Experimental design
Upcoming SlideShare
Loading in...5
×
 

Experimental design

on

  • 739 views

 

Statistics

Views

Total Views
739
Views on SlideShare
739
Embed Views
0

Actions

Likes
0
Downloads
6
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Experimental design Experimental design Presentation Transcript

  • Experimental Research designs
  • Concepts• Experiment: Lab or Field• Treatment• Treatment effects• Factor-independent variable• Blocking factor
  • Experimental DesignExamine possible cause and effect relationship among variablesTo 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 Design1. Quasi Experimental Design2. Pretest and posttest Experimental Group Design ( caution: testing and instrumentation)3. Post test only control design4. 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 EDExperimental groupPretest Treatment Post testO1 X O2Treatment Effect=(O2-O1)
  • Post test only control designGroup Treatment OutcomeExperimental group X O1Control group O2• Treatment Effect=(O1-O2)
  • Pretest posttest experimental and control group designGroup Pretest Treatment PosttestExperimental group O1 X O2Control group O3 O4Treatment Effect=[(O2-O1)-(O4-O3)]
  • Solomon Four-Group DesignGroup 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 RandomizedRandomized BlockLatin SquareFactorialThey 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 designA 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 likeRoutes Number of Treatment Number of passenger before passenger afterGroup 1 O1 X1 O2Group 2 O3 X2 O4Group 3 O5 X3 O6* OS SIGNFY NUMBER OF PASSENGERS
  • Randomized Block DesignNow 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 Areas5 X1 X1 X17 X2 X2 X210 X3 X3 X3* OS are not shown but these measures will be taken
  • Latin Square DesignTwo blocking factor (nuisance) across rows and columns.• Day of the week1. Midweek (Tue to Thrus)2. Weekend3. Mon and Friday• Residential localities
  • Latin Square Design Day of the WeekResidential Mid Weekend Mon/ FriAreaSuburbs X1 X2 X3Urban X2 X3 X1Retirement X3 X1 X2
  • Factorial DesignIt enables us to check manipulations of two or more manipulation at the same time on dependent variableThe 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 RatesType of Bus 5 7 10Luxury X1Y1 X2Y1 X3Y1Standard X2 Y2 X1Y2 X3Y2Regular X3Y3 X2Y3 X1Y3
  • Any doubts? Thank you