PSY 250

Exam 3 Review

RESEARCH STRATEGIES

Experimental strategies are not determined solely

by potential weaknesses – EVERY study has some

weakness.

Rather, the difference between true and non or

quasi experiments is determined by the amount of

control over assignment to groups (between

subjects) or order of conditions (within subjects)

RESEARCH STRATEGIES

Correlational designs are NOT between subject

designs with discrete categories or groups you are

comparing!• This is probably ex post facto or differential groups

design

Not every design that compares two variables is

correlational!

BETWEEN VS. WITHIN

Between • DIFFERENT individuals give data point at each

level of the IV. Therefore, you are comparing the average scores of one group of people to the average scores of (a) DIFFERENT group(s) of people

Within• The SAME individuals participate and give a data

point at each condition of the experiment (or each level of the IV).

• Thus, you are comparing an individual’s score under one condition to their own scores in a different condition(s)

VARIABLES

If you are looking at the effects of more than one variable on another

variable (DV), then you have multiple IVs (i.e.. a factorial design)

If one IV is between and another is within, you have a mixed factorial

design

You are then probably looking at main effects of IVs PLUS their

interactions• i.e. does the DV at one level of one IV depend on the level of another IV• E.g. do girls perform better with fewer classmates in a classroom while

boys perform better with more classmates in a classroom? (interaction with number of classmates (IV 1) and gender (IV 2)

INTERACTIONS CONT.

If both males and females do better (and about the

same amount better) with fewer classmates then

gender and number of classmates do not interact

However, if the improvement is much greater for

one gender than the other, there may be an

interaction

MAIN EFFECTS

If males generally perform better than females (or vice versa), but

class size does not effect performance, there is a main effect of

gender but not class size and no interaction

If both genders do equally well, but both do better in smaller

classes, then there is a main effect of class size, but not gender

If males do better than females but both do better in smaller

classes, there are main effects of both gender and class size but no

interaction

There can be main effects and no interaction AND interactions

without main effects

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dressy casual sloppyMales

Females

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dressy casual sloppyMales

Females

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sloppy casual dressy

malesfemales

SEEING INTERACTIONS

• Is there an interaction?

• What numbers do we

compare to see if there is

a main effect of:• Gender?• Class size?

• Are there main effects?

Small large

males 80 78

females 70 69

Small large

males 85 72

females 80 68

Small large

males 84 81

females 83 71

SEEING INTERACTIONS

• What numbers

would we place in

the missing cell to

create• An interaction?• No interaction?

Small large

males 80 78

females 70

Small large

males 85 72

females 68

Small large

males 84

females 83 71

1. DIFFERENTIAL RESEARCH DESIGN (NE)

Also called ex post facto research

Compares pre-existing groups defined by

participant variable

E.g. shyness scores from single child vs. child with

siblings

Existence and description of relationships

Similar to correlational design but different data

and analysis

2. POSTTEST-ONLY NON-EQUIVALENT CONTROL GROUP

DESIGN (NE)Also called static group comparison

Applied settings

Measure effectiveness of treatment with pre-existing

participants

Similar but nonequivalent participants used as control

condition

X O Exp. GrpO Control

3. P R E T E S T – P O S T T E S T N O N -E Q U I VA L E N T CONTROL GROUP

DESIGN (QE)

Stronger version of posttest only designBoth control (C) and experimental (E) groups measured prior to treatment and again after E group receives treatmentShows if groups are similar on the DV before manipulation of IV Also controls for time related changes in DV indep. of IVReduces threat of both assignment bias and time related threats

O X O Exp. Grp. O O Control

1 . O N E - G R O U P P R E T E S T – P O S T T E S T D E S I G N ( N E )

One pre and one post-test measurement

E.g. voter’s confidence in electoral candidate

before and after televised debate

O X O

2. TIME SERIES DESIGN (QE)

Treatment is manipulated by researcher

Series of observations for each participant before

and after treatment or event

E.g. Measures of stress weekly for 2 months

preceding and following introduction of

aromatherapy in workplace

O O O X O O O

3. I N T E R R U P T E D T I M E SE R I E S D E SI G N ( Q E )

Treatment is NOT manipulated by researcherE.g. Depression measured monthly for 3 months before and after ChristmasWorks with predictable event like decriminalizing marijuanaFor unpredictable events like Katrina, rely on archival dataCan see trends in data before treatmentCan observe long-term changes following treatmentBut other changes can coincide with treatment

• E.g. cold weather/snowfall and Christmas

4. E Q UI VA L E N T T I M E – SA M P L E S D E SI G N ( Q E )

Treatment is repeatedly administered and removed during

series of observations

E.g. introducing music in the workplace – turning it on and off

and measuring worker concentration at regular intervals weekly

O O O X O N O X O

Best used when treatment effect is expected to be temporary

Hard to determine causality if treatment effect is permanent

CORRELATIONAL STUDIES

Simply measures 2 variables [usually two scores (X and Y) from

same individual] or scores on 1 variable between 2 related individuals

Criterion (Y) and Predictor (X) variables

Degree and nature of relationship• descriptive or predictive

Correlation coefficients+1.00 to -1.00

No attempt to explain relationship

No attempt to manipulate or control variables