Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

Dats great > Final exam questions > Flashcards

Final exam questions Flashcards

1
Q

In a 2-way within-subjects ANOVA, there are n participants. ______

A

True.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

In a 2-way mixed-factors ANOVA where A is the within-subjects factor, there are a  n participants. ______

A

False

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

For a 2-way within-subjects ANOVA, the main effects of the treatments and the interaction are all tested using different MSError terms. ______

A

True

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

For a 2-way mixed-factors ANOVA, the main effects of the treatments and the interaction are all tested using different MSError terms. ______

A

False

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

The maximum value of eta^2 is ∞. ______

A

False

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

For treatment A in a 2-way design, the value of partial eta^2A is always greater than or equal to the value of eta^2A. ______

A

True

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

For a 1-way design, the value of eta^2 does not depend on whether you perform a within-subjects or between-subjects analysis. ______

A

True

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

A small Cohen’s effect size, f, for an ANOVA means that the null hypothesis will fail to be rejected. ______

A

False

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

9) ANOVA is robust to violations of homogeneity of variance so long as the design is balanced. ______

A

True

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

In a 1-way within-subjects analysis, if n = 8 then dfSubjects = 7. ______

A

True

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

In a 1-way within-subjects analysis, if N = 32 and you find F(3,21) = 3.12 then n = 11. ______

A

False

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

n^2 and r^2 are similar in that they both range between 0 and 1.

A

True

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

for a simple ANOVA, the df between is:

A

k-1

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

for a simple ANOVA, the df within is:

A

N-k

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

MS is…?

A

sums of squares of variance

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Xji is such that j refers to

A

the order of group overall/level

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Xji is such that i refers to

A

the order of the individual observation in a group

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

what is the structural model?

A

a method to decipher the individual sample as a part of an ANOVA, as it differs from the local treatment as well as the mean of all observations

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

what is the process by which all treatment means depart from a so-called grand mean?

A

centering

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

what are all treatment means departing from when compared to the mean of all observations?

A

the grand mean

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

once the data are centred, what can the structural model be viewed as accounting of?

A

why any observation deviates from the ground mean

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

what is the structural model for ANOVA composed of?

A

the total deviation of an observation from the grand mean which equals
the component of the deviation that is due to treatment differences, plus
the component of the deviation that cannot be accounted for by treatment differences

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

for the structural model, what does the total deviation from the mean look like between levels?

A

a bell curve on the left has its datapoint reaching as far to the centre mean/grand mean

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

for the structural model, what does the ERROR/within deviation from the mean look like between levels?

A

a bell curve on the left has its datapoint reaching to the centre of the LOCAL mean

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q

for the structural model, what does the TREATMENT/between deviation from the mean look like between levels?

A

a bell curve on the left and the difference between that local mean from the grand mean

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
26
Q

what are other names for treatment in the structural model?

A

the explained, or between

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
27
Q

what are other names for error in the structural model?

A

the unemplained or within

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
28
Q

What according to the structural model describes a treatment effect?

A

the between component (or “group” or “treatment” or “explained” component”) expresses the extent to which treatment j shifts the mean of its population from the overall mean

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
29
Q

What would the structural model characterize as the “sums of squares”?

A

the sums and then squared of the individual deviations of observations in each sample in the dataset from the overall mean

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
30
Q

What would the structural model characterize as the F-ratio?

A

the between variance from the mean over the within variance from the mean

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
31
Q

What does ANOVA terminology call a variance?

A

“mean squares”

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
32
Q

What are the degrees of freedom for dftotal for a 1-way anova?

A

dftotal = total numbers of observations minus 1, or N - 1

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
33
Q

What are the degrees of freedom for dftbetween for a 1-way anova?

A

dfbetween = # of groups/levels/treatments minus 1, or k - 1

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
34
Q

What are the degrees of freedom for dfwithin for a 1-way anova?

A

dfwithin = dftotal - dfbetween

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
35
Q

What is the structural model for a 1-way ANOVA?

A

(Xji-u) = Tj + Eji

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
36
Q

According to the structural model, what is the ANOVA ratio, or F?

A

the ratio of MS estimates of the variance in the population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
37
Q

What are the degrees of freedom for error in a 1-way ANOVA?

A

dferror = k(n-1); OR….dftotal - dftreatment

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
38
Q

Do degrees of freedom depend on experimental results in a 1-way ANOVA?

A

No

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
39
Q

What is the formula for MS in the ANOVA table?

