Non-Experimental Approaches to Research

Why is this Important?

The classic true experiment is one where the experimenter has control over all aspects of the situation. Groups of appropriately selected subjects are assigned at random to experimental conditions.

Sometimes this isn't possible. Can we put you in such conditions?

Let's say you wanted to test memory after some traumatic event.

How about the details of what occurred during a nuclear reactor mishap in your community?

In a True Experiment - we would select subjects at random and then randomly assign them to a control group (live in a calm environment - Group 1) or an experimental group (we arrange you to live next to a nuclear incident).

Consider our illustrations. Would this work?

Here are the conditions. Group 1 is the control group.

We wish to thank the Physics Department for helping in producing the conditions for Group 2.

 

Now what would our subjects think about this? I bet this wouldn't work.

It is obvious we can't put people in situations that are dangerous.

It is also obvious that we cannot always manipulate all the IVs.

 

 

 

 

What are you going to do? Let's see some solutions!

Quasi-Experiments

Quasi-experimental designs do not allow the researcher to control the assignment of subjects to conditions

1. Factorial Designs with One Nonmanipulated Variable

Another example, might be a study of gender issues - you can't make someone a male or female for purposes of the study. In our study, above, the EXPLOSION vs. Control would be the nonmanipulated variable as we would test accident survivors vs. a suitable matched control group.

2. Time Series and Interrupted Time Series

The researcher makes several observations of behavior over time prior to and then immediately after introduction of an IV.

The basic idea is:

Observation1 O2 O3 O4 X(treatment) O5 O6 O7 O8

This is the classic design from Cook and Campbell.