dependent Variable

    Experimental group

    Target words presented within complete sentences

    Word recognition task

    Control group

    Target words presented randomly

    Word recognition task

    Completely controlled by the experimenter

    Experimental manipulation same as Independent Var.

    Week 3; Experimental designs


    Forming variables1

    Forming Variables

    2.Indirect experimental manipulations

    • Experimental “induction” of a mood or state…

      • “Stage manage” a social event 

      • Induce mood via description of the experiment

    Stress require presentation in front of peers

    Depression  Write about worst mistake you ever made

    Stereotype threat  “This test reflects on your group”

    Anxiety  Stage a robbery or fight

    Happiness  Lottery winnings?

    Relaxation  Meditation

    E X A MP L E

    Week 3; Experimental designs


    Forming variables2

    Forming Variables

    2.Indirect experimental manipulations

    • Experimental “induction” of a mood or state…

      • “Stage manage” a social event 

      • Induce mood via description of the experiment

    • Do a manipulation check to see if you actually manipulated your Independent Variable

      • Self-report, standard assessment (e.g., of stress)

      • Observer rating

    Week 3; Experimental designs


    Indirect experimental manipulation

    Indirect experimental manipulation

    • Hypothesis: happiness enhances pain resistance.

    Independent Variable

    Experimental Manipulation

    Dependent Variable

    Imagine you won the lottery – what will you buy first?

    Happy state

    Cold Presser Task (ice bucket)

    Experimental group

    Control group

    …what will you need to buy this month?

    Normal / baseline state

    Cold Presser Task

    Directly controlled by experimenter

    Notdirectlycontrolled by experimenter

    Our induction of the Independent Variable (happiness) is indirect.

    Week 3; Experimental designs


    Indirect experimental manipulation1

    Indirect experimental manipulation

    • Hypothesis: happiness enhances pain resistance.

    Independent Variable

    Experimental Manipulation

    Dependent Variable

    Imagine you won the lottery – what will you buy first?

    Happy state

    Cold Presser Task (ice bucket)

    Experimental group

    Control group

    …what will you need to buy this month?

    Normal / baseline state

    Cold Presser Task

    AManipulation Checktests whether the experimental manipulation actually induced the Independent Variable

    Week 3; Experimental designs


    Quasi independent variables

    Quasi-independent variables

    3.Create a quasi-Independent variable using a measured variable.

    • Categorize participants by measuring (not manipulating) something:

      • Scores over / under an established “cut point”,

        • e.g., over 4 depression symptoms on a standard scale.

      • Scores based on a frequency a distribution:

        • Median split: top v. bottom half.

        • Extreme scores: top v. bottom 10% of scores.

    • Simple self-identification:

      • e.g., “Republican” v. “Democrat”.

  • Behavioral index:

    • Used any drug in previous year v. not.

    • Voted in 2012 v. not.

  • Not a “True” IV: Participants not randomly assigned to groups.

    Week 3; Experimental designs


    Using a measured variable to create groups

    Using a measured variable to create groups

    # of symptoms rated 2 or 3

    • Administer depression scale, count the # symptoms rated 2 or 3.

    Form groups based on a cut point; e.g., > 4 symptoms = quasi-clinical depression.

    Participants are assigned to groups based on their ratings, not random assignment.

    Below is a list of different feelings. Circle the number that shows howmanydaysyou felt each of these over the PAST WEEK.

    Rarely or A Little A moderateMost or all of

    none of of the Timeamount of the time

    the time the time

    (less than 1 day)(1 or 2 days)(3 - 4 days)(5 - 7 days)

    I was bothered by things that usually do 0123

    not bother me.

    I felt I could not shake off the blues even 0123

    with help from my friends or family.

    I had trouble keeping my mind on what 0123

    I was doing.