A

Respective SS/respective df = same MS

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
40
Q

What is a general term for ANOVA designs with more than 1 independent variable?

A

a multi-way ANOVA

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
41
Q

Are treatments/factors determined randomly?

A

Not necessarily. Such can include gender, which is inherent to the participant and not malleable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
42
Q

What are the different categories of eacah treatment called?

A

levels

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
43
Q

What is a key attribute of a design having multiple independent variables?

A

multiple treatments are applied simultaneously

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
44
Q

How does a multiple anova differ in tabling data?

A 
1-way = k = # of treatments
2-way = a for 1st level, b for 2nd level, etc. (axb)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
45
Q

if you have 2 levels of treatment a, and 3 levels of treatment b, what would you label individual datapoints?

A

xa,b,order in group

e.g. item 4 in level a2 b3 would be X234

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
46
Q

What is each particular combination of treatment levels within the design for a multiple ANOVA design called?

A

a cell

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
47
Q

Why do observations within a cell differ?

A

Solely due to experimental error

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
48
Q

What is the cell mean?

A

The mean of all observations within a particular cell, similar to the treatment means for 1-way ANOVA design

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
49
Q

What is the formula for number of observations in a multiple ANOVA design?

A

N = sum (nkj);

if 2-way, axbxn

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
50
Q

What are designs where all the cells have observations?

A

a factorial design; if all the same, a balanced factorial design

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
51
Q

How would you indicate a test for a ___ effect in a multiple ANOVA?

A

The simple effect of IV1 on DV, for IV2 level 2 (e.g. the simple effect of intervention on stress for/at females (from gender)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
52
Q

What kind of test can follow those for simple effects?

A

pairwise comparisons (or multiple pairwise comparison t-tests)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
53
Q

How would you plot a simple effect of B on A1 or A2?

A

You would likely plot an interaction plot with the levels of B on the horizontal axis, the interval amount for DV on the horizontal axis, and then 2 lines both indicating points for A1 and another for A2 to signify the simple effect of B on each of them at different levels of B

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
54
Q

After you plot a simple effect, are you done?

A

No! a t-test needs to be determined in order to assess whether it is significant; at present it is simply a visual analysis

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
55
Q

How many possible simple effects can be investigated using an a x b factorial ANOVA?

A

a + b possible simple effects

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
56
Q

What do you typically consider main effect?

A

collapsing across levels of a variable in an effect; the effect of IV1 on DV (with no mention of IVx anywhere)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
57
Q

What do you calculate when you collapse across means in the margins of a 2-way table in order to calculate the means necessary for examining the main effect of one fof the IVs?

A

the marginal means

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
58
Q

Is it possible to have a main effect for one IV but not the other?

A

yes

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
59
Q

What is the best order to assess effects?

A

interaction, simple and then (if applicable), main

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
60
Q

What is another way of indicating an interaction?

A

a modulation of the simple effects of IV2 by the variable IV1

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
61
Q

What are 2 points about interaction effects?

A

1 - the lines in an interaction plot DO NOT need to cross for an interaction to be present
2 - the lines in an interaction plot may be nonparalleld due only to sampling variability, i.e., there is no real interaction only an apparent one due to sampling variability

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
62
Q

Is it possible for an interaction to be present even if neither variable exhibits a main effect?

A

Yes. It can simply be interactions masking main effects

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
63
Q

Analyses in which there is only 1 DV are called “” analyses

A

“univariate”

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
64
Q

What is the structural model formula for a 2-way ANOVA?

A

Xkji - u = ak + Bj + aBkj+Ekji , or Xkji - u = Tkj + Ekji; ak = effect of treatment a; Bj = effect of treatment B; aBkj = effect of a x b interaction

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
65
Q

What do the terms in the structural model form?

A

the various sum-of-squares used in a 2-way ANOVA; Xkji - u = SStotal; ak = SSa; Bj = SSB; aBkj = SSaxb; Ekji = SSerror

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
66
Q

For the Eysenck example of age x instruction on time(?), what would be on the ANOVA table?

A 
Source would have:
age/a
instruction/b
age x instruction/axb
error/E
total
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
67
Q

What are the degrees of freedom for ak or Bj (main effects) in the ANOVA table?

A

k - 1

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
68
Q

What is the df for an interaction in the ANOVA table?

A

product of all df for main effects: dfa x dfb (NOT ka x kb)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
69
Q

What is used to form all F-ratios in a 2-way ANOVA?

