Discussion & Conclusions

1Dr. McKirnan; Foundations of

Research

Discussion &Conclusions

Methods & data

Phenomenon

Theory

Hypothesis

Results

Basic research designs.

Dr. David J. McKirnan, University of Illinois at Chicago, Psychology; [email protected]

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Research


Methods & data

Phenomenon

Theory

Hypothesis

Results


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Research


Methods & data

Phenomenon

Theory

Hypothesis

Results


This module addresses:Designs without a

control group

Variations on control group designs

The overall structure of an experiment


Research

Psychology 242, Dr. McKirnan

Week 3; Experimental designs

Basic experimental designs

This module overviews the core elements of an experimental research design.

We will discuss “pre-experimental” designs

These typically have no control group or may use existing groups

They are often used in preliminary or exploratory research

“True” experiments have several key characteristics:

A control group

Random assignment of participants to groups

Standardized or uniform procedures for each group


Research Experimental designs and validity

We will discuss internal and external validity.

Internal validity In experiments we manipulate (induce…) the Independent Variable.

We then measure the Dependent Variable.

Experimental hypothesis: the outcome (the level of the Dependent Variable) is caused by – and only by – the Independent Variable.

Internal validity: How confident are we that the outcome was due only to the Independent Variable.

Confound: A variable other than the IV that caused or influenced the result.

Did the participants in the experimental v. control groups differ on something other than the IV?

Were the procedures biased in some way…?Confound


ResearchExperimental designs and validity

We will discuss internal and external validity.

External validity Experimental participants are a sample of the larger population.

The experimental manipulation attempts to accurately induce the Independent Variable.

The outcome measure represents the Dependent Variable.

The experiment is conducted in a specific physical or cultural setting.

External validity:

Does the research sample accurately represent the larger population?

Do the exp. manipulation and outcome measures accurately represent the concepts underlying the Independent & Dependent Variables?

Is the experimental setting representative of how these processes work in nature?


Research External validity: summary

The study structure & context

The research

Setting:

The Dependent

Variable

The research Sample:

Is the sample representative of the larger population?

Is this typical of the natural

settings where the phenomenon

occurs?

Does the outcome measure represent

what we are trying to explain?

Does the experimental manipulation actually create the phenomenon you

are interested in?

The Independent

Variable


Research Overview: Basic Designs “Pre-experimental” designs: no control group

Post-Test Only Design Pre- Post- Test Design

Group assignment

Pre-test Experimental manipulation

Outcome

Experimental Observe2TreatmentObserve1


Research Basic Designs

“Pre-experimental” designs: no control groupPost-Test Only Design Pre- Post- Test Design

Group assignment


Outcome

Experimental Observe2TreatmentObserve1

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

“After only” Control group design

Pre- Post- Group Comparisons

Control Observe2ControlObserve1


Research Basic Designs

“Pre-experimental” designs: no control groupPost-Test Only Design Pre- Post- Test Design

Group assignment


Outcome

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


Pre- Post- Group Comparisons

Multiple group comparison

Experimental Observe1 Observe2

Experimental

Control

Observe1

Observe1

Treatment 2 Observe2

Observe2

Treatment 1

Control


Research

“Pre-experimental” designsPost-Test Only Design

Treatment MeasureGroup

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.

Measure1Treatment Measure1

Group

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.

Pre- Post- Test Design


Research “Pre-experimental” Designs (2)

Allow us to study naturally occurring interventions.

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

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.


Research “Pre-experimental” Designs (2)

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

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.

No control group = many threats to internal validity.


Research

Experiments“After only” Control group design

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:

Randomly assign participants to experimental v. control group, or

Match participants to create equivalent groups.

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

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

Experimental

Control


Observe2Control


Research Advantages of experimental design


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.

Experimental

Control


Observe2Control


Research Basic Designs: True experiments (2)

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

Two groups:

Observed (quasi-experiment)

orAssigned

(true experiment).

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

Group 1

Group 2

Measure 1

Measure 1




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

Group 1

Group 2

Measure 1

Measure 1

Treatment Measure 2

Measure2

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

Simple outcome Change from

baseline.

