1. Quasi Experiments Non-Experimental Research
Research Methods & Statistics
Fall 2011

2. Quasi Experiments
“Research procedure in which the scientist must select subjects for different conditions from preexisting groups”
Research Methods, McBurney & White
“An empirical study used to estimate the causal impact of an intervention on its target population. Quasi-experimental research designs share many similarities with the traditional experimental design or randomized controlled trial, but they specifically lack the element of random assignment to treatment or control. Instead, quasi-experimental designs typically allow the researcher to control the assignment to the treatment condition, but using some criterion other than random assignment.
Wikipedia, Nov. 17, 2011

3. It’s a matter of control
True Experiment
Quasi Experiment
Random assignment of subjects to condition
Manipulate the IV
Control allows ruling out of alternative hypotheses
Selection of subjects for the conditions
Observe categories of subjects
If the subject variable is the IV, it’s a quasi experiment
Don’t know whether differences are caused by the IV or differences in the subjects

4. Other features
In some instances cannot completely control the what, when, where, and how
Need to collect data at a certain time or not at all
Practical limitations to data collection, experimental protocol

5. Validity
Internal validity is reduced due to the presence of controlled/confounded variables
But not necessarily invalid
It’s important for the researcher to evaluate the likelihood that there are alternative hypotheses for observed differences
Need to convince self and audience of the validity

6. External validity
If the experimental setting more closely replicates the setting of interest, external validity can be higher than a true experiment run in a controlled lab setting
Often comes down to what is most important for the research question
Control or ecological validity?

7. Nonequivalent Control Group Designs
2 groups, non-random allocation of subjects and groups, pre-test, treatment (Y/N), post-test
Desired pattern:
Dependent variables have equal pre-test values, difference seen between experimental and control groups on post-test (Pre: LL, Post: HL)
Want to show that any differences that exist did not impact the value of the variable of interest

8. Exercise Interpret the following graphs (experimental, control):
Pre: (L, H) Post: (M, H)
Pre: (L, M) Post: (H, ML)
Pre: (L, M) Post: (H, M)
If unequal initial values, it is only if the control remains constant and the experimental goes from being lower than the control to higher than it (the third case), that can you have good confidence that the IV being manipulated was responsible for the change
In the first case, the control group remained constant and higher than the experimental group. There might be a ceiling effect so that it was not possible for the control group to perfom any better – the improvement in the experimental group might not be due to the experimental manipulation
In the second case, the experimental group was always better than the control group, but both improved for the post-test. Improvement likely caused by maturation.

9. Mixed Factorial Design with One Non-manipulated Variable
Example: experiment on pain perception (effect of caffeine, expected differences between men and women)
Protocol:
25 men/25 women, each takes part in two sessions, one week apart
One session: drink coffee (decaf) and put hand in ice-water until feel pain
Other session: drink coffee (caffeinated) and put hand in ice-water until feel pain
Between subjects variable (male/female)
Within subjects variable (caffeine intake)

10. Non-Experimental Research
Read and understand:
Gabriella Belli - Nonexperimental Quantitative Resarch
“Any quantitative study without manipulation of treatments or random assignment is a non-experimental study”
Experimental research shows cause and effect
Non-experimental research studies variables as they exist

11. Purpose Descriptive: Predictive: Explanatory :
primary focus for the research is to describe some phenomenon or to document its characteristics.
Predictive:
primary focus for the research is to predict some variable of interest (criterion) using information from other variables (predictors).
Explanatory :
the primary focus for the research is to explain how some phenomenon works or why it operates.

12. Time Frame Cross-sectional: Prospective (longitudinal): Retrospective:
data are collected at one point in time, often in order to make comparisons across different types of respondents or participants.
Prospective (longitudinal):
data are collected on multiple occasions starting with the present and going into the future for comparisons across time.
Retrospective:
look back in time using existing or available data to explain or explore an existing occurrence.

13. Techniques Surveys Interviews Observations Unobtrusive methods:
Interviews
Observations
Unobtrusive methods: