Quasi experiments
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Quasi-Experiments. Research Objective. Study relationships among variables for existing groups. Show direct cause & effect. Explain outcomes after the fact. Type of Design. Cross-Sectional Longitudinal. True Experiment Quasi-Experiment. Explanatory Case Study Exploratory Case Study.

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Quasi-Experiments

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Quasi experiments

Quasi-Experiments


Research objective

Research Objective

Study relationships among variables for existing groups

Show direct cause & effect

Explain outcomes after the fact


Type of design

Type of Design

Cross-Sectional

Longitudinal

True Experiment

Quasi-Experiment

Explanatory Case Study

Exploratory Case Study


What are quasi experiments

What Are Quasi-Experiments?

  • Quasi-experiments are just like experiments except for one thing.

  • They violate the condition of random assignment of test subjects to treatment and control groups.


Why do this

Why Do This?

  • There are two main reasons why researchers fail to achieve the random assignment assumption:

    • It is difficult or impossible to achieve random assignment because the participants are embedded in groups

      • Example: students in classes

    • There are ethical reasons for assigning some participants to the treatment group

      • Example: potentially life-saving new drug


The classic experiment

The Classic Experiment

  • Select representative sample

  • Randomly assign to control and treatment groups

  • Measure the outcome (dependent) variable for both groups

  • Do something to the treatment group

  • Measure the outcome variable again for both groups


True experiment

True Experiment


Quasi experiment

Quasi-Experiment

Did you select a representative sample of test cases from a single homogeneous population?

YES

No

Not a quasi-experiment

Not a quasi-experiment

Not a quasi-experiment

No

No

Did you ASSIGN test subjects to treatment & control groups NON-randomly?

YES

Did you then do something to treatment groups that you did not do to the control group?

YES

Quasi-Experiment


Non equivalent group designs

Non-Equivalent Group Designs

  • One of the most common reasons for going to a quasi-experiment is that your potential test subjects are naturally embedded in some larger groups.

    • Students in classes

    • Hospital patients in wards

    • Participants in an intervention program

    • Monkeys in troops


Subjects embedded in groups

Subjects Embedded in Groups

  • There is a new set of experiential learning materials about environmental education for high school students.

  • You believe that this way of learning about the environment is more apt to produce change in behavior than traditional methods.

    • Things like recycling, turning off the lights, not letting the water run while you brush your teeth.


Your subjects

Your Subjects

  • You get three of seven science teachers in a school district to agree to try the new approach.

    • The other 4 will use the old approach.

  • Your test subjects are students in their classes.

  • You will measure behavior (how often they recycle, etc.) before and after the education, new or traditional.


The problem

The Problem

  • This looks just like a true pre-post measurement experiment.

  • The problem is that your test subjects, the students, come in groups.

  • You did not assign Student A to control and Student B to treatment.


The threat

The Threat

  • The big problem with this design is that you cannot be really sure that the control and treatment groups are equivalent.

    • For example, what if the 3 teachers who agree to try the new approach are just better teachers and their students are therefore more motivated?


Key concepts

Key Concepts

What’s the same and what’s different between a true and a quasi-experiment.


The difference

The DIFFERENCE

  • Quasi-experiments differ from true experiments in only one way: there is no random assignment of individual participants to treatment and control groups.

  • This makes it much harder to control non-treatment variance.

  • It greatly increases threats to internal validity.

  • It can also increase threats to external validity.

  • It reduces explanatory power.


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