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ON BIAS AMPLIFIERS. Judea Pearl University of California Los Angeles (www.cs.ucla.edu/~judea/). ON BIAS AMPLIFIERS Judea Pearl University of California Los Angeles (www.cs.ucla.edu/~judea/). THE PROBLEM: - PowerPoint PPT Presentation
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ON BIAS AMPLIFIERS
Judea Pearl University of California
Los Angeles(www.cs.ucla.edu/~judea/)
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THE PROBLEM:We wish to estimate the causal effect P(y|do(x)) by adjusting for a set Z of variables.
Given a graph, G, find Z so as to minimize the bias:
zxdoyPzPzxyP ))(|()(),|(
ON BIAS AMPLIFIERSJudea Pearl
University of CaliforniaLos Angeles
(www.cs.ucla.edu/~judea/)
33
THE SOLUTION:Z must be admissible, i.e., satisfy the back-door criterion
But what if some confounders remain unmeasured (e.g., U)?
Would it help if we adjust for Z10? Z3? Perhaps Z5?
Or would it increase bias?
Z6
Z3
Z2
Z5
Z1
XY
Z10
Z7 Z8Z9
Z4
U
e.g., Z = {U, Z4, Z5}
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U
c1
X Y
Z
c2c3
c0
SURPRISING RESULT:Instrumental variables are Bias-Amplifiers in linear models (Bhattarcharya & Vogt 2007; Wooldridge 2009)
“Naive” bias
Adjusted bias
2123
2102
3
210
11))(|(),|( cc
c
ccc
c
cccxdoYE
xzxYE
xBz
2102100 ))(|()|( ccccccxdoYEx
xYEx
B
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INTUTION:When Z is allowed to vary, it absorbs (or explains) some of the changes in X.
When Z is fixed the burden falls on U alone, and transmitted to Y (resulting in a higher bias)
U
c1
X Y
Z
c2c3
c0
U
c1
X Y
Z
c2c3
c0
66
c0
c2
Z
c3
U
YX
c4
T1
c1
WHAT’S BETWEEN AN INSTRUMENT AND A CONFOUNDER?Should we adjust for Z?
T2
ANSWER:
CONCLUSION:
23
12
3
4
1 c
cccc
Yes, if
No, otherwise
Adjusting for a parent of Y is safer than a parent of X
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WHAT ABOUT NON-LINEAR MODELS?
1. Conditioning on IVs may reduce or amplify bias; mostly amplify
2. Conditioning on IVs may introduce its own bias where none existed.
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CAN AN IV AMPLIFY SELECTION BIAS?
ANSWER: NoExercise: which selection bias will be amplifiedby Z? S1? S2? or S3?
1
X Y
Zc3 c0
2
S
UY
S= s0
U1
S1
X Y
Z
S2 S3
UY
U2
99
CONCLUSIONS
• The prevailing practice of adjusting for all covariates, especially those that are good predictors of X (the “treatment assignment,” Rubin, 2009) is totally misguided.
• The “outcome mechanism” is as important, and much safer
• As X-rays are to the surgeon, graphs are for causation