A

the MSerror, which estimates the within estimate of population variance

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
70
Q

What do each of the F-ratios in a 2-way ANOVA test?

A

either a main effect or an interaction effect

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
71
Q

what is the structural model of overall effect?

A

Xkji - u = Tkj + Ekji; you would calculate the SSexplained by adding all of the SSmain and interaction effects together, , or you can take the SStotal and substract the SSerror to get the explained total. You can also for df take the dftotal and subtract the dferror to get the dfexplained…you are ignoring the a, b, and axb levels in favour of aggregating them…and the MSexplained can be done by SSexplained/dfexplained= MSexplained

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
72
Q

What is the explained model entry called in SPSS?

A

the “corrected model” entry

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
73
Q

what are two measurements of effect size for ANOVA?

A

Cohen’s f, and n^2 (similar to r^2, a popular regression technique)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
74
Q

What are the properties for effect sizes in ANOVA?

A
  • hey don’t depend on measurement scales
  • they don’t depend on sample size
  • they don’t depend on arbitrary choices made to increase statistical power (e.g. creating a larger alpha)
  • they are useful in meta-analysis
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
75
Q

What does n^2 refer to?

A

magnitude of the effect, or proportion of explained variation in dependent variable values that is associated with differences in the independent variable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
76
Q

How is n^2 pronounced?

A

eta squared

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
77
Q

What is the 1-way ANOVA magnitude of the effect formula?

A

n^2 = SStreatment/SStotal

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
78
Q

What does the value of n^2 always lie between?

A

0 and 1 (it’s a proportion, therefore a fraction of a total, i.e. 1)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
79
Q

What is eta squared according to the null hypothesis?

A

n^2 = 0

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
80
Q

What also does the magnitude of the effect measure?

A

the importance of the effect (e.g. an effect may be significant, but is it important?)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
81
Q

Again, what is the formula for magnitude of the effect for 1-way ANOVA?

A

SStreatment (or SS explained) / SStotal

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
82
Q

what does SPSS call leta squared or n^2?

A

R squared, since it works like the r^2 in regression problems

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
83
Q

What is another way of indicating that the ANOVA tests the null hypothesis such that n^2 = 0?

A

the null hypothesis consists of saying that differences in treatment do not explain any of the variation in the dependent variable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
84
Q

Is eta squared a biased or unbiased estimator of the true proportion of variance?

A

biased

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
85
Q

Why is eta squared a biased estimator of the true proportion of variance?

A

it overshoots the mark when attempting to explain how treatments affect a population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
86
Q

What is an unbiased estimator for the proportion of explained variation in the population?

A

quantity, or “adjusted R squared”; the formula for 1-way anova is =
sStreatment = (k1) MSerror/
(SStotal + MSerror)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
87
Q

How do you calculate eta squared for 2-way ANOVA?

A

SEPARATE N^2 FOR EACH FACTOR/VARIABLE (a, b, and axb):

Na^2 = SSa/SStotal

Nb^2 = SSb/SStotal

Naxb^2 = SSaxb/SStotal

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
88
Q

What is the value for each eta squared calculation for each variable of a two-way anova?

A

Each one befit a proportion, therefore each one has a value that is between 0 and 1

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
89
Q

How is n^2 interpreted for a 2-way anova?

A

a proportion of the overall variation in the DEPENDENT variable that is explained by differences in a FACTOR (or interaction)

90
Q

Where does SPSS indicate the R squared calculation in the 2-way ANOVA table?

A

the bottom left portion of the screen

e.g. R Squared = .729 (Adjusted R Squared = .702

91
Q

What is the Adjusted R Squared the same as?

A

oo^2 symbol, which is the UNBIASED counterpart of the overall eta squared value

92
Q

How is Cohen’s f calculated?

A

it is the standard error of the mean DIVIDED BY pooled standard deviation over all k treatment conditions, OR

f = Sm/Spooled

93
Q

What is a shortcut to determinee Cohen’s f for a 2-way ANOVA?

A

f = square root of(SStreatment/SSerror), with a result that is between 0 and INFINITY

94
Q

What are the equivalent effect sizes for Cohen’s f vs Cohen’s d (small, medium, large)?

A

S - Cohen’s d 0.2, f 0.1
M - Cohen’s d 0.5, f 0.25
L - Cohen’s d 0.8, f 0.4
EFFECT SIZES OF D ARE HALVED TO MAKE F!!!

95
Q

What formula using Cohen’s f makes eta squared?