    I felt depressed.0123

    I felt that everything I did was an effort.0123

    My sleep was restless.0123

    I was happy.0123

    I enjoyed life.0123

    I felt sad.0123

    Week 3; Experimental designs


    Question 4

    Question 4

    An independent variable…

    A = Is measured on a continuous scale

    B = Is manipulated by the researcher

    C = Is the outcome of the experiment

    D = Is the “phenomenon” you are trying to explain.

    E = Does not care about other people

    Week 3; Experimental designs


    Question 5

    Question 5

    An dependent variable…

    A = Is typically measured on a binary scale

    B = Is manipulated by the researcher

    C = Is the putative cause in the theory

    D = Is the “phenomenon” you are trying to explain.

    E = Is over-concerned about other people

    Week 3; Experimental designs


    The big picture introductory lectures3

    The big picture: Introductory lectures

    • How do social values affect science?

    • Where do research questions & hypotheses come from.

    • Variables in research

    • Basic experimental designs

    • True vs. Quasi- Experiments

    Phenomenon

    Theory

    Hypothesis

    Methods

    & data

    Results

    Discussion &

    Conclusions

    Week 3; Experimental designs


    Overview basic designs

    Overview: Basic Designs

    • “Pre-experimental” designs: no control group

    Experimental

    Observe1

    Treatment

    Observe2

    Post-Test Only Design

    Pre- Post- Test Design

    Group assignment

    Pre-test

    Experimental manipulation

    Outcome

    Week 3; Experimental designs


    Basic designs

    Basic Designs

    • “Pre-experimental” designs: no control group

    Experimental

    Observe1

    Observe1

    Treatment

    Observe2

    Post-Test Only Design

    Pre- Post- Test Design

    True (or Quasi-)experimental designs with a control group

    “After only” Control group design

    Pre- Post- Group Comparisons

    Group assignment

    Pre-test

    Experimental manipulation

    Outcome

    Control

    Control

    Observe2


    Basic designs1

    Basic Designs

    • “Pre-experimental” designs: no control group

    Post-Test Only Design

    Experimental

    Observe1

    Treatment 1

    Observe2

    Pre- Post- Test Design

    Control

    Experimental

    Observe1

    Treatment 2

    Observe2

    True (or Quasi-)experimental designs with a control group

    Control

    Observe1

    Observe2

    “After only” Control group design

    Pre- Post- Group Comparisons

    Multiple group comparison

    Group assignment

    Pre-test

    Experimental manipulation

    Outcome


    Pre experimental designs

    “Pre-experimental” designs

    Post-Test Only Design

    Group

    Treatment

    Measure

    Only 1 group - typically an existing group: no selection or assignment occurs.

    Experimental intervention (“Treatment”) may or may not be controlled by the researcher.

    Use for naturally occurring or system-wide events (e.g., group trauma, government policy change, etc.).

    Measurement may or may not be controlled by the researcher.

    Pre- Post- Test Design

    Group

    Measure1

    Treatment

    Measure1

    Only one group;

    • only group available?

    • naturally occurring intervention?

    Measurements given to all participants at baseline & follow-up

    All participants get the same treatment, which may or may not be controlled by the researcher.

    Week 3; Experimental designs


    Pre experimental designs 2

    “Pre-experimental” Designs (2)

    Advantage of “Post-” & “Pre- Post-” Designs:

    Allow us to study naturally occurring interventions.

    • e.g., test scores before and after some school change,

    • Crime rates after a policy change, etc.

  • Having both Pre- and Post measures allows us to examine change.

  • Week 3; Experimental designs


    Pre experimental designs 21

    “Pre-experimental” Designs (2)

    Disadvantage of “Post-” & “Pre- Post-” Designs:

    No control group = many threats to internal validity.

    Maturation: Participants may be older / wiser by the post-test

    History; Cultural or historical events may occur between pre- and post-test that change the participants

    Mortality: Participants may non-randomly drop out of the study

    Regression to baseline: Participants who are more extreme at baseline look less extreme over time as a statistical confound.

    Reactive Measurement:Scores may change simply due to being measured twice, not the experimental manipulation.

