### CS&SS\STAT 566

#### CAUSAL MODELING

#### WINTER 2017

### Readings

(*Notes on using UW's proxy server to access some of these papers.*)

###
Introduction to Potential Outcome Models (Week 1)

Morgan and Winship: Section 1.1; Sections 2.1-2.5;

Angrist and Pischke: Chapter 1, and Chapter 2.1-2.2

#### Background Reading

Samuel Pepys, Isaac Newton and Probability
E. Rubin and E.D. Schell. * The American Statistician * Vol.14, No.4, 27-30.

###
SUTVA and the consistency assumption

Statistics and Causal Inference Paul W. Holland
* Journal of the American Statistical Association *, Vol. 81, No. 396. (Dec., 1986), pp. 945-960.

Estimating causal effects of treatments in randomized and nonrandomized studies
Don B. Rubin * Journal of Educational Psychology*, Vol 66(5), Oct, 1974. pp. 688-701

#### Background Reading

On the Application of Probability Theory to Agricultural Experiments J.Neyman (D.M.Dabrowska, T.P.Speed, Trans.). * Statistical Science * Vol.5, No.4, 465-472.

### More on Consistency and SUTVA

The Consistency Statement in Causal Inference:
A Definition or an Assumption? S.R. Cole and C.E. Frangakis
* Epidemiology *, Vol. 20, No. 1. (Jan., 2009), pp. 3-5.

Concerning the Consistency Assumption in Causal Inference
T.J. VanderWeele
* Epidemiology *, Vol. 20, No. 6. (Nov., 2009), pp. 880-883.

On the Consistency Rule in Causal Inference: Axiom, Definition, Assumption, or Theorem?
J. Pearl
* Epidemiology *, Vol. 21, No. 6. (Nov., 2010), pp. 872-875.

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