A

n^2 = f^2/(1+f^2)

96
Q

What formula using eta squared makes Cohen’s f?

A

f = square root of(eta squared/(1-eta squared))

97
Q

What are the equivalent effect sizes for Cohen’s d, f, and eta squared?

A

S - Cohen’s d 0.2, f 0.1, eta squared .01
M - Cohen’s d 0.5, f 0.25, eta squared .06
L - Cohen’s d 0.8, f 0.4 ], eta squared .14
EFFECT SIZES OF D ARE HALVED TO MAKE F!!!
It’s not as simple for eta-squared; memorize! (TREAT THESE SIZES AS PERCENTAGES %%%%%%%%%%%%%)

98
Q

How many Cohen’s effect sizes are there for a 2-way ANOVA?

A

1 for each factor/interaction, therefore 3 (Fa, Fb, and Faxb)

99
Q

What is the formula for calculating Cohen’s f for the effect size of variable a?

A

Fa = square root of (SSa/SSerror)

100
Q

What is the formula for calculating Cohen’s f for the effect size of variable b?

A

Fb = square root of (SSb/SSerror)

101
Q

What is the formula for calculating Cohen’s f for the effect size of the interaction in a 2-way ANOVA?

A

Faxb = square root of (SSaxb/SSerror)

102
Q

Why do we calculate partial eta squared calculations for Cohen’s f?

A

Because there is not a direct relationship between Fa and n^2a, so we say it is n^2a partial to then calculate Cohen’s f for individual factors in 2-way ANOVA

103
Q

what names can we use for the cousin of eta squared as related to Cohen’s f?

A

partial eta squared, or eta squared partial

104
Q

How do we calculate treatment A in a 2-way design for eta-squared a partial?

A

N^2a,partial = (SSa/SSa+SSerror)

105
Q

What elements do we eliminate when calculating n^2a,partial in the formula?

A

SSb, and SSaxb, because we assume they have no effect (H0 = 0), therefore we can take them out of the equation

106
Q

How can you interpret partial eta squared for level a for a 2-way ANOVA?

A

the proportion of variation in the dependent variable that would be explained by differences in factor A, IF treatment B has been held steady at a single value (remained consistent) through the entire experiment

107
Q

How else would you call in a 2-way ANOVA calculating the proportion of variation that would be explained by one treatment A when Treatment B is held steady?

A

partialling out the effect of B!!!!!!!!!!!!!!!!!

108
Q

Is there a distinction between eta squared partial and eta squared in a 1-way ANOVA?

A

No

109
Q

Are there partial eta squared values for all factors and interactions in a 2-way design?

A

yes

110
Q

What values ar directly related to Cohen’s f in a 2-way ANOVA?

A

PARTIAL ETA SQUARED VALUES (REGULAR ONES ARE ONLY DIRECTLY RELATED TO COHEN’S F IN A 1-WAY ANOVA)

111
Q

What type of estimates of effect size does SPSS calculate in a 2-way ANOVA?

A

IT PROVIDES PARTIAL ETA SQUARED VALUES FOR INDIVIDUAL FACTORS, NOT REGULAR ETA SQUARED VALUES

112
Q

Does SPSS calculate the eta squared values for a, b, and axb in a 2-way ANOVA table?

A

No. It only calculates partial eta squared values for individual factors, and they can be placed on the right column of the table

113
Q

What does SPSS characterize SStotal as in a 2-way output table?

A

SSCORRECTED TOTAL

114
Q

For a 2-way ANOVA test, what does a higher non-centrality parameter measurement equal?

A

higher power!

115
Q

If you have a big sample and power, is the non-centrality parameter likely high or low?

A

High

116
Q

What helps ensure a high non-centrality parameter for a two-way ANOVA design?

A

a bigger sample, and high power, and a smaller SSerror

117
Q

how do you calculate power?

A

by calculating the noncentrality parameter

118
Q

What is the formula for a 1-way ANOVA for the noncentrality parameter?

A

h = f^2N

119
Q

What is another method to calculate h or noncentrality parameter for a 1-way ANOVA?

A

h = SStreatment/SSerror * N, therefore sample size affects the size of the noncentrality parameter

120
Q

What is the noncentrality parameter?

A

The noncentrality parameter is just a one-number summary that serves as a single overall measure of difference. It gives us a simple way to form a test for any differences between any of the group means

121
Q

How is the noncentrality parameter for 2-way ANOVA calculated

A

Actually, there is a noncentrality parameter for each factor/interaction of a 2-way anova, so there are THREE calculations:

ha = Fa^2N = SSa/SSerror * N

hb - Fa^2N = SSb/SSerror * N

h

122
Q

What is another name for the SSerror for a 2-way analysis?

