Psychology Exam 3: Factoral Design ch.12

Testing threat

A type of order effect in which there is a change in participants as a result of experiencing the dependent variable(DV) —the test, more than once.

Ex:(One group)—>Pretest(before)—→New Method—>Post test(after)

Selection-history threat

An outside event or factor systematically affects participants at one level of the IV(independent level)

Ex: Treatment(death of a family member)—>it will effect the protest.

Selection-history threat

An outside event or factor systematically affects participants at one level of the IV(independent level)

Ex: Treatment(death of a family member)—>it will effect the protest.

Selection-attrition threat

Participants in only one experimental group experience attrition.

Ex: Two universities. Group one (university 1): Has to only travel few miles. While Group 1 travels more miles. Group 1 will most likely continue with the study while Group 2 will not select to travel extra miles. They are similar because they are both bias and select what they feel like doing.

Observer bias

Bias caused by researchers’ expectations influencing how they interpret the results.

Demand characteristics

Bias that occurs when participants figure out what a research study is about and Change their behavior in the expected direction

• Controlling for observer bias and demand characteristics(double-blind study, masked study)

Placebo effect

Participants in an experimental group improve only because they believe in the efficacy of the therapy or drug they receive.

Ex: Women receiving cognitive therapy improve simply bc they believe the therapy will work for them.

Ceiling effect

The participants scores on the DV are clustered at the high end.

Ex:Questions too easy: everyone gets them right.

Floor effect

The participants scores on the DV are clustered at the low end.

Ex: Questions too hard: Everyone gets them wrong

How do designs confounds threaten internal validity?

Confounds

Confounds usually threaten internal validity by creating false differences between groups:

• Sometimes a compound can actually make it harder to detect an effect

• Confound can act in reverse—it can mask the true effect of your independent variable

Confounds

Confounds usually threaten internal validity by creating false differences between groups:

• Sometimes a compound can actually make it harder to detect an effect

• Confound can act in reverse—it can mask the true effect of your independent variable

Independent variable

Dependent variable

Measurement Error

Any factor that can inflate or deflate a person’s true score on the DV—Solutions for reducing measurement error:

-Using reliable, precise measurements

-Measuring more instances.

Individual Differences

Note: Individual differences spread out scores within each group