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Research Design

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Content

• Introduction

• Nature of and classification of design

• Developing and appropriate research design

• Experimental research design

– Randomized design – Latin Square design

– Factorial design

• Basic principles, types of experimental design -pre-experimental design -true-experimental design

• Validity – External

– Internal

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1. Introduction

• A research design is the arrangement of conditions for collection and analysis of data ina manner that aims to combine relevance tothe research purpose with economy in

procedure.• Research design is the conceptual structure or

framework within which research is conducted.

• It constitutes the blueprint for the collection,

measurement and analysis of data.• As such the research design includes an outline of

what the researcher will do from writing thehypothesis to the final analysis of data.

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1.1 Research DesignDecisions

• More explicitly, the research design decisionshappens to be in respect of:

– What is the study about?

– Why is the study being undertaken? (Rationale)

– Where will the study be carried out?

– What type of data would be required?

– What would be most appropriate source for thesedata?

– What would be the sample design?

– What would be time frame for the study?

– What techniques of data collection will be used?

– How will the data be analyzed?

– In what style will the report be prepared?

–

–

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1.2 Important Features of aResearch Design

• From what has been stated in the previous slide,one can state the important features of aresearch design as:

– It is a plan that specifies the sources and types of

information relevant to the research problem – It is a strategy specifying which approach will be

used for gathering and analyzing data

– It also includes the resource and other constraintsunder which the study would be conducted

• In brief a research design must contain: – A clear statement of the research problem

– Procedures and techniques to be used for gatheringinformation

– The population to be studied, and

– Methods to be used in processing and analyzing data

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2. Nature of and Classificationof DesignResearch Design

ConclusiveResearch Design

ExploratoryResearch Design

DescriptiveResearch

CausalResearch

Cross-SectionalDesign

LongitudinalDesign

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2.1 Classification of Design

• Research designs can be broadly classified asexploratory or conclusive

• Exploratory research – The primary objective is to provide insights into, and

an understanding of, the problem confronting theresearcher.

– The information needed is loosely defined

– The research process that is adopted is flexible andunstructured

– Given the above characteristics, the findings of exploratory research is generally regarded astentative or as input for further research

– Typically such research is followed by furtherexploratory or conclusive research

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• Conclusive research – The objective of conclusive research is to test

specific hypotheses and examine specificrelationships.

–

It is typically more formal and structured – Conclusive research design may be either descriptive

or causal, and descriptive research may be eithercross-sectional or longitudinal

– Descriptive research•

The major objective of descriptive research is to describesomething with some degree of certainty

– Causal research• It is used to obtain evidence of cause-and-effect (causal)

relationships.

–

–

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• Causal research is appropriate for the followingpurposes

– To understand which variables are the cause(independent variables) and which variables are

the effect (dependent variables) of a phenomenon – To determine the nature of the relationship between

the causal variables and the effect

–

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3. Developing an AppropriateResearch Design

• Because of varied research objective adopted byresearchers, it is impossible to outline aresearch design that is appropriate forachieving all types of research objectives.

• The question of good design is related to thepurpose or objective of the research problemand also with the nature of the problem to bestudied.

• Generally, the design which minimizes bias andmaximizes the reliability of the data collectedand analyzed is considered a good design.

•

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• A research design appropriate for a particularresearch problem, usually involves theconsideration of the following factors:

– The means of obtaining information

– The skills of the researcher – The objective of the problem to be studied

– The availability of resources

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4. Experimental ResearchDesign

• An experimental research design is a set of procedures specifying:

– The test units (for example, individuals) and howthese units are to be divided into homogenous

subsamples – What independent variable(s) or treatment(s) are to

be manipulated

– What dependent variable(s) are to be measured, and

– How the extraneous variables are to be controlled

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4.1 Symbols Used inExperimental Designs

• X = the exposure of a group to an independentvariable, treatment, or event, the effects of which are to be determined

•

• O = The process of observation or measurementof the dependent variable on the test units orgroup of units

•

• R = the random assignment of test units orgroups to separate treatment

•

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4.2. Randomized Design

• In randomized design the test units are randomlyassigned to experimental treatments.

• Randomized block designs are useful when thereis only one major external variable, such as

sales, store size, or income of the respondent,that might influence the dependent variable.

• The test units are blocked, or grouped, on thebasis of the external variable.

• By blocking, the researcher ensures that thevarious experimental and control groups arematched closely on the external variable.

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4.3. Latin Square Design

• A Latin Square is used in experimental designs inwhich one wishes to compare treatments andto control for two other known sources of variation.

•

Latin Squares were first used in agriculturalexperiments. It was recognized that within afield there would be fertility trends runningboth across the field and up and down the field.

– So, in an experiment to test, say, four different

fertilizers, A, B, C, and D, the field would bedivided into four horizontal strips and four verticalstrips, thus producing 16 smaller plots.