A

residual error

123
Q

Why is it more advantageous to use a 2-way analysis instead of a 1-way?

A

it tends to create a smaller residual error because more of the unexplained variation is thereby explained in the new variable that is introduced, as well as a potential interaction between the new and old variable in the 1-way ANOVA design

124
Q

What has more power, a 2-way anova or a 1-way anova?

A

2-way, because it explains more of the variation than the 1-way, UNLESS the second variable does not appear to make a difference, or its interaction, which would make it even weaker than the 1-way variable (the larger the SSerror, the greater the likelihood of more power, a higher noncentrality parameter, and perhaps even a greater likelihood of significance and even importance; also, an ineffective nuisance variable creates a lower degrees of freedom which raises the amount of MSE to then calculate the F-statistic)

125
Q

What kind of variable is often used to simply get rid of some extra residual error in a multiple anova design?

A

a nuisance variable

126
Q

what do we consider a dependent-groups ANOVA?

A

when observations in different treatment groups are correlated, such as when we have the same participants appear in the different treatment groups (it is then a dependent-measures design in general, and for this specific method it is a repeated measures design)

127
Q

How do you calculate N for a balanced 2-way factorial design?

A

N = a x b x n

128
Q

How do you calculate N for a balanced 1-way design?

A

N = k x n

129
Q

what is the formula for a paired-samples t-test?

A

t = Md / (Sd x square root of (1/n))

130
Q

As the correlation between samples grows larger (whether due to being from the same participants, or a personality trait having similar components), what happens to the noncentrality parameter?

A

it gets larger (closer to 1, from 0)

131
Q

How does a dependent-groups design affect the F-statistic?

A

it typically creates a smaller “within variance” from which to calculate the F-statistic

132
Q

How do you assess how a repeated-measures ANOVA works to remove the effects of individual differences?

A

1 analyze the data as thought we did not realize it was a repeated measure (i.e. looking at SStotal = SStreatment + SSerror ONLY)
2 reanalyze the data using repeated-measures techniques

133
Q

Do we encode individual differences if they are stable or unstable?

A

Stable. If they are consistent regardless of the treatment, then are inherent to the individual, and we can theoretically “throw them out” in order to concentrate on the effect of the treatment/s. Otherwise, by focusing on the individual differences, we have included a new independent variable: THE SUBJECT HER/HIMSELF

134
Q

In order to “weed out” individual differences, what would the new structural model look like?

A

Xji - u = Ti + (pi)i + Eji

OR…

SStotal = SStreatments + SSsubjects + SSerror

135
Q

What does a repeated measures ANOVA table look like?

A

Source has under it: Treatment, Subject, Error, and Total.

136
Q

What changes when you change a design from 1-way to a repeated measures ANOvA?

A

the treatment values for SS remains the same, but that for subject, and error (MSE) differs, totalling the SAME as the 1-way
…
SIMPLY CALCULATE THE INCLUSION OF SUBJECT AND CHANGE THE AMOUNT OF ERROR THAT RESULTS, HOWEVER EVERYTHING ELSE SHOULD BE THE SAME, APART FROM THE RESULTING F-STATISTIC

137
Q

What does SSerror split off into from a 2-way anova to a repeated measures ANOVA?

A

SSerror (Under source, called Error) becomes SS subjects (or Subjects) and SS error (*New Error)

138
Q

How do you calculate the (pi)i (individual difference) measure?

A

estimated by measuring the deviation of subject mean from the grand meant
…
(pi)i = Msubject,i = M…
…
Taking the subject means and subtracting the grand mean from it…or the marginal means for the individual subject, minus the grand mean for all of the subject/marginal means calculated

139
Q

What do you calculate to get SSsubjects in a repeated-measures ANOVA?

A

each (pi)i term squared, and then added together
(sums of squares for the subjects in order to “get rid of them” to see what JUST THE TREATMENT shows an effect, not the individuals themselves, creating a very sophisticated design)

140
Q

Again, what is the results table for a 2-way repeated-measures design?

