Chapter 9: Within Subject Design

Question 1

within subject design

Answer 1

it uses a single group of participants and tests or observes each individual in all of the different treatments being compared. sequentially or together

Question 2

the key element

Answer 2

all the individuals in one sample participate in all of the treatment conditions

Question 3

often called as

Answer 3

repeated measures design

Question 4

it can be used in

Answer 4

experimental and nonexperimental

Question 5

threats to internal validity in within subject experiments

Answer 5

environmental variables and time related factors

Question 6

confounding from environmental variables

Answer 6

time of experiment room color etc

Question 7

confounding from time related variables

Answer 7

during the time between the first measurement and the final, the participants may be influenced by a variety of factors other than the treatments being investigated

Question 8

history

Answer 8

refers to environmental events other than the treatment that change over time and may affect the scores. events that occur in participants lives. has to be influence enough of the participants to have an effect

Question 9

maturation

Answer 9

any systematic changes in participants’ physiology or psychology that occur during a research study. young children or elderly adults

Question 10

Instrumentation

Answer 10

instrumental bias or instrumental decay refers to changes in a measuring instrument that occur over time. behavioral observation measures. dependent on the observer a people

Question 11

regression toward the mean

Answer 11

statistical regression, refers to the tendency for extreme scores on any measurement to move toward the mean, when the measurement procedure is repeated. one time it can be high score other time it probably be lower.

Question 12

order effects

Answer 12

practice fatigue and carry over effects/gaining experience etc or post experiment influence the another

Question 13

practice

Answer 13

participant gainin experience through the series of treatment condition improvement in performance

Question 14

fatigue

Answer 14

progressive decline in performance as a participant works through a series of treatment conditions

Question 15

carry over effects

Answer 15

learning new technique to memorize etc contrast effect subjective perception of a treatment condition is influenced by its contrast with the previous treatment

Question 16

notice that carry over effects

Answer 16

are caused by experiencing a specific treatment. Other order effects such as practice or fatigue, come from general experience of being in the study

Question 17

progressive error

Answer 17

refers to changes in a participant’s behavior or performance that are related to general experince in a research study but not related to a specific treatment or treatments. so that carry over effects are not included here

Question 18

time related vs order

Answer 18

time relateds are related to time and are not directly connected to experience in a previous treatment.

Question 19

dealing with time related threats and order effects

Answer 19

environmental factors can be handled by randomization holding them constant and matching across treatment conditions but time related and order effects requires special attention.

Question 20

controlling time

Answer 20

shortnening the time between treatments can reduce the risk of time related threats but this technique increases the likelihood that order effects occur

Question 21

switch between subjects design

Answer 21

in extreme cases like children etc using a between subjects design is good.

Question 22

counterbalancing: matching treatments with respect to time

Answer 22

different participants undergo the treatment conditions in different orders so that every treatment has some participants who experience the treatment first, some for whom it is second..

Question 23

counterbalancing requires separate groups of participants, with each group going through the series of treatments in different order

Answer 23

the existence of separate groups may appear contradict the basic definition. but they all recieve the full set of treatments still.

Question 24

counterbalancing is affected

Answer 24

both order effects and time related effects

Question 25

order effects can change individual scores

Answer 25

but with counterbalancing mean difference is the same.

Question 26

counterbalancing does not eliminate the order effects

Answer 26

they are still there but hidden in data so that researcher cannot see whether they exist or how large they are

Question 27

random assignment vs counterbalancing

Answer 27

one of them between one of them within

Question 28

counterbalancing and variance

Answer 28

counterbalancing adds some participants extra points in within treatment so that it can cause variance. process of counterbalancing can undermine the potential for a successful experiment

Question 29

asymmetrical order effects

Answer 29

we assume that the order effects are symmetrical. it is definetely possible that one treatment might produce more of an order effect than another treatment

Question 30

counterbalancing and the number of treatments

Answer 30

complete counterbalancing. it requires n! to do it. If 5 treatments exist, counterbalancing sequence is 120. this would require at least 120 participants. solution is partial counterbalancing

Question 31

partial counterbalancing

Answer 31

instead of every possible sequence, partial counterbalancing simply uses enough different orderings to ensure that each treatment condition occurs first in the sequence for one group of participants, occurs second for another group, so on

Question 32

latin square

Answer 32

to create a latin square for four treatments conditions start with a 4x4 matrix and fill it in with letters A B C D, list the letters ABCD in order in the top row. to create the next row, simply move the last letter in line to the beginning. DABC. CDAB so on..

Question 33

problem of latin square

Answer 33

in this method participants always face treatment B after the A. To prevent this we should use a random process to rearrange the columns

Question 34

advantages of within subjects

Answer 34

requires relatively few participants, eliminates all of the problems based on individual differences which is can be problem for between subjects in terms of confounding variable or variance. eliminates variance risk that is caused by individual differences. In statistical terms, a within subjects design is generally more powerful than a between subject design

Question 35

you cannot use equalizing process to remove the individual differences from the data in

Answer 35

between subjects design

Question 36

disatvantages of within subjects design

Answer 36

time related factors, participant attrition so that exaggerate volunteer bias, order effects.

Question 37

choosing within or between subjects design

Answer 37

1 individual differences you should choose within subject 2 time related factors and order effects you should choose between subject design 3 fewer participants you should choose within because it requires fewer participants

Question 38

matched subject designs

Answer 38

approximate the advantages of within and between using this technique. uses a separate group for each treatment condition (like between subjects) but each individual in one group is matched one to one with an individual in every other group. altough a matched subjects study does not have exactly the same participants, it does have equivalent individuals in each treatment

Question 39

the goal of matched subjects design

Answer 39

is to duplicate all the advantages of each of them. statistics that are used for matched is the same with the within subjects. removing all individual differences so that variance can be small. ALSO matched subjects design also mimics the between subjects in terms of each individual goes through each treatment once. so that time related and order effects can be eliminated. But not as effective as within subjects in terms of removing individual differences!

Question 40

two treatment designs

Answer 40

easy to conduct, results are easy to understand. maximize the treatment difference. it is easy to counterbalancing we cannot determine how the dependent variable would respond to small gradual changes of the independent variable

Question 41

in two treatment designs it is used for statistic

Answer 41

repeated measures t or single factor ANOVA. to determine whether the obtained mean difference is greater than what would be reasonably expected from sampling error. (if the data interval or ratio) if the data is nominal or ordinal a Wilcoxon Signed-Ranks test can be used.

Question 42

Multiple treatment designs

Answer 42

data are more likely to reveal the functional relationship between the two variables being studied, more convincing demonstration of a cause and effect. disadvantage is treatments may become too small to generate significant differences in behavior. time required is increased so that participant attrition more likely to increase. completely counterbalancing is requiring too much possibility and participants for multiple treatment designs.

Question 43

in Multiple treatment designs it is used for statistic

Answer 43

repeated measures ANOVA ratio or interval