1. Would you exclude any items on the questionnaire on... multicollinearity or singularity? pattern

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1. Would you exclude any items on the questionnaire on the basis of
multicollinearity or singularity?
Yes, I would delete some items one the questionnaires. According to Varimax
pattern, I would delete
(1) I could spend all day explaining statistics to people
(2) I once woke up in the middle of a vegetable patch hugging a turnip that I'd
mistakenly dug up thinking it was Roy's largest root
(3) Thinking about Bonferroni corrections gives me a tingly feeling in my groin
(4) I soil my pants with excitement at the mere mention of Factor Analysis
(5) I calculate 3 ANOVAs in my head before getting out of bed every morning
(6) I love teaching because students have to pretend to like me or they'll get bad
marks
(7) I spend lots of time helping students
(8) Helping others to understand Sums of Squares is a great feeling
By using Oblimin pattern, I would delete
(1) Thinking about Bonferroni corrections gives me a tingly feeling in my groin
Because the facts are overloading, we’d better delete these items.
2. Is the sample size adequate? Explain your answer quoting any relevant
statistics.
The sample size 239 is not adequate. At least, 300 sample size is enough.
If the sample size is not adequate, we can look at convergent validity. If the sample
size is 250, the sufficient factor loading is 0.35.
3. How many factors should be retained? Explain your answer quoting any
relevant statistics?
I think all five factors should be retained, because all of them can explain three or
more items.
Pattern Matrixa
Component
1
A-R
factor score
2
1 for
1.071
1 for
1.071
Thinking about whether to
.790
3
analysis 2
A-R
factor score
analysis 1
use repeated or independent
measures thrills me
I'd rather think about
.783
appropriate dependent
variables than go to the pub
I quiver with excitement when
.723
thinking about designing my
next experiment
I enjoy sitting in the park
.693
contemplating whether to use
participant observation in my
next experiment
Designing experiments is fun
.561
I like control conditions
.527
I could spend all day
.423
explaining statistics to people
A-R
factor score
3 for
-1.030
3 for
-1.030
analysis 2
A-R
factor score
analysis 1
I like to help students
-.735
I love teaching
-.669
Passing on knowledge is the
-.645
greatest gift you can bestow
an individual
4
5
I love teaching because
-.581
students have to pretend to
like me or they'll get bad
marks
I spend lots of time helping
-.512
students
Helping others to understand
-.497
Sums of Squares is a great
feeling
I like it when people tell me
I've helped them to
understand factor rotation
A-R
factor score
4 for
1.031
4 for
1.031
analysis 2
A-R
factor score
analysis 1
My cat is my only friend
.678
I often spend my spare time
.673
talking to the pigeons ... and
even they die of boredom
I still live with my mother and
.658
have little personal hygiene
People fall asleep as soon as
.506
I open my mouth to speak
A-R
factor score
2 for
1.058
2 for
1.058
analysis 1
A-R
factor score
analysis 2
I tried to build myself a time
.742
machine so that I could go
back to the 1930s and follow
Fisher around on my hands
and knees licking the floor on
which he'd just trodden
I memorize probability values
for the F-distribution
.650
I worship at the shrine of
.588
Pearson
I soil my pants with
.492
excitement at the mere
mention of Factor Analysis
I once woke up in the middle
.484
of a vegetable patch hugging
a turnip that I'd mistakenly
dug up thinking it was Roy's
largest root
Thinking about Bonferroni
.436
.482
corrections gives me a tingly
feeling in my groin
I calculate 3 ANOVAs in my
head before getting out of
bed every morning
A-R
factor score
5 for
1.029
5 for
1.029
analysis 1
A-R
factor score
analysis 2
Teaching others makes me
.800
want to swallow a large bottle
of bleach because the pain of
my burning oesophagus
would be light relief in
comparison
If I had a big gun I'd shoot all
.768
the students I have to teach
Standing in front of 300
people in no way makes me
lose control of my bowels
Extraction Method: Principal Component Analysis.
Rotation Method: Oblimin with Kaiser Normalization.
a. Rotation converged in 11 iterations.
.545
4. What method of rotation have you used and why?
I would choose to use Oblimin patter. Based on the “Component Plot in Rotated
Space”, the distribution can be seen clearer than Varimax Pattern.
Oblimin
Varimax
5. Which items load onto which factors? Do these factors make psychological
sense (i.e. can you name them based on the items hat load onto them?)
Factor 1 is an enthusiasm for experimental design.
Factor 2 stands for a profound love of statistics.
Factor 3 represents a love of teaching.
Factor 4 and 5 seems like the factor of a complete absence of normal interpersonal
skill.
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