A 
Source has:
Subjects
Variable A -- F-statistic is noted here because this is the variable that we want to study, NOT THE SUBJECTS
Error
Total
141
Q

A treatment effect that is measured WITHIN individuals is called a

A

within-subjects effect (we are dealing with individual subjects, NOT GROUPS)

142
Q

A treatment effect that is measured BETWEEN individuals is called a

A

between-subjects effect (we are dealing with individual subjects, NOT GROUPS)

143
Q

Since we are dealing with differences between and within subjects, what is another way of writing the results for a 2-way repeated-measures ANOVA?

A 
Source:
Between subjects
Error ---
Within Subjects
Weeks---
Error---
Total
144
Q

Again, to delete out individual differences, what are they required to be ?

A

Stable, otherwise we cannot determine if it is in fact due to individual differences

145
Q

How else can we characterize residual error in a repeated-measures design?

A

the residual errors can be seen as the TreatmentXsubjects interaction (subjects being a nuisance-like variable)

146
Q

How else can within subjects error be labelled as in a repeated-measures design?

A 
treatmentXsubjects interaction...
...
Source
Between
   subjects
Within 
   Treatment
   Treatment x subjects (ERROR)
Total
147
Q

What is the df for within error?

A

df treatment x df subjects (k-1) x (n-1)

148
Q

What is a mixed design?

A

a 2-way design wih 1 within-subjects variable and 1 between-subjects variable, just to confuse the F out of me

149
Q

How would you plot out a mixed design that is 2 x 3 with fact A between, and factor B within?

A

B
A G1 G1 G1
G2 G2 G2

150
Q

How many participants are in a mixed design that is 2 x 3 with fact A between, and factor B within?

A

between variable/a x n participants (there are 2 groups for a, whereas it’s the same group for b levels)

151
Q

How would you write out the structural model for a mixed design ANOVA, with 1 within-subjects variable and 1 between-subjects variable?

A

Xkji - u = ak + Bj + aBkj + ((pi)ki + Ekji)
…
it is the same as a 2-way between-subjects (independent) structural model with a new term, (pi)ki added.
…
this shows an interaction between the within-subjects variable B and subjects?????
…
Most importantly, it ciphons off the between-subjects error and the within-subjects (residual) error = total error in parentheses… so what you’re really looking at is

Subject datapoint = main effectA + main effect B + interaction effect AxB + total error (between-subjects and within-subjects)

152
Q

How many sums-of-squares calculations are expected in a mixed design ANOVA with 1 within and 1 between?

A 
5, PLUS SS total = 6
Source
Between subjects ------------------------------------------------------
A 
Subjects (error)
Within subjects ----------------------------------------------------------
B 
B x A (interaction)
B x subjects (error)
Total
153
Q

What levels do we indicate a F-statistic for in a mixed design ANOVA with 1 W and 1 B?

A

Between Variable A (main effect)
Within Variable B (main effect)
Within Variable B x A (interaction)

154
Q

How do you calculate the df for a mixed design ANOVA table with 1 B and 1 W?

A 
Source 
Between
A = kA -1
Subjects = total participants -1) -dfa
Within 
B = kB - 1 
B x A = (dfB) x (dfA)
B x subjects = (dfB) x (dfBetweensubjects--listed above)
Total = add everything together, or N-1
155
Q

What does an ANOVA results table look like for a 2 within-subjects ANOVA design?

A 
Source 
Between
Error
Within
A (stays the same between designs)
ErrorA
B *stays the same between designs
ErrorB
AxB (stays the same between designs)
ErrorAxB
... 
Each effect (2 main, 1 interaction) has their OWN ERROR term, which is used to calculate their SEPARATE MSerror for the F-stat, instead of the "within error" source in a mixed or a standard repeated-measures design
156
Q

What is the rule for calculating the between-subjects vs. within-subjects?

A

For between subjects, all effects tested use the SAME MSE (in order to create some structure amongst different variables)
…
For within subjects, all effects tested use their OWN MSE (in order to create some variability amongst the same participant group)

157
Q

What is a rule for the analysis of multiple within-subjects variables?

A

for any WITHIN subjects effect, the appropriate SSerror is SSeffectxsubjects (for instance, to test for the main effect of A, use SSaxsubjects

158
Q

What is another way of plotting a 2-within subjects ANOVA table?

A 
Source
Between
   Subjects
Within
   A        SSa      dfa     MSa     MSa/MSaxs
   AxS     SSaxs     dfaxs     MSaxs    ------
   B
   BxS
   AxB
   AxBxS
159
Q

What is a formula for looking at the SStotal error for a 2 within-subjects variables design?

