Experimental Research designs

Concepts

• Experiment: Lab or Field

• Treatment

• Treatment effects

• Factor-independent variable

• Blocking factor

Experimental Design

Examine possible cause and effect relationship among variables

To establish variable X causes variable Y, all three conditions should be met:

• Both X and Y should covary

• Time sequence X should precede Y

• No other factor should possibly change the dependent variable Y

Principles of Research Design

• Principle of Replication

• Principle of Randomization

• Principle of Local control

Informal Experimental Design

1. Quasi Experimental Design

2. Pretest and posttest Experimental Group Design ( caution: testing and instrumentation)

3. Post test only control design

4. Pretest posttest experimental and control group design

Validity

• External – Generalizability to other setting

• Internal- History, maturation effects, testing, instrumentation, selection bias etc

Quasi E.D.

• Experimental group treatment and measure effects

Pre test & Post test ED

Experimental group

Pretest Treatment Post test

O1 X O2

Treatment Effect=(O2-O1)

Post test only control design

Group Treatment Outcome

Experimental group X O1

Control group O2

• Treatment Effect=(O1-O2)

Pretest posttest experimental and control group design

Group Pretest Treatment Posttest

Experimental group O1 X O2

Control group O3 O4

Treatment Effect=[(O2-O1)-(O4-O3)]

Solomon Four-Group Design

Group Pretest Treatment PosttestExperimental O1 X O2Control O3 O4Experimental X O5Control O6Treatment Effect E=O2-O1 =O2-O4 =O5-O6 =O5-O3 =[(O2-O1)-(O4-O3)] * all Es are similar if cause and effect is highly valid

Double blind studies

• Researcher-subjects are unaware

• Drugs

Design a study to examine the following situation.

An organization would like to introduce one of two types of new manufacturing processes to increase to the productivity of the workers, and both involve heavy investment in expansive technology. The company wants to test the efficacy of each process in one of its small plants.

Formal E.D.

Completely Randomized

Randomized Block

Latin Square

Factorial

They are required to judge simultaneous effect of two or more variables on dependent variable.

Concept

• Factor denotes independent variable• Level denotes various gradations of factor

(high, medium and low price)• Treatment refers to various levels of

factors• Blocking factor is a preexisting variable

that has an effect on dependent variable in addition to the treatment, the impact of which is important to assess

Completely randomized design

A transportation compnay manager wants to know the effect of fare reduction by 5, 7, and 10 rupees, on the average increase in number of passengers using bus as a means of transportation.

He chooses 27 routes and randomly assign nine routes to each of treatments for a two week period.

The design would look like

Routes Number of Treatment Number of

passenger before passenger after

Group 1 O1 X1 O2

Group 2 O3 X2 O4

Group 3 O5 X3 O6

* OS SIGNFY NUMBER OF PASSENGERS

Randomized Block Design

Now company manager was interested in targeting price reduction of right routes or sectors. Reduction would be more welcomed by the senior citizens or people living in crowded areas were driving is a problem than the suburbs.

First the manager would identify the routes fally into three categories i.e. retirement areas, crowded areas and suburbs. Thus now 27 routes would get assigned to one or the other of three blocks and then randomly assigned, within the blocks to three treatments.

Randomized Block Design

Blocking Factor: Residential AreasFare Reduction Suburbs Crowded Retirement

Urban Areas

5 X1 X1 X1

7 X2 X2 X2

10 X3 X3 X3

* OS are not shown but these measures will be taken

Latin Square Design

Two blocking factor (nuisance) across rows and columns.

• Day of the week 1. Midweek (Tue to Thrus)2. Weekend3. Mon and Friday

• Residential localities

Latin Square Design

Day of the Week

Residential Mid Weekend Mon/ Fri

Area

Suburbs X1 X2 X3

Urban X2 X3 X1

Retirement X3 X1 X2

Factorial Design

It enables us to check manipulations of two or more manipulation at the same time on dependent variable

The manager now is interested in knowing passenger increases if he used three different types of buses( Luxury, standard and regular). Using fare reduction and type of vehicle simultaneously

Fare reduction and Vehicle used

Bus Fare Reduction Rates

Type of Bus 5 7 10

Luxury X1Y1 X2Y1 X3Y1

Standard X2 Y2 X1Y2 X3Y2

Regular X3Y3 X2Y3 X1Y3

Any doubts?Thank you