Data Collection Via Experiments

Subject

Subject

Individual on which we are going to measure a variable

Response variable (y)

Outcome of the experiment

Explanatory variable (x)

Variable used to explain the response

Factor

Explanatory variable with a fixed number of values

Treatment

The condition or conditions applied to a subject or individual in an experiment

Control

A “treatment” with supposedly zero effect

Placebo

A fake treatment level to account of psychological effects

Double-blind study

An experiment where the individual and researcher don’t know which treatment is applied

Confounding

A situation where a lurking variable, in addition to the explanatory variable, is affecting the response

Principles of valid experiments

1. Control/comparison

2. Randomization

3. Replication

4. Double blinding (if possible)

Control/comparison

Control lurking variables by including comparison treatments, using homogeneous subjects; used to measure placebo effect

Randomization

Neutralize effects of lurking variables by randomly assigning subjects to treatments (to limit bias)

Replication

Assign more than one subject to each treatment group

Randomized controlled experiments

Randomly split all subjects into treatment groups

Randomized block experiment

Separate first, then randomize within each group/block

Diagnostic Effect

Diagnosis of subjects biased by preconceived notions about the effectiveness of the treatment

Solution: blind the dignoser

Hawthorne Effect

People behave differently from how they would normally behave

Solution: hidden observation (if ethical)