Currently, I do not automatically handle non-independent data. v4.0 is likely to change this
github.com/pzivich/Deli...
Currently, I do not automatically handle non-independent data. v4.0 is likely to change this
github.com/pzivich/Deli...
So, it is good for modeling proportions as outcomes. While we can also use fractional logistic regression, this is another option
So, it is good for modeling proportions as outcomes. While we can also use fractional logistic regression, this is another option
Let consider the effect of action A on outcome Y through mediator M
Let consider the effect of action A on outcome Y through mediator M
deli.readthedocs.io/en/latest/Ex...
deli.readthedocs.io/en/latest/Ex...
In other words, I found Wooldridge's book and the Mroz 1987 paper
deli.readthedocs.io/en/latest/Ex...
In other words, I found Wooldridge's book and the Mroz 1987 paper
deli.readthedocs.io/en/latest/Ex...
M-estimation, or the act of stacking estimating functions, has great potential to improve the statistical rigor of scientific research
M-estimation, or the act of stacking estimating functions, has great potential to improve the statistical rigor of scientific research
This example ties in with #WorldAIDSDay as it relies on data from the AIDS Clinical Trial Group (ACTG) 175, comparing 2-drug versus 1-drug ART for prevention of disease progression among persons with HIV
This example ties in with #WorldAIDSDay as it relies on data from the AIDS Clinical Trial Group (ACTG) 175, comparing 2-drug versus 1-drug ART for prevention of disease progression among persons with HIV
For this, I am going to reach outside my subject area and pontificate about cheminformatics
For this, I am going to reach outside my subject area and pontificate about cheminformatics
To start, I am going to note a new release of `delicatessen` v3.2
The major addition of this release is confidence bands
To start, I am going to note a new release of `delicatessen` v3.2
The major addition of this release is confidence bands
Like proximal causal inference, this is another way to address unmeasured confounding. For this, let's go over per-protocol effects in trials
Like proximal causal inference, this is another way to address unmeasured confounding. For this, let's go over per-protocol effects in trials
We can think about proximal causal inference as an extension of the standard identification assumptions to allow for more rich data structures. Specifically, we can account for unmeasured confounding
We can think about proximal causal inference as an extension of the standard identification assumptions to allow for more rich data structures. Specifically, we can account for unmeasured confounding
To start, let's talk computational aspects. As you might recall from the weeks on the sandwich variance, we need to compute derivatives. One option is automatic differentiation (autodiff)
To start, let's talk computational aspects. As you might recall from the weeks on the sandwich variance, we need to compute derivatives. One option is automatic differentiation (autodiff)
This is based on the algorithm in my pre-print, but needs a few tweaks
arxiv.org/abs/2504.13291
This is based on the algorithm in my pre-print, but needs a few tweaks
arxiv.org/abs/2504.13291
I'm going to take advantage of microblogging as a format and live code a new estimating equation
I'm going to take advantage of microblogging as a format and live code a new estimating equation
More specifically, we are going to bridge different trials together to address a single question
pubmed.ncbi.nlm.nih.gov/38110289/
More specifically, we are going to bridge different trials together to address a single question
pubmed.ncbi.nlm.nih.gov/38110289/
So far we've seen how the M-estimation framework is useful computationally, so let's step back and see how it is also useful for statistical proofs
So far we've seen how the M-estimation framework is useful computationally, so let's step back and see how it is also useful for statistical proofs
Let's talk about something M-estimation has a bit of difficulty with: the median
Let's talk about something M-estimation has a bit of difficulty with: the median
As setup for later weeks, let's talk about data fusion and why M-estimators are a useful way to build fusion estimators. Today is based on the following paper
pubmed.ncbi.nlm.nih.gov/35388406/
As setup for later weeks, let's talk about data fusion and why M-estimators are a useful way to build fusion estimators. Today is based on the following paper
pubmed.ncbi.nlm.nih.gov/35388406/
So, if something isn't clear, I'm incorrect, or there is something missing; passive-aggressively quote the offending skeet
So, if something isn't clear, I'm incorrect, or there is something missing; passive-aggressively quote the offending skeet
pmc.ncbi.nlm.nih.gov/articles/PMC...
pmc.ncbi.nlm.nih.gov/articles/PMC...
bsky.app/profile/paus...
Specifically, I am going to focus on the use of dose-response models. We have some different dosages (D) and some continuous response (R)
bsky.app/profile/paus...
IV analysis is nice because we can get around unmeasured confounding (at the cost of a more easily interpretable parameter)
IV analysis is nice because we can get around unmeasured confounding (at the cost of a more easily interpretable parameter)