Friday , October 18 2024
Home / Tag Archives: Statistics & Econometrics (page 23)

Tag Archives: Statistics & Econometrics

How to achieve ‘external validity’

How to achieve ‘external validity’ There is a lot of discussion in the literature on beginning with experiments and then going on to check “external validity”. But to imagine that there is a scientific way to achieve external validity is, for the most part, a delusion … RCTs do not in themselves tell us anything about the traits of populations in other places and at other times. Hence, no matter how large the population from which we draw our random samples...

Read More »

Randomizations creating illusions of knowledge

Randomizations creating illusions of knowledge The advantage of randomised experiments in describing populations creates an illusion of knowledge … This happens because of the propensity of scientific journals to value so-called causal findings and not to value findings where no (so-called) causality is found. In brief, it is arguable that we know less than we think we do. To see this, suppose—as is indeed the case in reality—that thousands of researchers...

Read More »

Why the idea of causation cannot be a purely statistical one

Why the idea of causation cannot be a purely statistical one If contributions made by statisticians to the understanding of causation are to be taken over with advantage in any specific field of inquiry, then what is crucial is that the right relationship should exist between statistical and subject-matter concerns … Where the ultimate aim of research is not prediction per se but rather causal explanation, an idea of causation that is expressed in terms of...

Read More »

Structural equation modelling (student stuff)

Structural equation modelling (student stuff) .[embedded content] This is a good introduction to some of the basic thoughts behind the use of SEMs. But — for the controversial question if SEMs really can be considered causal, yours truly highly recommends reading Kenneth Bollen’s and Judea Pearl’s Eight myths about causality and structural equation models.

Read More »

Discrimination and the use of ‘statistical controls’

The gender pay gap is a fact that, sad to say, to a non-negligible extent is the result of discrimination. And even though many women are not deliberately discriminated against, but rather self-select into lower-wage jobs, this in no way magically explains away the discrimination gap. As decades of socialization research has shown, women may be ‘structural’ victims of impersonal social mechanisms that in different ways aggrieve them. Wage discrimination is unacceptable. Wage...

Read More »

On the limits of ‘mediation analysis’ and ‘statistical causality’

“Mediation analysis” is this thing where you have a treatment and an outcome and you’re trying to model how the treatment works: how much does it directly affect the outcome, and how much is the effect “mediated” through intermediate variables … In the real world, it’s my impression that almost all the mediation analyses that people actually fit in the social and medical sciences are misguided: lots of examples where the assumptions aren’t clear and where, in any case,...

Read More »