
Thinking Clearly About Correlations and Causation (2018) [pdf] - Anon84
https://dacemirror.sci-hub.tw/journal-article/7fe084d6885f9339910bf080b718c012/rohrer2018.pdf?download=true
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vajrabum
Those methods were invented by Judea Pearl, a computer science professor at
UCLA who won the Turing Award in 2011 partly for that work. He's written
several books on the topic. The most recent is The Book of Why. See here for
previous discussions of the book including one just two days ago
[https://news.ycombinator.com/item?id=24487135](https://news.ycombinator.com/item?id=24487135)
[https://news.ycombinator.com/item?id=20889143](https://news.ycombinator.com/item?id=20889143)
ago
[https://news.ycombinator.com/item?id=18871450](https://news.ycombinator.com/item?id=18871450)

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pacbard
Unfortunately for psychologists, establishing causality within a structural
equations framework is really hard (regardless of the common claims that SEM
is causal in nature).

The approach outlined in the paper is close to [Directed Acyclic
Graphs]([https://en.wikipedia.org/wiki/Directed_acyclic_graph](https://en.wikipedia.org/wiki/Directed_acyclic_graph))
and Pearl's approach to causality (see [this
comment]([https://news.ycombinator.com/item?id=24506593](https://news.ycombinator.com/item?id=24506593))
for more info).

The basic issue with these approaches is that the structural model needs to be
well specified in order to get to an unbiased estimate of the causal effect
that you want to estimate. By well-specified, I mean that you have measured
all possible variables impacting the relationship of interest and that you
have specified the correct relationships among the variables (no controls for
mediators or no colliders, as the paper outlines). If you believe that, SEM
can give you unbiased estimates of the coefficient of interest.

On the other hand, if the model is misspecified, coefficients will be biased
and it is difficult to figure out where the bias is. Bollen (1989) pretty much
says that any coefficient could be biased in a misspecified model.

(Micro) Economists have addressed this issues by moving away from a regression
framework and towards experimental and quasi-experimental methods. The same
methods are not really used outside of microeconomics, as far as I can tell.

SEM is a little bit more common (at least with developmental psychologists
that I know of) and that framework doesn't really work well with even basic
quasi-experimental methods (e.g., diff-in-diff).

~~~
currymj
well-specified also requires that the functional relationships are actually
linear, if you're using linear models, right?

this is a common critique of linear SEMs -- some ML researchers refer to a
broader class of "structural causal models (SCMs)", which are basically SEMs
where the relationships may be drawn from broader function classes.

~~~
pacbard
Yes. SEM assumes that all relationships are linear and that all variables are
normally distributed (for standard errors and fit indices calculations). Those
assumptions are baked into the model and are usually never discussed.

Non-linear models are not common in social sciences so that's probably why I
never used them. There are a few variables that are usually quadratic (like
the effect of age on wages). Other than that, linear relationships are good
enough most of the time.

The only real application of non-linear model that I have seen are generalized
structural equation models (GSEM). These allow for the use of link functions
in SEM (logits, logs, poisson, exponentials, etc.) and are the multiple
equations analogue of generalized linear models.

I am not familiar with structural causal models (SCMs), but a quick google
search shows that these are a non-parametric version of SEM based on Baysian
estimation and are a generalization of Baysian network. They sound cool but I
don't think that they will become mainstream in psychology research anytime
soon.

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tj-teej
Reminds me of the XKCD joke:

Person A: I used to think correlation implied causation, then I took a
statistics class. Now I don't.

Person B: Sounds like that class helped.

Person A: Well, maybe...

------
RobertoG
Please, add [pdf] to the title.

~~~
wombatmobile
Sounded interesting. I found it so challenging to read on my phone I didn’t
read it.

~~~
segfaultbuserr
Is there any mobile PDF reader that can do "smart" reformatting?

~~~
HuShifang
Xodo [0] has a "Reading" view (at least in its Android app) that seems to do
just that. A good selection of other features too.

[0]: [https://www.xodo.com/](https://www.xodo.com/)

