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17. Quasi-experimental

research designs

Pelham & Blanton

Ch. 8

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Results from last week:

Psych 217:

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Maybe not enough power, so I took the

leftover chocolate to work:

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BiM chose in the opposite direction,made overall results worse!

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My co-workers . . .

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Examples of Quasi-Experimental

Independent Variables Demographic categories (e.g., gender,

culture, race)

Individual differences (e.g., high & lowself-esteem)

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Types of Quasi-experiments

1. Person by treatment quasi-

experiments

2. Natural experiments

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Person by Treatment

Quasi-Experiments Measures at least one IV

e.g., men vs. women, low vs. high self-

esteem, patient vs. control, class section inyesterdays demo

Manipulates (and randomly assigns) at

least one other IV e.g., drug vs. placebo, success vs. failure

feedback, high fat vs. low fat

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Culture & the Effect of Talking

on Cognitive Performance To examine cultural

difference in how thinkingaloud and silently affects

cognitive performance IV Culture (European

American vs. East AsianAmerican)

Talking (Talking vs.Silence)

DV Cognitive Performance

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Median Split

A way to convert a continuous variable

into a categorical variable

Determine the median of a sample anddivide the group into two groups (e.g.,

high vs. low SE)

Problem people near the cut-off point

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Therefore, rather than doing median

split take people with extreme scores

What do you know about people in themiddle of the distribution?

assume that people who possess a

medium amount of an attitude or trait willrespond to treatments in medium amounts

when compared to people who scored at

the extreme

Use extreme scores to increase testsensitivity

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Inductive Problem

Because we are not manipulating the IV

it is possible that there are confounds

e.g., self-esteem correlated with gender.SES, depression, anxiety, etc

Inductive problem we never know if

we have ruled out all possibleconfounds

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Natural Experiments

Experimenter does not manipulate anything

Naturally occurring events expose some

people to a condition and other people toother condition

e.g., effect of job loss on marital satisfaction; effect

of natural disasters on anxiety levels

Usually rely on archival data

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Again we have issue of

confounds!!! Because naturally occurring events are

not completely random

Measures all the possible confounds(again problem of induction)

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Comparison (Control) Group?

It is difficult to determine what an

adequate control group would be in

natural experiments. Patching: adding new conditions to help

establish the size of the effect, to test

for the influence of conceivableconfounds, or both

i.e., many control groups

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True vs Quasi-Experiments

Internal validity true wins

External validity quasi wins

Ethical sensitive topics quasi wins

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Examples

1. The effect of poor housing on health.

2. The effect of learning a second

language on cognitive ability.