Smith/Davis (c) 2005 Prentice Hall Chapter Twelve Designing and Conducting, Experiments with More...

Smith/Davis (c) 2005 Prentice Hall

Chapter Twelve

Designing and Conducting, Experiments with More than Two Groups

PowerPoint Presentation created by Dr. Susan R. BurnsMorningside College


Experimental Design: Adding to the Basic Building Block

The two-group design is the basic building block.

Researchers typically want to move beyond two-group designs so they can ask more complicated and interesting questions.


The Multiple-Group Design

How many IVs?– This chapter deals with experiments that use only

one IV.– Although one-IV experiments are simpler than

experiments that use multiple IV’s, they are not inferior in any way.

A well-designed experiment with one IV is vastly preferable to a sloppy experiment with many variables thrown together.



How Many Groups?– This question marks the difference between the multiple-

group design and the two-group design. A multiple-group design compares three or more levels or

amounts of an IV. A multiple-group design can have a control group and two or

more experimental groups.– We can compare three, four, five, or even more differing levels or

amounts of an IV. A multiple-group design does not have to have a control group.


Psychological Detective

Suppose you wished to test more than three noise conditions. Could you use a multiple-group design in such a case? Why or why not?



Assigning Participants to Groups– After we decide to conduct a multiple-group

experiment, we must decide about assignment or research participants to groups.

– We may choose between independent groups or correlated groups.



Independent samples– Groups of participants that are formed by random

assignment.Random assignment serves as an important

control procedure. – One of several steps experimenters take to ensure that

potential extraneous variables are controlled and avoid a confounded experiment.


Random Selection

Is Cathy using random assignment or random selection in this cartoon?

Because she is tasting chocolate Santas in a nonsystematic way (rather than assigning Santas to groups), Cathy’s gluttony illustrates random selection



Correlated samples (nonrandom assignment to groups)– Matched sets

Participants are matched on a variable that will affect their performance on the DV (matching variable).

Then sets of participants are created who are essentially the same on the matching variable.



Correlated samples– Repeated measures

Each participant must participate in all of the treatment conditions.

– Natural setsAnalogous to using natural pairs except that sets

must include more than two research participants.Many animal researchers use littermates as natural

sets.


Deciding on an Experimental Design

Researchers who want to design an experiment with one IV also need to choose between multiple-group designs and the two-group designs.


Comparing Multiple-Group and Two-Group Designs

All you have to do to change your two-group design into a multiple-group design is to add another level (or more) to your IV.

A two-group design can tell you whether your IV has an effect.


Comparing Multiple-Group and Two-Group Designs

A two-group design can tell you whether your IV has an effect.

– You should never conduct an experiment to determine whether a particular IV has an effect without first conducting a thorough literature search

– If you find no answer in a library search, then you should consider conducting a two-group (presence vs. absence) study.

A multiple-group design is appropriate when you find the answer to your basic question and wish to go further.


Comparing Multiple-Group Designs

Choosing a multiple-group design– Your first consideration should be your

experimental question.– Then decide on whether to use

independent or correlated groups.



Control issues– The multiple-independent groups design uses the

control technique of randomly assigning participants to groups.

If you have a substantial number of research participants (at least 10 per group), you can be fairly confident that random assignment will create equal groups.

– Multiple-correlated groups designs use the control techniques of matching, repeated measures, or natural pairs to assure equality of groups and to reduce error variability.



Remember the general equation that represents the formula for a statistical test

Reducing the error variability in the denominator of the equation will result in a larger computed statistical value, thereby making it easier to reject the Null hypothesis.

Using a correlated groups design reduces your degrees of freedom, which makes it more difficult to achieve statistical significance and reject the Null.

However, the reduced error variability typically more than offsets the loss of df. Thus, correlated designs often produce stronger tests for finding statistical significance.



Practical considerations– Correlated-Groups Designs

Matched sets– You must consider the difficulty of finding three (or more)

participants to match on the extraneous variable you choose. Natural sets

– May be limited by the size of the natural sets you intend to study. Repeated measures

– Each participant must be measured at least three times.

– Independent groups Designs You must take into account the large number of participants

you will need to make random assignment feasible and to fill the multiple groups.


Variations on the Multiple-Group Design

Comparing different amounts of an IV– If we already know that a particular IV has an

effect, then we can use a multiple-group design to help us define the limits of that effect.

– In this type of experiment, we often add an important control in order to account for a possible placebo effect.

Placebo effect– An experimental effect that is due to expectation

or suggestion rather than the IV.


Variations on the Multiple-Group Design

Dealing with measured IV’s– Ex post facto research deals with measured

rather than manipulated IV’s.

Smith/Davis (c) 2005 Prentice Hall Chapter Twelve Designing and Conducting, Experiments with More...

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