    Week 3; Experimental designs


    Experiments

    Experiments

    “After only” Control group design

    Control

    Experimental

    Treatment 2

    Observe2

    Adds a control group. Either…

    Observed Groups:

    • Naturally occurring (e.g., Class 1. v. Class 2) or

    • Self-selected (sought therapy v. did not…).

      Assigned Groups:

    • Randomlyassign participants to experimental v. control group, or

    • Matchparticipants to create equivalent groups.

    Measure Dependent Variable(s) only at follow-up.

    Use experimental or standard measures (e.g., grades, census data, crime reports).

    Control

    Observe2

    Week 3; Experimental designs


    Advantages of experimental design

    Advantages of experimental design

    “After only” Control group design

    Control

    Experimental

    Treatment 2

    Observe2

    Control

    Observe2

    Advantage: Lessens the likelihood of confounds or threats to internal validity.

    • Control group

    • Random assignment

      Disadvantage:Existing or self-selected groups may have confounds.

      No baseline or pre- measure available:

    • We cannot assess change over time.

    • We cannot assess whether the groups are equivalent at baseline.

    Week 3; Experimental designs


    Basic designs true experiments 2

    Basic Designs: True experiments (2)

    Pre- Post- Group Comparisons (most common study design)

    Group 1

    Measure 1

    Group 2

    Measure 1

    Two groups:

    Observed

    (quasi-experiment)

    or

    Assigned

    (true experiment).

    Baseline (“pre-test”) measure of study variables and possible confounds.

    Week 3; Experimental designs


    Basic designs true experiments 21

    Basic Designs: True experiments (2)

    Pre- Post- Group Comparisons (most common study design)

    Group 1

    Measure 1

    Treatment

    Measure 2

    Control

    Group 2

    Measure 1

    Measure2

    The group getting the experimental condition is contrasted with a control group..

    “Post-test” follow-up of dependent variable(s);

    • Simple outcome

    • Change from baseline.

    Advantages:Pre-measure assesses baseline level of Dependent Variable

    -- allows researcher to assess change

    -- can detect ceiling (or floor) effects

    -- can use to assign participants to groups via matching

    -- can assess baseline equivalence of groups

    Disadvantage:Highly susceptible to confounds if using observed or self-selected groups.

    Week 3; Experimental designs


    Basic designs true experiments 22

    Basic Designs: True experiments (2)

    Pre- Post- Group Comparisons (most common study design)

    Group 1

    Measure 1

    Treatment

    Measure 2

    Control

    Group 2

    Measure 1

    Measure2

    Advantages:Pre-measure assesses baseline level of Dependent Variable

    • Allows researcher to assess change

    • Can find matched pairs of participants and assign each to different groups (rather than random assignment).

    • Can assess whether groups are equivalent at baseline.

      Disadvantage:Highly susceptible to confounds if using observed or self-selected groups.

    Week 3; Experimental designs


    More complex experimental designs

    More Complex Experimental Designs

    Multiple group comparison

    Group 1

    Measure1

    Treatment #1

    Measure1

    Group 2

    Treatment #2

    Control

    Measure1

    Group 3

    • 3 (or more) groups

    • Typically formed by Random assignment.

    Multiple experimental groups, e.g.

    • Low drug dose,

    • High drug dose,

    • Placebo.

      or

    • Male therapist,

    • Female therapist,

    • Wait list control.

    Week 3; Experimental designs


    More complex experimental designs1

    More Complex Experimental Designs

    Multiple group comparison

    Group 1

    Measure1

    Treatment #1

    Measure2

    Measure1

    Group 2

    Treatment #2

    Measure2

    Control

    Measure1

    Group 3

    Measure2

    Compare:

    • Level 1 of independent variable from Level 2

    • Either / both experimental groups from control grp.

