Ch.6 Independent Groups Design

Question 1

Internal validity

Answer 1

an experiment has internal validity when we can state confidently that the independent variable caused differences between groups on the dependent variable (a causal inference)

Question 2

Three conditions for casual inference

Answer 2

covariation, time-order relationship, elimination of plausible alternative causes

Question 3

Covariation

Answer 3

relationship between IV and DV

Question 4

Time-order relationship

Answer 4

presumed cause precedes the effect

Question 5

Elimination of plausible alternative causes

Answer 5

use control techniques to eliminate other explanations

Question 6

Control techniques

Answer 6

with proper use of control techniques, an experiment has internal validity by eliminating alternative explanations

Question 7

Holding conditions constant

Answer 7

the only thing we allow to vary across groups are IV conditions - everything else should be the same for the groups of the experiment

ex. how a brain area is defined, what constitutes an AUD

Question 8

Balancing

Answer 8

when things must vary across groups, make sure that they are equal on average so as to not be biased; necessary because some variables cannot be held constant

ex. individual ages, time of day the scanning is done

Question 9

Random groups designs

Answer 9

• done irrespective of the individual or time, only done in relation to the conditions
• can be done with various methods, e.g. coin flips, pulling names out of a hat, random number generating
• establishes proper time order relationships for casual inference
• balances subject characteristics
• any differences between groups on dependent variable are caused by independent variable (if no confounds)

Question 10

Block randomization

Answer 10

a “block” is a random order of all conditions in the experiment

ex. a random order of conditions A, B, C could be B C A
- 1st participant assigned to condition B
- 2nd participant - condition C
- 3rd participant - condition A

Question 11

Threats to internal validity

Answer 11

ability to make casual inferences is jeopardized when
- intact groups are used
- extraneous variables are not controlled
- selective subject lost occurs
- demand characteristics and experimenter effects are not controlled

Question 12

Intact groups

Answer 12

• these groups exist before experiment, members interact
• individuals are not randomly assigned to intact groups
• when intact groups (not individuals) are randomly assigned to conditions, subject characteristics are not balanced
• do not use intact groups for casual inference

Question 13

Extraneous variables

Answer 13

practical considerations when conducting an experiment may create confounding, i.e. if systematically different

control by balancing and holding conditions constant

Question 14

Subject loss

Answer 14

occurs when participants fail to complete an experiment

Question 15

mechanical subject loss

Answer 15

when equipment failure or experimenter error results in participant’s inability to complete experiment
- often due to chance factors so likely to occur equally across conditions
- because mechanical subject loss is unbiased, it does not threaten internal validity of experiment

Question 16

Selective subject loss

Answer 16

occurs when participants are lost differentially across conditions, some characteristic of participant is responsible for the loss, and the subject characteristic is related to the IV or DV

Question 17

Demand characteristics

Answer 17

cues participants use to guide their behavior in a study

Question 18

Placebo control group

Answer 18

used to assess whether participants’ expectancies contribute to outcome of experiment

• participants receive a placebo (inert substance), but believe they may be receiving an effective treatment

Question 19

double-blind experiment

Answer 19

procedures in which both participants and experimenters/observers are unaware of the condition being administered; controls both demand characteristics and experimenter effects

Question 20

Matched group designs

Answer 20

when random assignment is not possible because only small samples are available

Question 21

Procedure for matched groups design

Answer 21

• select matching variable (individual differences variables are characteristics of people that differ, or vary; choose matching variables related to outcome or dependent variable)
• measure variable and order individuals’ scores
• match pairs (or triples, quadruples, etc. depending on number of conditions) of identical or similar scores
• randomly assign participants within each match to the different conditions

Question 22

Important points about matching

Answer 22

• participants are matched only on the matching variable
• participants across conditions may differ on other important variables
• these differences may be alternative explanations for study’s results (confounding)
• the more characteristics a researcher tries to match, the harder it will be to match

Question 23

Natural groups designs

Answer 23

psychologists’ questions often ask about how individuals differ, and how these individual differences are related to important outcomes
- grouping based on subject characteristics, so group membership exists prior to the start of the study
- when a researcher investigates an independent variable in which the groups (conditions) are formed naturally
- individual differences (subject) variables
- allow researchers to describe and predict relationships among individual differences variables and outcomes; do not allow them to make casual inferences about individual differences variables

Question 24

Increasing external validity

Answer 24

• include characteristics of situations, settings, and populations to which researchers wish to generalize
• field experiments
• partial replications
• conceptual replications

Question 25

Statistical analysis

Answer 25

we rely on it to claim an independent variable produced an effect on a dependent variable and rule out the alternative explanation that chance produced differences among the groups in an experiment

Question 26

Replication

Answer 26

best way to determine whether findings are reliable; repeat experiment and see if same results are obtained

Question 27

Analysis of experimental designs

Answer 27

Check the data
- errors? outliers?
Describe the results
- descriptive statistics such as means, standard deviations
Confirm what the data reveal
- inferential statistics