Control




Group 1

Group 2

Measure 1

Measure 1

Treatment Measure 2

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.

Control


Research

More Complex Experimental Designs


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.

Group 1

Group 2

Group 3

Measure1

Measure1

Measure1

Treatment #2

Treatment #1

Control


Research More Complex Experimental Designs


Measure2Group 1

Group 2

Group 3

Measure1

Measure1

Measure1

Treatment #2 Measure2

Measure2

Treatment #1

Compare: Level 1 of independent

variable from Level 2 Either / both experimental

groups from control grp.

Control


Research More Complex Experimental Designs


Measure2Group 1

Group 2

Group 3

Measure1

Measure1

Measure1

Treatment #2 Measure2

Measure2

Treatment #1

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.

Control


Research

Core components of a research study

Participant Selection

Participant Assignment

Experimental Procedures

Experimental Treatment or Manipulation

Results

We will use this framework to think about the basic elements of an experiment.

Who is in our research study?

How did we recruit or sample them?

We will have at least one Experimental Group and a Control Group.

How do we assign participants to be in one or the other?

What instructions do we give?

What experimental tasks will participants be performing?

What measures might we be taking?

Experimental & control groups get different conditions.

We hypothesize that this manipulation “causes” the outcome.

What outcomes are we measuring?

What is the experiment trying to explain?


Research Experimental design overview





Results

Sample

Group A Procedure Treatment Outcome

Group B Procedure Control Outcome

(Group C) (Procedure ) (Alternate Treatment?) (Outcome)

We recruit a sample of participants from the larger population.

We randomly assign them to groups to ensure the groups are equivalent at baseline.

Procedures for all groups should be exactly the same…

…except the experimental manipulation, i.e., the Independent variable.

Hypothesis: The outcome or Dependent Variable varies only by group.


Research

Overview of true experimental designs





Results

Sample

Group A Procedure Treatment Outcome

Group B Procedure Control Outcome

(Group C) (Procedure ) (Alternate Treatment?) (Outcome)

Experimental group

Control group


Research

Overview: experimental designs

Participant Recruitment




Results

Sample

Group A Procedure A Treatment Outcome

Group B Procedure A Control Outcome

Group C Procedure A Alternate Treatment (?) Outcome

Does the sample well represent

the population?

External validity

• Was recruitment biased?

• Is the sample size large enough?

What form of validity is threatened by sample

bias?

What can we do to avoid that threat?

Random selection


Research






Results

Sample




Does the sample well

represent the population?

External validity

Random selection

Are the groups equal at

baseline?

Internal validity

Random Assignment

• Did participants Self-select (in or out) of the study?

• Did we use existing groups?

Validity Threat?

Solution?


Research






Results

Sample






External validity

Random selection

Are the groups equal at baseline?

Internal validity

Random Assignment

Procedures the same for all groups?

Internal validity:

Lack of confounds

• Do both groups have the same expectations?

• Are participants (and researchers) really blind?

• Do we treat both groups the same?

Validity Threat?

Solution?


Research






Results

Sample






External validity

Random selection


Internal validity

Random Assignment


Internal validity:

Lack of confounds

Independent variable faithfully

reflects the construct?

External Validity

Correct IV?

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

• Have we given the correct dose of the IV?

Validity Threat?

Solution?


Research






Results

Sample






External validity

Random selection


Internal validity

Random Assignment


Internal validity:

Lack of confounds



External Validity

Correct IV?

Internal Validity:

Statistical testing

Groups really

different at outcome?

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

• …or it is due to chance alone..

Validity Threat?

Solution?


Research






Results

Sample






External validity

Random selection


Internal validity

Random Assignment


Internal validity:

Lack of confounds



External Validity

Correct IV?

Internal Validity:

Statistical testing

Groups really different at outcome?


Research

Experimental design key elements Control group v. non-controlled designs Threats to internal validity:

Maturation History Mortality Regression to baseline Reactive Measurement

“Pre-experimental” designs Pre-post designs Multiple group comparisons

Overview: key terms


Research






Results



External validity


Internal validity




Groups really different at outcome?

External validity

Internal validity

Internal validity

Discussion & Conclusions

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Transcript of Discussion & Conclusions