    Week 3; Experimental designs


    More complex experimental designs2

    More Complex Experimental Designs

    Multiple group comparison

    Group 1

    Measure1

    Treatment #1

    Measure2

    Measure1

    Group 2

    Treatment #2

    Measure2

    Control

    Measure1

    Group 3

    Measure2

    Advantages: Test dose or context effects:

    • Drug doses, amounts of psychotherapy, levels of anxiety, etc. Increasing dose effect can be tested against no dose.

    • Diverse conditions to test 2nd hypotheses or confounds, e.g., therapy delivered by same sex v. opposite sex therapist.

      Disadvantage:

    • More costly and complex.

    • Potential ethical problem with a “no dose” (or very high dose) condition.

    Week 3; Experimental designs


    Experimental design overview

    Experimental design overview

    We recruit a sample of participants from the larger population

    …then randomly assign them to groups.

    Procedures for all groups should be exactly the same…

    …except the experimental manipulation, (Independent variable).

    Hypothesis: The outcome (Dependent Variable) varies by group only.

    Week 3; Experimental designs


    Overview of true experimental designs

    Overview of true experimental designs

    Experimental group

    Control group

    Week 3; Experimental designs


    Overview experimental designs

    Overview: experimental designs

    Does the sample well represent the population?

    • Is recruitment biased?

    • Is the sample size large enough?

    External validity

    Random selection


    Overview experimental designs1

    Overview: experimental designs

    Does the sample well represent the population?

    Are the groups equal at baseline?

    • Self-selection (in or out)

    • Existing groups?

    External validity

    Random selection

    Internal validity

    Random Assignment


    Overview experimental designs2

    Overview: experimental designs

    • Do both groups have the same expectations?

    • Are participants (and researchers) really blind?

    • Do we treat both groups the same?

    Does the sample well represent the population?

    Are the groups equal at baseline?

    Procedures the same for all groups?

    External validity

    Random selection

    Internal validity

    Random Assignment

    Internal validity:

    Lack of confounds


    Overview experimental designs3

    Overview: experimental designs

    Procedures the same for all groups?

    Does the sample well represent the population?

    Are the groups equal at baseline?

    Independent variable faithfully reflects the construct?

    • Does the operational definition really express the construct we are interested in?

    • Have we given the correct dose of the IV?

    External validity

    Random selection

    Internal validity

    Random Assignment

    Internal validity:

    Lack of confounds

    External Validity

    Correct IV?


    Overview experimental designs4

    Overview: experimental designs

    Procedures the same for all groups?

    Does the sample well represent the population?

    Are the groups equal at baseline?

    Independent variable faithfully reflects the construct?

    Groups really different at outcome?

    • Is any difference we see actually statistically significant (reliable & meaningful)?

    External validity

    Random selection

    Internal validity

    Random Assignment

    Internal validity:

    Lack of confounds

    External Validity

    Correct IV?

    Internal Validity:

    Likelihood of chance results


    Overview experimental designs5

    Overview: experimental designs

    Does the sample well represent the population?

    Are the groups equal at baseline?

    Procedures the same for all groups?

    Independent variable faithfully reflects the construct?

    Groups really different at outcome?

    External validity

    Random selection

    Internal validity

    Random Assignment

    Internal validity:

    Lack of confounds

    External Validity

    Correct IV?

    Internal Validity:

    Likelihood of chance results


    Internal external validity

    Internal & external validity

    • How do social values affect science?

    • Where do research questions & hypotheses come from.

    • Variables in research

    • Basic experimental designs

    • True vs. Quasi- Experiments

    Experimental Design & sampling


    True experiments

    True experiments

    How do True experiments differ from Quasi-experiments?

