This is a summary of the third-year BSc Psychology course "Applied Methods and Statistics" at Tilburg University. It includes all relevant information about the topics of the course (i.e., path analysis, factor analysis and a methodological overview).
SPURIOUS RELATIONS
⑤
#
Variable
Variable
s causes x
} × is related to
y
q g
s cause, y
-
-
- -
spurious
DIRECT AND
relationship
INDIRECT EFFECTS
Direct : Variable x causes y
⑦ -7
⑦
Indirect : Variable
Variable
x
m
causes
causes
y
m
⑦ -
② -
⑦
mediator
⑦
UNKNOWN EFFECTS
§py spurious relation
tenting
\
No statement is made about the
direction of the effect ,
I
⑦
indirect effect
↳ correlation
④ y y
RECIPROCAL EFFECTS
Variable
Variable
x
y
causes
causes
y
x
⑦ ⑦
moderator
②
CONDITIONAL EFFECTS
The size of the effect of X
L
on
of
y depends
a third
on
variable
the
.
value
⑦ →
⑦
, LECTURE I
03.10912020
FROM THEORY TO PATH DIAGRAM
F
Fr÷aaiO\
D
,
ft
ka
i .
O O
D D
'
s .
Gz
←
D
Golden rule = all variables that cause a
spurious relation between two variables with an
may
assumed causal effect between them must be included in the model
Include common causes
*
to avoid an inaccurate estimation of bi
→ we include the spurious if we have to
relation to see reject the causal
hypothesis
(i -
e .
.
be = O)
Possible
findings
•
when
testing causal hypotheses
:
bi bn
D
causal hypotheses can
only be rejected if . . .
D.
Size of spurious relation Cs) =
correlation
explained completely by spurious
→
correlation is relation
D. Two
possibilities
Size of spurious relations ) =
correlation
be O causal hypothesis rejected
→
no causal relation and
-
-
,
Size of
spurious relation Cs ) t correlation
→
There is a causal relation ,
OR
→ Not all variable that cause a
spurious relation are included in the model
, Endogenous
D
variables = a variable explained by other variables in the model
D
Exogenous variables =
a variable that is not explained in the model
United between
exogenous variables are
always included ,
even if we don't draw
them
D
Disturbance terms ( = 5 )
• 5 ( ' '
zeta
"
) represents . . .
→ Unknown variables →
endogenous
→ known variables that are omitted
→
Human unpredictability
→
Measurement variable
error in
endogenous
Bo
Disturbance terms included , if don't draw them
are
always even we
•
Assumption : disturbance terms are small ,
uncorrelated with each other and uncorrelated
with variables
exogenous
All variables that omitted effect
from the model have
relatively the
→
endogenous
are a small on
variables
All variables that omitted from the model unrelated
mutually
→ are
are
→ No spurious relations have been omitted from the model
FROM PATH DIAGRAM TO LINEAR EQUATIONS
One
equation per endogenous
D
variable with . . .
•
All variable ( direct effect)
variables that explain the
endogenous
Be An intercept
• A disturbance term
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