– A Latin Square design will give a random allocation of fertilizer type to a plot in such a way that eachfertilizer type is used once in each horizontal strip

(row) and once in each vertical strip (column).

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4.4. Factorial Design

• A factorial design is used to measure the effects of two or more independent variables at variouslevels.

• Unlike the randomized block design and Latin Square,factorial designs allow for interactions betweenvariables.

• An interaction is said to take place when thesimultaneous effect of two or more variables isdifferent from the sum of their separate effects.

• A factorial design may also be conceptualized as atable. In a two-factor design, each level of onevariable represents a row and each level of anothervariable represents a column.

• Multidimensional tables can be used for three or morefactors.

• Factorial designs involve a cell for every possible

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5. Types of ExperimentalDesign

• Pre-experimental designs – One shot design (after only design)

– One group pre- and post-test design

– Static group design

• True experimental Designs – Post-test only control group design

– Pre- and post-test control group design

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5.1 One Shot Design

• Also know as after-only design, can besymbolically represented as:

– X O1

•

A single group of test unit is exposed to atreatment (X), and then a single measurementon the dependent variable is taken (O1 ).

• There is no random assignment of test units.

•

Note that the symbolR

is not used, because thetest units are self-selected or selectedarbitrarily by the researcher.

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5.2 One Group Pre-Post testDesign

• Symbolized as: O1 X O2

• In this design, a group of test units is measuredtwice. There is no control group.

•

First a pre-treatment measure is taken (O

1), thenthe group is exposed to the treatment ( X ).Finally, a post-treatment measure is taken (O2).

• The treatment effect is treated as O2 - O1

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5.3 Static Group Design

• It is a two group experimental design. One groupcalled the experimental group (EG), is exposedto the treatment, and the other, called thecontrol group (CG), is not.

• Measurements on both groups are made onlyafter the treatment, and test units are notassigned at random. This is symbolicallydescribed as:

–

EG:X O1 – CG: O2

• The treatment effect is measured as O1 - O2

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5.4 Pretest-Posttest ControlGroup Design

• The distinguishing feature of the trueexperimental designs, as compared to pre-experimental designs, is randomization.

• In true experimental designs, the researcher

randomly assigns test units to experimentalgroups and treatments to experimental groups.

• In the pretest-posttest control group design, testunits are randomly assigned to either the

experimental or the control group, and a pre-treatment measure is taken on each group.Only the experimental group is exposed to thetreatment, but post-test measures are taken onboth groups.

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• The design is symbolized as: EG:R O1 X O2

CG: R O3 O4

• The treatment effect (TE) is measured as: (O2 - O1) – (O4 - O3 )

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Posttest-Only Control GroupDesign

• The posttest-only control group design does notinvolve any pre-measurement. It may besymbolized as: EG:R X O1

CG: R O2

• Treatment effect is obtained by

• TE = O1 - O2

• The design is fairly simple to implement, becausethere is no pre-measurement, the testingeffects are eliminated.

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6. Validity

• When conducting an experiment, a researcherhas two goals:

1. Draw valid conclusions about the effects of independent variables

2. Make valid generalizations to a larger population of interest.

•

• The first goal concerns internal validity, and the

second goal concerns external validity

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6.1 Internal Validity

• Internal validity refers to whether the manipulation of the independent variables or treatments actuallycaused the observed effects on the dependentvariables.

• Thus, internal validity examines whether the observed

effects on the test units could have been caused byvariables other than the treatment.• If the observed effects are influenced or confounded

by extraneous variables, it is difficult to draw validinferences about the causal relationship betweenthe independent and dependent variables.

• Internal validity is the basic minimum that must bepresent in an experiment before any conclusionabout treatment effects can be made.

• Control of extraneous variable(s) is a necessarycondition for establishing internal validity

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Threats to Validity

• History – Specific events that are external to the experiment but occur

at the same time as the experiment

• Maturation – Changes in test units over a period of time

•

Testing Effects – Caused by the process of experimentation

• Instrumentation – Refers to changes in the measuring instrument

• Statistical Regression – Occurs when test units with extreme scores move closer to the

average score during the course of the experiment• Selection Bias

– Improper assignment of test units to treatment conditions

• Mortality – Refers to loss of test units while the experimentation is in

progress

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6.2 External Validity

• External validity refers to whether the cause-and-effect relationships found in the experiment canbe generalized.

• In other words, can the results be generalized

beyond the experimental situation

• It is desirable to have an experimental designthat has both internal and external validity, but

there is a dilemma… – To control the effects of extraneous variables, a

researcher may conduct an experiment in anartificial environment. This enhances internalvalidity, but it may limit the generalizability of the

results, thereby reducing external validity.

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End of Chapter 3

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