    Group 1

    Observe1

    Treatment

    Observe2

    Observe2

    Group 2

    Observe1

    Control

    Group Assignment

    Baseline (pre-test)

    Experimental condition

    Follow-up (post-test)

    Week 3; Experimental designs


    True experiments1

    True experiments

    Key elements of true experiments

    • Manipulate the Independent Variable

    • Randomly assign participants to groups

    • Groups are Equivalent:

      • Participants

      • Researcher

      • Common procedures

    Group 1

    Observe1

    Treatment

    Observe2

    are blind

    Observe2

    Group 2

    Observe1

    Control

    Group Assignment

    Baseline (pre-test)

    Experimental condition

    Follow-up (post-test)

    Week 3; Experimental designs


    Quasi experiments

    Quasi-experiments

    Quasi-experiments

    • No control over the Independent Variable;

      • Naturally occurring event

      • Existing data

    • Non-equivalent groups:

      • Non-random assignment

      • Participants not blind

      • Naturally occurring groups

      • Self-selection into groups

    Group 1

    Observe1

    Treatment

    Observe2

    Observe2

    Group 2

    Observe1

    Control

    Group Assignment

    Baseline (pre-test)

    Experimental condition

    Follow-up (post-test)

    Week 3; Experimental designs


    Revised 9 11 13

    Experimental Designs, example 1

    • True Experiment

    • I randomly assign participants to groups

    • I manipulate the independent variable

      • Group 1: Drug dose

      • Group 2: Placeboor alternate drug

    • I keep all procedures = across groups

      • E.g., keeping researcher & participants blind.

    • I am (more) assured that the outcome is due only to the independent variable

    E X A MP LE

    Random Assignment to Groups

    Procedures = for groups

    Baseline Assessment

    Experimental condition

    Follow-up (post-test)

    Assess all participants’

    blood pres.

    Group 1

    New drug

    Assess Bp for 1 year for all Parts.

    Group 2

    Placebo

    Experimental Design & sampling


    Revised 9 11 13

    Experimental Designs, example 1

    • Quasi-experiment

    • Random assignment may not be possible.

      • Existing groups

      • Self-select in or out of experiment

    • Researcher & participants not blind?

      • Psychotherapy or other exp. conditions

      • Researcher cannot be blind?

    • May not controlall of the experiment.

      • Cannot treat gropsexactly equivalent?

    E X A MP LE

    Random assignment possible?

    Random Assignment to Groups

    Groups may need different procedures

    Baseline Assessment

    Experimental condition

    Follow-up (post-test)

    Assess fear & loathing of statistics

    Group 1

    Induce stress

    More may drop out of stress grp.

    Group 2

    Relax

    Experimental Design & sampling


    Overview key terms

    Overview: key terms

    • Theory

    • Hypothetical construct

    • Hypothesis

    • Variable

    • Operational definition

    • Internal & external validity

    • Independent v. Dependent variables

    • Measurement v. experimental studies

    Weeks 1 & 2; Introduction to science.


    Revised 9 11 13

    Research flow

    Week 3; Experimental designs


    Basics of major forms of research

    Basics of major forms of research.

    External validityInternal validity

    Weeks 1 & 2; Introduction to science.


    Key terms concepts

    Key terms & concepts

    • Role of values & social judgments in the research process

    • Basic elements of science

      • Hypothetical constructs

      • Operational definitions

      • Statement of testable hypothesis

        • Predictive, potentially refutable

        • Specify Variables in functional relationship

      • Replication

    The hierarchy of phenomena, theory, hypotheses, & methods:

    Week 3; Experimental designs


    Key terms concepts 2

    Key terms & concepts, 2

    • Measurement v. experimental methods

      • Types of variables used

      • Cause & effect assumptions

    • Creating variables

      • Direct treatment dose or manipulation

      • Indirect use of context (manipulation check)

      • Using a measured variable (self-reports or “status” variable”) to assign to groups

    Week 3; Experimental designs


    Overview 3

    Overview, 3

    • Experimental design key elements

      • Control group v. non-controlled designs

      • Threats to internal validity:

    • Maturation

    • History

    • Mortality

    • Regression to baseline

    • ReactiveMeasurement

    • “Pre-experimental” designs

    • Pre-post designs

    • Multiple group comparisons.

    Week 3; Experimental designs


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