experiment research for class

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Causal Research

Unit 2 chapter 3


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An Overview

To Obtain Cause-and-Effect Relationships

To understand which variable is the cause(Independent) and which is the effect( Dependent)

The nature of the relationship between the Cause

and the Effect.


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Conditions for Causality

Before making causal inferences, three conditionsare to be satisfied

Concomitant Variations (association)

Time Order of Causality

Elimination of other possible causal Factors


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Why Experiments?

Experiments provide the most convincingevidence of all the three conditions.

Variable(s) are controlled/ manipulated

Effect is measured on DependentVariable(s)


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Definitions

1. Treatment: Different levels of thevariable hypothesized to affect outcomes

of interest Examples: Price levels, different ads,

different packages


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Definitions

2. Dependent Variable: outcome variable (s)thought to be caused by the treatment

Examples: sales, intentions to purchase,awareness


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Definations

3) Independent Variables: variables to bemanipulated/treated which would cause

the outcome Example: In Store Service, Price, Ads


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Experimental Design

3) Test Units (consumers, households)

4) Extraneous Variables: Variables otherthan the Hypothesized, that might impactoutcome of experiment

For e.g. Store Size, Competitors Price,Competitors Ads.


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Experimental Design

Set of Procedures Specifying:

Test units

Independent variables

Dependent variables

How to control extraneous variables


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Symbols

X represents exposure of a test group to anexperimental treatment/independent variable

O represents the process of observation ormeasurement of the dependent variable

R indicates that test units (subjects) have beenrandomly assigned to treatments


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Movement from Left to Right indicates movementthrough time

Horizontal Alignment of symbols implies that all thosesymbols refers to specific treatment

For e.g. the symbolic arrangement

X O1 O2

This means: A given Group of Test Units was exposed to atreatment Variable (X) and the response was measured at twodifferent points in Time; O1 and O2


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Vertical Alignment of symbols implies that thoseSymbols refer to activities or events that occursimultaneously

For e.g. the symbolic arrangement

R X1 O1R X2 O2

This means that two groups of Test Units wererandomly assigned for two different Treatments at thesame time;the dependent variable was measured in the twodifferent groups


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Validity

Internal Validity

External Validity


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Internal Validity

Caused effect?

Or, Did Extraneous Variables Come into Picture???

IndependentVariables

Manipulation

DependentVariables


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External Validity

Can we generalize our results to the wholepopulation of interest?

Threats to external Validity arise when thespecific set of experimental conditions doesntreflect the Hypothesized condition

Example: Test market for a particular productfor a particular region may not hold true forother regions.


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Threats to Internal Validity-

Extraneous Variables

History: Events external to the experimentthat affect responses of the people

involved in the experiment (weather,news reports, time of day)

For eg: Promotional Campaign, Sales------Recession


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Threats to Internal Validity

Maturation: Changes in respondents overthe time period of the experiment

(maturing, getting hungry, getting tired,getting bored)

For e.g. test units are department stores. These stores change over time in terms of physical

layout, Dcor, Traffic etc.


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Instrumentation Effects: The measuringinstrument may change,

different interviewers may be used, or an interviewer gets tired

A common case: order of presentation

produces an effect Example: In an advertising experiment, initially one questionnairewas used to measure the awareness, then another questionnairewas used to measure the same.


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Mortality: Some subjects drop out of theexperiment between measurements.

The Loss of Test Units while theexperiment is in progress

Example: testing a weight-loss program,people feel shy, voluntarily drop out


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Selection Bias: The improper assignmentof test units to treatment conditions.

self-selected subjects by the researcher orthe test units themselves

Random assignment to treatments willsolve this.

Example: students selected according topreference.


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General Classes of

Experiments

Laboratory Experiments: some variable(s)are manipulated and others are carefully

controlled

May result in artificial situation

Question: Will the response be the sameoutside the laboratory?


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Experimental Simulation

Retain some realism of content thoughcontext is not real

Examples: simulated grocery aisles;

ad testing facilities


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Field Experiment

Take place in real settings

Control is traded off for realism

Example: Test marketing


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TestMarketing

Introducing the Product to the Limited but carefully selectedparts of the market places.

Two objectives

To determine the market acceptance

To test alternative level of marketing mix

Often used to fine-tune marketing strategiesand to determine sales volume


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Classification of

Experimental Designs

Symbols

X represents exposure of a test group to an

experimental treatmentO represents the observation or

measurement of the dependent variable

R indicates that test units (subjects) havebeen randomly assigned to treatments


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Experimental Design

PreExperimental

TrueExperimental Design

QuasiExperimental


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Pre-Experimental Designs

Three examples:

1. After-only design

X O1Problems?

No comparison

No control of Extraneous Variables


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2. One-group pretest-posttest design:

O1 X O2

Comparison of same individuals beforeand after

Problems?

Maturation, mortality, no control group,history effects

Frequently used in marketing research


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3. Static Group Design

Experimental Group: X O1

Control Group: O2 Design relies on similarity of two control

groups

Possible solution: matchingcharacteristics of the two groups (not thesame as random assignment)


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True Experimental Designs

All experimental designs involve randomassignment of test units to treatment and

control/comparison groups in the design Random assignment eliminates selection

bias


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Pretest-posttest control group design

Experimental Group R O1 X O2

Control Group R O3 O4 Treatment Effect= (O2-O1)-(O4-O3)

Assumption: Extraneous variables,

history, maturation, testing effects,instrumentation, will affect both groupsequally


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Posttest Only Control Group Design

Experimental Group: R X O1

Control Group: R O2

Treatment effect = O2-O1


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Solomon Four Group Design

Experimental Group 1: R O1 X O2

Control Group 1: R O3 O4Experimental Group 2: R X O5Control Group 2: R O6

Treatment effect, extraneous factors effectcan all be measured with this design


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More Complex Designs-

Quasi-Experimental Designs

Times Series designs: Severalmeasurements are made of dependent

variables over time Often do not to have control/comparison

groups

Are especially vulnerable to history/maturation effects


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Time Series can be symbolised as:

O1 O2 O3 O4 O5 XO6 O7 O8 O9 O10


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Multiple Time Series

EG: O1 O2 O3 O4 O5 XO6 O7 O8 O9 O10

CG: O11 O12 O13 O14 O15 O16 O17 O18

Similar to Time Series, one more group is added toserve as control group.


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Limitation of Experiments

Time

Cost

Administration


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thankyou

experiment research for class

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