Chapter Twelve: Designing, Conducting, Analyzing, and...

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The Psychologist as Detective, 4e by Smith/Davis © 2007 Pearson Education Chapter Twelve: Chapter Twelve: Designing, Conducting, Designing, Conducting, Analyzing, and Interpreting Analyzing, and Interpreting Experiments with Multiple Experiments with Multiple Independent Variables Independent Variables

Transcript of Chapter Twelve: Designing, Conducting, Analyzing, and...

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Chapter Twelve:Chapter Twelve:Designing, Conducting,Designing, Conducting,

Analyzing, and InterpretingAnalyzing, and InterpretingExperiments with Multiple Experiments with Multiple

Independent VariablesIndependent Variables

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Hypothetical ExperimentHypothetical Experiment

• Suppose you were interested in determining whether Men or Women were more likely to convict a courtroom defendant. You design an ex post facto study with randomly selected groups of men and women. You present them with a defendant who tells a story, and ask them to rate the likelihood that the defendant was guilty.

• What other factor might influence these results?

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Experimental Design: Doubling Experimental Design: Doubling the Basic Building Blockthe Basic Building Block• A factorial design gives us the power we need to devise an

investigation of several factors (IVs) in a single experiment.

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Experimental Design: Doubling Experimental Design: Doubling the Basic Building Blockthe Basic Building Block• Factors

• Synonymous with IVs

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Experimental Design: Doubling Experimental Design: Doubling the Basic Building Blockthe Basic Building Block• Factors

• Synonymous with IVs• Independent Variables (IVs)

• Stimuli or aspects of the environment that are directly manipulated by the experimenter to determine their influences on behavior.

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Experimental Design: Doubling Experimental Design: Doubling the Basic Building Blockthe Basic Building Block• Factorial designs look at combinations of IVs at the same time

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How Many IVs?How Many IVs?• The factorial design gets its name because we refer to each IV as

a factor.• Multiple IVs yield a factorial design.

• Theoretically, there is no limit to the number of IVs that can be used in an experiment.• Practically speaking, however, it is unlikely that you would want

to design an experiment with more than two or three IVs.

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How many Groups or Levels?How many Groups or Levels?• The simplest possible factorial design is known as a 2 X 2

design.

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How many Groups or Levels?How many Groups or Levels?• The number of numbers tells us how many IVs there are.• The value of each number tells us how many levels each IV has.

• 2 x 2 (say 2 by 2) means we have two independent variables with two levels each.

• What would you call an experiment that had three levels of a drug (0, low, and high) given to ADD-diagnose and non-diagnosed children?

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How many Groups or Levels?How many Groups or Levels?• Various factors are often designated by letters, so the first factor

is labeled Factor A, the second as Factor B, and so on.

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How many Groups or Levels?How many Groups or Levels?• Various factors are often designated by letters, so the first factor

is labeled Factor A, the second as Factor B, and so on.• The levels within a factor are often designated by the letter that

corresponds to the factor and a number to differentiate the different levels.

• Thus, the two levels within the first factor would be labeled A1(A sub 1) and A2 (A sub 2).

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Assigning Participants to Assigning Participants to GroupsGroups• We have two options for this assignment – independent groups

or correlated groups.

• Independent – participants are randomly assigned

• Correlated• Matched sets• Natural sets• Repeated measures

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Assigning Participants to Assigning Participants to GroupsGroups• Independent – Each participant is tested in only ONE condition

of the study – In a two x two design, you would need separate participants for all four groups.

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Nonrandom Assignment to Nonrandom Assignment to GroupsGroups• Natural Pairs or Sets

• Using natural groups in a totally within-subjects design has the same difficulties as the matched pairs or sets variation of thisdesign, but it would be even harder.

• The difficulty lies in being able to find an adequate number of naturally linked participants.

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Nonrandom Assignment to Nonrandom Assignment to GroupsGroups• Repeated Measures

• In a completely within-groups experiment using repeated measures, participants would take part fully and completely.

