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Chapter 3
Causal Research Design:Experimentation
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7-2
Chapter Outline
1) Overview
2) Concept of Causality
3) Conditions for Causality
4) Definition of Concepts5) Definition of Symbols
6) Validity in Experimentation
7) Extraneous Variables8) Controlling Extraneous Variables
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7-3
Chapter Outline
9) A Classification of Experimental Designs
10) Pre-experimental Designs
11) True Experimental Designs
12) Quasi Experimental Designs13) Statistical Designs
14) Laboratory vs. Field Experiments
15) Experimental vs. Non-experimental Designs16) Limitations of Experimentation
17) Application: Test Marketing
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7-4
Chapter Outline
18) Determining a Test Marketing Strategy
19) International Marketing Research
20) Ethics in Marketing Research
21) Internet and Computer Applications22) Focus on Burke
23) Summary
24) Key Terms and Concepts
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7-5
Concept of Causality
A statement such as "Xcauses
Y" will have thefollowing meaning to an ordinary person and to a
scientist.
____________________________________________________
Ordinary Meaning Scientific Meaning____________________________________________________
Xis the only cause of Y. Xis only one of a number of
possible causes of Y.
Xmust always lead to
Y The occurrence of
Xmakes the(Xis a deterministic occurrence of Ymore probable
cause of Y). (Xis a probabilistic cause of Y).
It is possible to prove We can never prove that Xis a
that Xis a cause of Y. cause of Y. At best, we can
infer that Xis a cause of Y.
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7-6
Conditions for Causality
Concomitant variationis the extent towhich a cause, X, and an effect, Y, occurtogether or vary together in the waypredicted by the hypothesis underconsideration.
The time order of occurrenceconditionstates that the causing event must occureither before or simultaneously with theeffect; it cannot occur afterwards.
The absence of other possible causalfactorsmeans that the factor or variablebeing investigated should be the only possiblecausal explanation.
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7-7
Evidence of Concomitant Variation betweenPurchase of Fashion Clothing and Education
High
High Low
363 (73%) 137 (27%)
322 (64%) 178 (36%)
Purchase of Fashion Clothing, Y
Table 7.1
500 (100%)
500 (100%)LowEducation,
X
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7-8Purchase of Fashion Clothing ByIncome and Education
Low Income
Purchase
High Low
High
LowEducation 200 (100%)
300 (100%)
300
200
122 (61%)
171 (57%)
78 (39%)
129 (43%)
High Income
Purchase
High
High
Low
Low
241 (80%)
151 (76%)
59 (20%)
49 (24%)Education
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7-9
Definitions and Concepts
Independent variablesare variables oralternatives that are manipulated and whose effectsare measured and compared, e.g., price levels.
Test unitsare individuals, organizations, or otherentities whose response to the independent variables
or treatments is being examined, e.g., consumers orstores.
Dependent variablesare the variables whichmeasure the effect of the independent variables onthe test units, e.g., sales, profits, and market shares.
Extraneous variablesare all variables other thanthe independent variables that affect the response ofthe test units, e.g., store size, store location, andcompetitive effort.
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7-10
Experimental Design
An experimental designis a set ofprocedures specifying
the test units and how these units are to
be divided into homogeneous subsamples, what independent variables or treatments
are to be manipulated,
what dependent variables are to bemeasured, and
how the extraneous variables are to becontrolled.
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7-11
Validity in Experimentation
Internal validityrefers to whether themanipulation of the independent variables ortreatments actually caused the observedeffects on the dependent variables. Controlof extraneous variables is a necessarycondition for establishing internal validity.
External validityrefers to whether thecause-and-effect relationships found in theexperiment can be generalized. To whatpopulations, settings, times, independentvariables and dependent variables can theresults be projected?
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Extraneous Variables
Historyrefers to specific events that are external tothe experiment but occur at the same time as theexperiment.
Maturation(MA) refers to changes in the test unitsthemselves that occur with the passage of time.
Testing effectsare caused by the process ofexperimentation. Typically, these are the effects onthe experiment of taking a measure on thedependent variable before and after the presentation
of the treatment. The main testing effect(MT) occurs when a prior
observation affects a latter observation.
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7-13
Extraneous Variables
In the interactive testing effect(IT), a priormeasurement affects the test unit's response to theindependent variable.
Instrumentation(I) refers to changes in themeasuring instrument, in the observers or in the
scores themselves. Statistical regressioneffects (SR) occur when test
units with extreme scores move closer to the averagescore during the course of the experiment.
Selection bias(SB) refers to the improper
assignment of test units to treatment conditions. Mortality(MO) refers to the loss of test units while
the experiment is in progress.
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Controlling Extraneous Variables
Randomizationrefers to the random assignment oftest units to experimental groups by using randomnumbers. Treatment conditions are also randomlyassigned to experimental groups.
Matchinginvolves comparing test units on a set of
key background variables before assigning them tothe treatment conditions.
Statistical controlinvolves measuring theextraneous variables and adjusting for their effects
through statistical analysis. Design controlinvolves the use of experiments
designed to control specific extraneous variables.
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7-15
A Classification of Experimental Designs
Pre-experimental designsdo not employrandomization procedures to control forextraneous factors: the one-shot case study,the one-group pretest-posttest design, andthe static-group.
In true experimental designs, theresearcher can randomly assign test units toexperimental groups and treatments toexperimental groups: the pretest-posttestcontrol group design, the posttest-onlycontrol group design, and the Solomon four-group design.
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A Classification of Experimental Designs
Quasi-experimental designsresult whenthe researcher is unable to achieve fullmanipulation of scheduling or allocation oftreatments to test units but can still applypart of the apparatus of true
experimentation: time series and multipletime series designs.
A statistical designis a series of basicexperiments that allows for statistical controland analysis of external variables:randomized block design, Latin squaredesign, and factorial designs.
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A Classification of Experimental Designs
Pre-experimental
One-Shot CaseStudy
One GroupPretest-Posttest
Static Group
TrueExperimental
Pretest-PosttestControl Group
Posttest: OnlyControl Group
Solomon Four-Group
QuasiExperimental
Time Series
Multiple TimeSeries
Statistical
RandomizedBlocks
Latin Square
FactorialDesign
Figure 7.1
Experimental Designs
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One-Shot Case Study
X 01
A single group of test units is exposed to atreatment X.
A single measurement on the dependentvariable is taken (01).
There is no random assignment of test units.
The one-shot case study is more appropriatefor exploratory than for conclusive research.
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One-Group Pretest-Posttest Design
01
X 02
A group of test units is measured twice.
There is no control group. The treatment effect is computed as
0201.
The validity of this conclusion isquestionable since extraneous variablesare largely uncontrolled.
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7-20
Static Group Design
EG: X 01
CG: 02
A two-group experimental design.
The experimental group (EG) is exposed tothe treatment, and the control group (CG) isnot.
Measurements on both groups are made only
after the treatment. Test units are not assigned at random.
The treatment effect would be measured as01- 02.
7-21T E i t l D i
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7 21True Experimental Designs:Pretest-Posttest Control Group Design
EG: R 01 X 02
CG: R 03 04
Test units are randomly assigned to either the experimental orthe control group.
A pretreatment measure is taken on each group.
The treatment effect (TE) is measured as:(02- 01) - (04- 03). Selection bias is eliminated by randomization.
The other extraneous effects are controlled as follows:
0201= TE+ H+ MA+ MT+ IT+ I+ SR+ MO
0403= H+ MA+ MT+ I+ SR+ MO
= EV(Extraneous Variables)
The experimental result is obtained by:
(02- 01) - (04- 03) = TE+ IT
Interactive testing effect is not controlled.
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7 22
Posttest-Only Control Group Design
EG :R
X
01
CG : R 02
The treatment effect is obtained byTE= 01- 02
Except for pre-measurement, the
implementation of this design is verysimilar to that of the pretest-posttestcontrol group design.
7-23Q i E i t l D i
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7 23Quasi-Experimental Designs:Time Series Design
01
02
03
04
05
X
0
60
70
80
90
10
There is no randomization of test units
to treatments. The timing of treatment presentation,
as well as which test units are exposed
to the treatment, may not be within theresearcher's control.
