Observational vs quasi-experimental design?

I am having some difficulty understanding the difference between and identifying an observational vs quasi-experimental design. From my understanding, an observational study is one in which the researcher does not influence the system and only records what they observe (duh). In an experimental study, the researcher manipulates the experimental units such they have different treatments and measures some resultant metric(s), usually to compare them. My understanding of quasi experimental studies is that the researcher uses groups that are already different from one another rather than apply the treatment to the EUs themselves.

For example, let’s say a researcher is making observations on bird diversity in different land use types (eg forest vs agriculture). Odds are he or she isn’t going to make a forest and farm and put birds in them to see which survive. They are going to go to several farms and several forests and observe the birds that live in each.

Now, it seems that this is a quasi-experimental design based on my above definitions, but does that mean that every comparison study is going to be either experimental or quasi experimental? I can’t think of particularly many studies that would fall under the observational category, in that case (correlational, descriptive).


First, as far as you have described the research design, the study is not a quasi-experiment.

I prefer the term natural experiment to quasi-experiment, because I think it more clearly communicates the fact that treatment needs to have been randomly assigned (or as-if randomly assigned). I use the term natural experiments below, but I consider the two equivalent in meaning.

You are correct that experiments are confined to those situations where a researcher actually manipulates treatment assignment.

Observational studies comprise anything that was not an experiment. Natural experiments are a subset of observational studies, but in a natural experiment units were assigned to treatment in a random process (or as-if random, or almost random).

You might look for a natural experiment (or quasi-experiment) if you were seeking to identify the causal effect of a treatment on a set of outcomes. Then you would look for a situation where assignment to that treatment was assigned randomly (or as-if randomly) by nature or a government program, for example. For example, if you wanted to study the impact of forest fires on bird diversity, you might find a place where the government has defined that it will fight fires when they come with X miles of residential areas. After forest fires, you could compare (i) bird diversity in areas affected by the forest fire just a little further than X miles away from residential areas (treatment group) to (ii) bird diversity in areas just a little less than X miles away from residential areas (control group). Because birds would not choose where to live prior to fire based on the government’s designation of the distance X, we can expect that before the fire on either side of the X-mile cutoff, birds would be identical on average. There assignment to treatment (being “treated” by the forest fire) is as-if random on either side of the X-mile cutoff. This design is called a regression-discontinuity design [1] or a geographic regression discontinuity design [2].

Also, see more discussion of the difference here: Panel study is a quasi-experimental study? Quasi-experimental is the same as correlational?

  1. https://en.wikipedia.org/wiki/Regression_discontinuity_design
  2. “Geographic boundaries as regression discontinuities.” LJ Keele, R Titiunik. Political Analysis, 2014

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