• Participants take part in every possible treatment combination.

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Assigning Participants to Assigning Participants to GroupsGroups• Mixed designs

• Combine independent and repeated measures:

• Hypothetical experiment: • A researcher wants to know whether short or long words are

remembered more easily and he wants to know whether the delay between testing and recall effects the words differently. He gives participants a list containing BOTH short and long words. He then randomly assigns participants to have either a short or a long delay.

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What does a factorial design tell us?What does a factorial design tell us?

• Main Effect• A main effect refers to the sole effect of one IV in a factorial design.

• Interaction• Does the level of one variable influence the effect of the other

variable?

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Hypothetical ProblemHypothetical ProblemExample #1: A researcher wishes to examine whether time of day (morning versus afternoon) affects the memory of older and younger participants. He obtains a sample of 40 older individuals and 40 younger individuals and gives them a passage to read. They are later given a test over the passage (scores on the test could range from 0 to 30). Half of the individuals are randomly assigned to read the passage and take the test in the morning, and the other half do so in the afternoon. The data are reported in the table below (the numbers represent mean test scores for each group).

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Data from problem 1Data from problem 1Morning Testing Afternoon Testing

Older Adults M = 15 M = 8

Younger Adults M = 16 M = 20

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Hypothetical ProblemHypothetical ProblemExample #2: A researcher takes a sample of 40 introverts and 40 extroverts and asks them to solve problems in either a crowded room or an uncrowded room. The researcher measures the number of problems solved (numbers can range from 0 problems solved to 25 problems solved).

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Data from problem 2Data from problem 2

Crowded Room Uncrowded Room

Introverts M = 12 M = 12

Extroverts M = 18 M = 18

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Hypothetical ProblemHypothetical ProblemExample #3: A researcher wishes to examine whether people high or low in self-esteem react differently to different kinds of therapy for depression. She takes a sample of 120 people (half have high self-esteem and half have low self-esteem) and randomly assigns them to one of three conditions (humanistic therapy, cognitive-behavioral therapy, and a control group of no therapy). She records their level of depression after 3 months of therapy. Scores can range from 1 (very little depression) to 30 (extreme depression).

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Data from problem 3:In the boxes below, write in a Data from problem 3:In the boxes below, write in a pattern of means that would reveal a main pattern of means that would reveal a main effect of type of therapy.effect of type of therapy.

Humanistic Cognitive-Behavioral

Control Group

High Self-Esteem

M = M = M =

Low Self-Esteem

M = M = M =

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Data from problem 3:In the boxes below, write in a Data from problem 3:In the boxes below, write in a pattern of means that would reveal a main pattern of means that would reveal a main effect of self esteem.effect of self esteem.

Humanistic Cognitive-Behavioral

Control Group

High Self-Esteem

M = M = M =

Low Self-Esteem

M = M = M =

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Expanding the factorial designExpanding the factorial design

• When you add a level to an IV in a factorial design, you add several groups to your experiment because each new level must be added under each level of your other independent variable(s). • For example, expanding a 2 X 2 to a 3 X 2 design requires six

groups rather than four.• Adding levels in a factorial design increases groups in a

multiplicative fashion.

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Using Measured IVsUsing Measured IVs• Using a measured rather than a manipulated IV results in ex

post facto research.• A research approach in which the experimenter cannot directly

manipulate the IV but can only classify, categorize, or measure the IV because it is predetermined in the participants (e.g., IV = sex).

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Dealing with More than Two IVsDealing with More than Two IVs• Designing an experiment with more than two IVs is probably

the most important variation of the factorial design.

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Dealing with More than Two IVsDealing with More than Two IVs• The simplest possible factorial design with three IVs (often

referred to as a three-way design) has three IVs, each with two levels.• This design represents a 2 X 2 X 2 experiment.• This design would require eight different groups if it is planned as

a completely between-groups design.