Ch.11, Complex Designs

Question 1

Why are repeated measures used on smaller sample sizes?

Answer 1

Need fewer people; produces more power (probability of finding statistically significant results)

Question 2

Why is individual difference not a confound in repeated measures?

Answer 2

INDIVIDUAL DIFFERENCE VARIABLES DON’T MATTER; AN INDIVIDUAL’S MEASURES ARE JUST BEING COMPARED TO THAT INDIVIDUAL

Question 3

Difference between carryover and sensitization effects

Answer 3

Carryover Effects: something about the condition specifically influences next condition (medication/drug carryover effects)
Sensitization Effect: specific type of carryover type, in which an experience in one condition makes participants extra sensitive to the manipulated variable in the next condition

Question 4

Repeated Measures/Within Subjects

Answer 4

Each participant all levels of the independent variable
Dependent variable is measured at every level

Question 5

Between Subjects/Independent Groups Designs

Answer 5

Comparing measures two groups

Question 6

Within Subject Counterbalancing

Answer 6

Everyone does all possible orders, just in different order;

Question 7

2 x 2 Between-Subjects Factorial Design

Answer 7

= 2 Independent Variables, 2 Levels of Variables, 4 Groups

Question 8

Confirmatory Hypotheses:

Answer 8

researcher specifies what they expect to find

Question 9

Exploratory Hypotheses:

Answer 9

researcher does not specify what results will be found

Question 10

Directional Hypotheses:

Answer 10

you specify what the EXACT effect will be

Question 11

Interaction Effect:

Answer 11

combined effects of the multiple independent variables; (an effect of one independent variable on the dependent variable depending on the level of the other independent variable)

Question 12

Main Effect:

Answer 12

when we isolate the effect of one of the predictors and see what it did (if you wanted to compare playing games for 3 hrs with playing games for 6hrs and ignore the type of game completely DIFFERENCE BETWEEN THE TWO GROUPS

Question 13

What indicates an interaction on a graph?

Answer 13

When lines on graph cross, it is a disordinal INTERACTION, LINES CROSSING ALWAYS MEANS INTERACTION
Lines NOT parallel at any time is an INTERACTION^^^^^^^^^

Question 14

Post Hoc Tests

Answer 14

Allow Researchers to compare the means of the levels of the independent variables

Question 15

High-Order Factorial Designs

Answer 15

A design with three or more independent variables
2x2x2: 3 main effects (has three two way interactions, and one three way interactions)

Question 16

Difference between OR and AND wording when discussing groupsn

Answer 16

A design with three or more independent variables
2x2x2: 3 main effects (has three two way interactions, and one three way interactions)

Question 17

What do Two flat parallel lines indicate on a graph?

Answer 17

one main effect

Question 18

What do two lines overlapping flat mean

Answer 18

Lines are overlapping flat: no main effect

Question 19

What does “factorial” imply?

Answer 19

MORE THAN ONE INDEPENDENT VARIABLe, o

Question 20

What is an ABAB design?

Answer 20

The ABAB design is also known as a time-series design or reversal design. In our imaginary experiment, an ABAB-design study will include: A—Baseline measurements of correct responses. B—Measurement of correct responses during intervention X. A—Baseline measurements of correct responses after intervention X is removed.

Question 21

What is an ABA design?

Answer 21

The A-B-A design, which is also called the ABA design, is a method of behavioral intervention often used in Applied Behavior Analysis. This design utilizes a three-stage process that includes baseline measurement (A), treatment (B), and withdrawal (A).

Question 22

AB design

Answer 22

A-B. An AB design is a two-part or phase design composed of a baseline (“A” phase) with no changes and a treatment or intervention (“B”) phase

Question 23

Difference between multiple baseline design and reversal design

Answer 23

While reversal designs can be used to compare effects of interventions, multiple baseline designs provide experimental control for testing one intervention but do not compare different interventions.