A

SS total error = SSsubjects + SSaxs + SSbxs + SSaxbxs
…
we want to delete all of this error in order to concentrate on simply the effect of the treatments, which we create F-statistics for. The data (except for the F stats) should not change for that of the treatment variables or the Source total; only the errors would be modified

160
Q

What is a rule for analysis of multiple WITHIN-subjects variables?

A

for any within-subjects effect, the appropriate SSerror is SSeffect x subjects (for instance, to test for the main effect of A use SSaxsubjects)

161
Q

What are the assumptions for ANOVA?

A

That the population is normal, the distributions of errors for each treatment are indicative of that from the same population, and that each participant is independent/individual of each other within a treatment

162
Q

If violated, what could be a result of an assumption of ANOVA not fulfilled?

A

the result is losing control over the rate of Type I errors; it may be much larger than we think it is

163
Q

When is ANOVA robust from Type I errors?

A
  • violations of normality (only slightly affected if n < 30)
  • if the design is BALANCED
  • errors WITHIN a treatment group are INDEPENDENT of each other
164
Q

When is ANOVA NOT robust from Type I errors?

A
  • if the populations from which the samples are drawn are ALL significantly skewed in the SAME direction
  • if the design is UNBALANCED
  • errors WITHIN a treatment group are DEPENDENT on one another
165
Q

What should be done if samples are skewed in the same direction?

A

consider a transformation, using SPSS

166
Q

What is actually tested using ANOVA re HoV?

A

if the treatment populations all have the same variance, and if they are all normally distributed as we also assume, then the ONLY way left for them to differ is in the values of their treatment means

167
Q

How do you test ANOVA for homogeneity of variance?

A

Using Levene’s test! If the result is not significant, then use data as originally intended. If not, use the modified Welch’s test (“equal variance is NOT assumed” row of SPSS)

168
Q

What kind of plot do you refer to when a treatment group in an ANOVA design is dependent of another?

A

a lag plot, in which the observations Xi in a group are plotted against their neighbours Xi+1.

169
Q

What does a lag plot usually look like?

A

a structureless cloud

170
Q

When are violations of assumption for ANOVA serious?

A

when using an unbalanced design, and when the observations are NOT independent (this does not refer to repeated participants…this means that another factor ties them together in which would not easily be noticeable in an ANOVA design)

171
Q

When referring to repeated measures design, what is another assumption of ANOVA?

A

that not only is HoV maintained, but that covariances (similar to correlations) of DEPENDENT-variable values are the SAME between every pair of cells

172
Q

What does it mean when covariances of dependent-variable values are the same between every pair of cells in a repeated-measures ANOVA?

A

compound symmetry, or sphericity

173
Q

What is compound symmetry?

A

when the covariances (similar to the correlations) of dependent-variable values are the same between every pair of cells (a.k.a. sphericity) in a repeated measures design

174
Q

What is sphericity?

A

when the covariances (similar to the correlations) of dependent-variable values are the same between every pair of cells (a.k.a. compound symmetry) in a repeated measures design

175
Q

What do we use to calculate HoV in a 1-way repeated measures design?

A

a variance-covariance matrix
…
the diagonals give the variances at each treatment level and the off-diagonals give the covariances between treatment levels (covij = covji so the upper part of the matrix is not written down)

var11
cov21 var22
cov31 cov32 var33
cov41 cov42 cov43 var44

176
Q

How do you determine sphericity?

A

if the order of subjects along different treatment levels is consistent throughout the experiment

177
Q

What does the assumption of sphericity mean?

A

that the deviations of subject means from the grand mean represent the variation due to individual differences

178
Q

What test do you use to test for sphericity AND homogeneity of variance?

A

Mauchley’s test

179
Q

What conditions can you only use Mauchley’s test for?

A

WITHIN-subjects variables that have 3 or more levels

180
Q

Can you use Mauchley’s test for a between-subjects design?

A

No

181
Q

Can you use Mauchleys’ test for a mixed design with 2 levels of within-subjects?

A

no, use Levene’s since determining between two levels doesn’t make a big difference

182
Q

Are violations of sphericity common?

A

Yes, it’s sometimes hard to detect changes between subjects.

183
Q

What does E stand for in the structural model?

A

epsilon, a measure of how far the data depart from sphericity

184
Q

What does epsilon measure in a repeated measures design?

A

how far the data depart from sphericity…needs to be in a repeated measures design

185
Q

What should you do if Mauchley’s test is significantly smaller than 1?

