In some scientific experiments in, say, medicine or biology,
you have a lot of control over your subjects and your independent variables--you can randomly assign subjects to
certain conditions and select the treatments you want to give them. For
example, if you're studying the effects of Valium on memory, you get
to pick the doses of Valium that you give to people.
In a pseudoexperiment, however, you have little or no control
over your subjects and independent variables. For example, suppose you're
instead studying the effects of mild head injury on memory. You don't
get to choose who has a head injury and who doesn't--you just have to take
whoever comes.
Why do you care? Well, it's harder to draw conclusions from
pseudoexperiments; in particular, it's generally difficult--even
impossible--to make claims about causation. Let's say that in the
example study above, you find that people with a history of head injuries
do more poorly than control subjects in school. Now, maybe the head
injury caused the poor school performance. Then again, maybe these head-injured people were generally dumber to begin with and had a tendency
to do dumb things in every aspect of their lives. Then too, maybe these
people weren't dumb; maybe they were ADHD types who can't sit still in
school but who get thrills from participating in dangerous activities. It's hard to tell.
Okay, so given the problems with pseudoexperiments, why do them at all?
Well, as I suggested above, sometimes they're the only way you can address
an interesting question or problem. If you're comparing men to women,
African-Americans to Caucasians people,
children to adolescents, college students to elderly adults, or crack
addicts to non-addicts, you don't get to pick who goes in what
group--but it's still useful to know if there are differences between
them, and careful experiments can help rule out possible causes of
those differences.