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7 24
Multiple Time Series Design
EG : 01 02 03 04 05 X 06 07 08 09 010CG : 01 02 03 04 05 06 07 08 09 010
If the control group is carefully
selected, this design can be animprovement over the simple timeseries experiment.
Can test the treatment effect twice:
against the pretreatment measurementsin the experimental group and againstthe control group.
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7 25
Statistical Designs
Statistical designsconsist of a series of basic
experiments that allow for statistical control and analysisof external variables and offer the following advantages:
The effects of more than one independent variable canbe measured.
Specific extraneous variables can be statisticallycontrolled.
Economical designs can be formulated when each testunit is measured more than once.
The most common statistical designs are the randomizedblock design, the Latin square design, and the factorialdesign.
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Randomized Block Design
Is useful when there is only one majorexternal variable, such as store size,that might influence the dependentvariable.
The test units are blocked, or grouped,on the basis of the external variable.
By blocking, the researcher ensures
that the various experimental andcontrol groups are matched closely onthe external variable.
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Randomized Block Design
Treatment GroupsBlock Store Commercial Commercial CommercialNumber Patronage A B C
1 Heavy A B C2 Medium A B C3 Low A B C4 None A B C
Table 7.4
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Latin Square Design
Allows the researcher to statistically control two noninteracting
external variables as well as to manipulate the independentvariable.
Each external or blocking variable is divided into an equalnumber of blocks, or levels.
The independent variable is also divided into the same number
of levels.
A Latin square is conceptualized as a table (see Table 7.5), withthe rows and columns representing the blocks in the twoexternal variables.
The levels of the independent variable are assigned to the cellsin the table.
The assignment rule is that each level of the independentvariable should appear only once in each row and each column,as shown in Table 7.5.
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Latin Square Design
Table 7.5
Interest in the StoreStore Patronage High Medium Low
Heavy B A CMedium C B ALow and none A C B
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Factorial Design
Is used to measure the effects of two ormore independent variables at variouslevels.
A factorial design may also beconceptualized as a table.
In a two-factor design, each level ofone variable represents a row and eachlevel of another variable represents acolumn.
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Factorial Design
Table 7.6
Amount of HumorAmount of Store No Medium HighInformation Humor Humor Humor
Low A B C
Medium D E FHigh G H I
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Laboratory versus Field Experiments
Factor Laboratory Field
Environment Artificial RealisticControl High LowReactive Error High Low
Demand Artifacts High LowInternal Validity High LowExternal Validity Low HighTime Short LongNumber of Units Small Large
Ease of Implementation High LowCost Low High
Table 7.7
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Limitations of Experimentation
Experiments can be time consuming,particularly if the researcher is interested inmeasuring the long-term effects.
Experiments are often expensive. Therequirements of experimental group, controlgroup, and multiple measurementssignificantly add to the cost of research.
Experiments can be difficult to administer. Itmay be impossible to control for the effectsof the extraneous variables, particularly in afield environment.
Competitors may deliberately contaminatethe results of a field experiment.
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Competition
Overall Marketing Strategy
Socio-CulturalEnvir
onment
NeedforS
ecrecy
New Product DevelopmentResearch on Existing ProductsResearch on other Elements
Simulated Test Marketing
Controlled Test Marketing
Standard Test Marketing
National Introduction
Stop
and
Reevaluate
-ve
-ve
-ve
-ve
Very +ve
Other Factors
Very +veOther Factors
Very +ve
Other Factors
Selecting a Test-Marketing Strategy
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Criteria for the Selection of Test Markets
Test Markets should have the following qualities:1) Be large enough to produce meaningful projections. They
should contain at least 2% of the potential actual population.
2) Be representative demographically.
3) Be representative with respect to product consumption behavior.
4) Be representative with respect to media usage.
5) Be representative with respect to competition.
6) Be relatively isolated in terms of media and physical distribution.
7) Have normal historical development in the product class
8) Have marketing research and auditing services available
9) Not be over-tested
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