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Research Methods in MIS: Experimentation Dr. Deepak Khazanchi Acknowledgment: Some of the information in this presentation is Based on Cooper and Schindler.

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Presentation on theme: "Research Methods in MIS: Experimentation Dr. Deepak Khazanchi Acknowledgment: Some of the information in this presentation is Based on Cooper and Schindler."— Presentation transcript:

1 Research Methods in MIS: Experimentation Dr. Deepak Khazanchi Acknowledgment: Some of the information in this presentation is Based on Cooper and Schindler (2000) and Sproull (1996).

2 Variables in Experiments Independent variables Treatment or experimental variable: The independent variable that is manipulated by the researcher so that different groups of subjects receive different kinds or amounts. Dependent variables

3 Advantages of an Experiment? Researcher’s ability to manipulate the independent variable Contamination from extraneous variables can be controlled more efficiently Convenience Cost Replication

4 Disadvantages of Experiments Artificiality of the laboratory Generalization from nonprobability samples Larger budgets needed Restricted to problems of the present or immediate future Ethical limits to manipulation of people

5 Experimentation Process Select relevant variables Specify the treatment levels Control the experimental environment Choose the experimental design Select and assign the subjects Pilot-test, revise, and test Analyze the data

6 Ways to Assign Subjects Random Assignment Matching Assignment Quota matrix

7 Does a Measure Accomplish What it Claims? Internal validity External validity

8 Threats to Internal Validity History Maturation Testing Instrumentation Selection Statistical Regression Experimental Mortality

9 Threats to External Validity The Reactivity of Testing on X Interaction of Selection and X Other Biasing Effects on X Artificial setting of testing Respondents knowledge of testing

10 Experimental Designs Preexperimental designs True experimental designs Field experiments

11 Design Symbols X the introduction of an experimental stimulus to the respondent 0 a measure or observation activity R an indication that sample units have been randomly assigned

12 Preexperimental Designs One-shot case study One-group pretest-posttest design Static group comparison

13 True Experimental Designs Pretest-posttest control group design Posttest-only control group design

14 Operational Extensions of True Designs Completely randomized designs Randomized block design Latin square Factorial design Covariance analysis

15 Field Experiments: Quasi- or Semi-Experiments Non Equivalent Control Group Design Separate Sample Pretest-Posttest Design Group Time Series Design


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