A

use an alternative to the usual within-subects ANOVA that has a reduced number of degrees of freedom to preserve the Type I error rate. This is so that you can allot for changes of individual differences throughout the exam

186
Q

What are alternate procedures in SPSS for sphericity?

A

Greenhouse-Geisser

187
Q

Why is using the Huynh-Feldt procedure more preferred than the Greenhouse-Geisser test, even though the latter is traditionally used most often for tests of sphericity?

A

it tends to give up less power

188
Q

If Mauchley’s test isn’t passed, what do you do?

A

Ues either the G-G or the H-F tests for the appropriate df to get the SAME F and significance level (controls for more error to make sure the info is more accurate)

189
Q

How do you calculate n^2 (proportion of variance explained by the treatment)?

A

Usually it’s SStreatment tested over SStotal

190
Q

What is ANOVA a test of?

A

The means

191
Q

What do all ANOVA designs presuppose?

A

a single dependent variable that is at least interval in nature (so that you can calculate the means) and one or more categorical independent variable

192
Q

When would you not use an ANOVA?

A

you’d use an analog design if the iV is interval or better, or you would if the ANOVA violated tests of HoV, sphericity, balance, etc.

193
Q

What is higher power: ANOVA or analog designs?

A

ANOVA designs, IF assumptions of HoV and normalcy and independence of participants are met)

194
Q

What test would you use for 1 IV with 2 or more levels?

A

a one-way ANOVA

195
Q

What test would you use for ordinal or interval IVs for 2 or mroe levels?

A

Kruskal Wallis

196
Q

What test would you use for categorical IVs for 2 or mroe levels

A

chi-squared test

197
Q

What are examples of ordinal data?

A

rank in the army, grades (letter), etc.

198
Q

What are examples of categorical data?

A

pass or fail an exam, gender, etc.

199
Q

What are examples of interval data?

A

temperature levels

200
Q

What are examples of ratio data?

A

weight scales

201
Q

What is the Kruskal-Wallis test?

A

it’s a DV (ordinal) and IV (categorical) design, with RANK scores given for each observation, and teh mean rank score is calculated in teach group

202
Q

What stats are used for the Kruskal-Wallis test?

A

H or K, giving a x^2 distribution if all the samples come from the same population

203
Q

What are tests that do not require normal distribution

A

nonparametric or distribution-free

204
Q

What is another name for the Mann-Whitney test?

A

Wilcoxon test, a nonparametric analog test for the independent-samples t-test

205
Q

What test do you use for a nonparametric, 1-way WITHIN-subjects test with an ordinal DV?

A

Friedman’s test

206
Q

What is a dichotomous variable?

A

one that we can’t calculate means, therefore calculate proportions

207
Q

What analog test do you use to test 1 iv with 2 or more levels that are CATEGORICAL?

A

x^2/chi squared test of independence (proportionality, like percent extro or introvert and colour test)

208
Q

What is another name for the chi squared test?

A

the x^2 test of independence

209
Q

Are there nonparametric tests for all ANOVA designs?

A

yes

210
Q

What are the advantages of nonparametric analog tests?

A

they do not require assumptions of normality, and do nto have to always test for the mean

211
Q

What is an advantage of using an ANOVA over a nonparametric analog?

A

more power

212
Q

What kinds of tests are best for interval x interval design tests?

A

correlation and regression tables

213
Q

Are correlation or regression tables in a different order?

A

Yes, which is the main advantage over ANOVA design, albeit we would get the same results for both in either design

214
Q

What if in a regression or correlation table there IS an important order required for the data?

A

then a straight line would go through it to determine the equal intervals in x are associated with equal intervals in yk

215
Q

what do you call the line representing the regression onf Y on x in a regression table?

A

a PREDICTION

216
Q

What does the regression line always include?

A 
the mean (Mx, My) of ALL DATA POINTS 
...
Y = a + bX
...
(a = value of Y when X is p)
(b = slope of the line)
217
Q

In a regression table, if b is zero, then what can be said about the relationship?

A

x and y are not connected with each other in any way

218
Q

What dos the regression line in a regression table do?

A
  • it shows the part of the overall variation in Y that is explained by differences in X
  • it maximizes explained variation in Y
219
Q

What kind of test is it for b in a regression table?

Y = a + bX

A

a t-test

220
Q

What to study for ANOVA tables in the exam

A

1-way within-subjects design, and 2-way within- and 2-way between-subject designs, as well as mixed designs

Dats great (26 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions