Fill in the blanks questions regarding experiments

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Experiment Settings

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LEARNING OUTCOMES

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Basic characteristics of experiments

Experimental effects

Issues in experimental design

Manipulation of IV

Measurement of DV

Selection of test units

Different types of experiment designs

Manipulation check

Internal validity of experiments

Test-marketing

Design a basic and factorial experiment

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Research Questions

  • Does jogging make you feel better?
  • Does point-of-purchase advertising influence sales?
  • Is the anti-drug campaign successful in decreasing the drug usage?
  • What is the effect of color and lighting on shopper patronage?

Experiments

Experiments are usually conducted to investigate questions like these, with the goal to establish causal claims.

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EXHIBIT 9.1 Experimental Conditions
in Color and Lighting Experiment

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The Characteristics of Experiments

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Subjects (a.k.a. Participants)

  • Human respondents who provide measures based on experimental manipulation.

  • Experimental Condition
  • One of the possible levels of an experimental (independent) variable manipulation.

  • Independent Variable (IV) & Dependent Variable (DV)

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EXHIBIT 9.2 Consumer Average Patronage Scores in Each Condition

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Main Effect of Color on Consumer Patronage:

Blue color attracted consumers more than did orange color.

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EXHIBIT 9.3 Experimental Graph Showing
Interaction Effect

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EXHIBIT 9.3 Experimental Graph Showing
Interaction Effect

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The effect of color on consumer patronage is stronger when

the lighting is bright than when the lighting is soft.

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Experimental Effects

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  • Main effect: The experimental difference in dependent variable means between the different levels of any single experimental variable.
  • The effect of a single IV on a DV, regardless of the other IV.

  • Interaction effect: Differences in dependent variable means due to a specific combination of independent variable.
  • The effect of one IV on DV depends on the level of the other IV.

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LEARNING OUTCOMES

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Basic characteristics of experiments

Experimental effects

Issues in experimental design

Manipulation of IV

Measurement of DV

Selection of test units

Different types of experiment designs

Manipulation check

Internal validity of experiments

Test-marketing

Design a basic and factorial experiment

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All of the following are experimental design issues EXCEPT:

a. selection and assignment of subjects to treatments

b. control over extraneous variables

c. manipulation of the independent variable

d. manipulation of the dependent variable

d. manipulation of dependent variable

If I ask you to design an experiment, what would you do? What issues should you consider?

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Basic Issues in Experimental Design

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  • Manipulation of the Independent Variable
  • Experimental treatment: the way an experimental variable is manipulated.
  • Categorical variables: class or quality (e.g., color)
  • Continuous variables: quantity (level) (e.g., price)

Experimental Treatment

Experimental Group

Control Group

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Categorical variables: color, present or absent of humor appeals in advertising, type of movies

Continuous variables: price, age, customer satisfaction score, $ spent.

Experimental Design (cont’d)

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  • Manipulation of the Independent Variable
  • Several experimental treatment levels (different values of the independent) may be used.
  • More than one independent variable may be examined.
  • Cell: a specific treatment combination associated with an experimental group.
  • How to compute # of cells in an experiment:
    K = (T1)(T2)..(Tm)

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Manipulation may sound negative, but it simply means that experimenters vary the levels of IV systematically. For example, if a marketing researcher is interested in the effect of price on consumers’ buying behavior, s/he can vary the levels of price. For example, s/he can decide using $1.99 as low price and $2.99 as high price for a tube of lip balm, or $2.29 as low and $3.99 as high. Again, s/he can manipulate the levels of IV to go along with the study purpose.

Experimental Design (cont’d)

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  • Selection and Measurement of the Dependent Variable
  • Selecting dependent variables that are relevant and truly represent an outcome of interest is crucial.
  • Will outcomes of the dependent variable (information or insights gained) assist managers in decision making?

Sales

Ad Attitude

Recall

Purchase Intention

Brand Attitude

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Very often, marketing managers choose sales as DV. In addition, they (should) also consider other variables that lead to or explain sales. For example, choosing brand attitude as DV. The reasoning is that if consumers say they have positive/favorable attitudes toward a product, then they are more likely to buy it, which will increase sales. In Ch. 10, we are going to discuss how we measure ATTITUDES, among other constructs.

Experimental Design (cont’d)

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  • Selection and Assignment of Test Units
  • Test units: the subjects or entities whose responses to treatment are measured or observed.

Randomization

  • Random assignment of subject and treatments to groups
  • Device for equally distributing the effects of extraneous variables to all conditions.

Repeated measures

  • Experiments in which individual subject is exposed to more than one level of an experimental treatment.

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Suppose a company has a new nicotine patch product and they want to test if it works. They want to run an experiment to find out. They create one experimental condition, where subjects will use actual product and a control condition, where subjects will use a placebo (what is it? See Slide 19) product. Now, let’s say they have recruited 100 smokers to participate in the study. How should they assign subjects to the 2 study conditions. Can they assign the first 50 smokers to the experimental condition and the rest of 50 to the control condition? Why or why not? See next slide.

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Methods of Random Selection

  • Tossing a perfect coin
  • Using computer programs that provide random selection
  • Use random number table

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The answer is NO. Because they may introduce other variables that will confound the effect of nicotine patch on quit smoking, such as willingness to quit. The smokers who sign up for the study earlier may have stronger willingness to quit. The correct procedure is random assignment. This slide discusses different methods we can randomly assign subjects to conditions. For example, we can flip a coin (decision rule: head for experimental condition; tail for control condition) when a subject signs in. If the coin is head, assign that person to experiment condition, etc. We can also use random number tables to do the random assignment. But first, be sure you make a decision rule (e.g., even # for experimental; odd # for control).

Demand Characteristics and Experimental Validity

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  • Demand Characteristic
  • An experimental design element or procedure that unintentionally provides subjects with hints about the research hypothesis.
  • Demand Effect
  • Occurs when demand characteristics actually affect the dependent variable.

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Reducing Demand Characteristics

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  • Experimental disguise
  • Placebo – an experimental deception involving a false treatment.
  • Placebo effect – the corresponding effect in a dependent variable that is due to the psychological impact that goes along with knowledge that a treatment has been administered.
  • Isolate experimental subjects
  • Use a “blind” experimental administrator
  • Administer only one experimental condition per subject

Establishing Control

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  • Constancy of Conditions
  • Subjects in all experimental groups are exposed to identical conditions except for the differing experimental treatments.

  • Counterbalancing
  • Attempts to eliminate the confounding effects of order of presentation by varying the order of presentation (exposure) of treatments to subject groups.

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LEARNING OUTCOMES

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Basic characteristics of experiments

Experimental effects

Issues in experimental design

Manipulation of IV

Measurement of DV

Selection of test units

Different types of experiment designs

Manipulation check

Internal validity of experiments

Test-marketing

Design a basic and factorial experiment

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Basic versus Factorial Experimental Designs

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  • Basic Experimental Designs
  • A single independent variable and a single dependent variable.

  • Factorial Experimental Designs
  • Allows for an investigation of the interaction of two or more independent variables.

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On IPA3, you will see examples for these two different designs. You will be asked to explain IV, DV and experimental effects, etc.

Laboratory and Field Experiments

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  • Laboratory Experiment
  • A situation in which the researcher has more complete control over the research setting and extraneous variables.

  • Field Experiments
  • Research projects involving experimental manipulations that are implemented in a natural environment.

EXHIBIT 9.5 The Artificiality of Laboratory versus Field Experiments

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  • High control
  • Strong causal relationship
  • Low control
  • Weak causal relationship

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Within- and Between-Subjects Designs

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Advantages of Between-Subjects Designs

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  • Within-Subjects Design
  • Involves repeated measures because with each treatment the same subject is measured.
  • Between-Subjects Design
  • Each subject receives only one treatment combination.
  • Usually advantageous although they are usually more costly.
  • Validity is usually higher.

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Exercise: Questions

Suppose you wanted to test the effect of three different email requests inviting people to participate in a survey posted on the Internet. One simply contained a hyperlink with no explanation, the other said if someone participated $10 would be donated to charity, and the other said if someone participated he or she would have a chance to win $100.

1. To design an experimental study, how many experimental conditions will there be?

2. If 15 participants are needed for each experimental condition, how many participants in total are needed for a between-subjects design? Within-subjects design?

3. How many times does each participant need to be measured for the dependent variable in a between-subjects design? Within-subjects design?

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Answer questions by yourself first, and then look at the key on the next slide

Answers

3 experimental conditions.

45 people needed for between-subjects design; 15 needed for within-subjects design.

3 times in within-subjects design; 1 time in between-subjects design.

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Internal Validity

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  • Internal Validity
  • The extent that an experimental variable is truly responsible for any variance in the dependent variable.
  • Does the experimental manipulation truly cause changes in the specific outcome of interest?
  • 6 threats (factors) to internal validity (SKIP pp. 230-232)

  • Manipulation Checks
  • A validity test of an experimental manipulation to make sure that the manipulation does produce differences in the independent variable.

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Uses of Test-Marketing

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Identifying Product Weaknesses

Forecasting New Product Success

Testing the Marketing Mix

Test- Marketing

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EXHIBIT 3.2 Testing for Causes with an Experiment

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Advantages and Disadvantages of Test-Marketing

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  • Advantages
  • Real-world setting
  • Easily communicated results

  • Disadvantages
  • Cost
  • Time
  • Loss of secrecy

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Read the example “Hidden Valley Ranch” on p. 237.