#confounders

Live, measured metrics for the hashtag #confounders from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

hashtag.org network · sponsored

Own #confounders

This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.

$10.85/ year · 11-character #name
Claim #confounders — $10.85/yr→Buy on hashtag.space (web3)
card via hashtag.org · tokens via hashtag.space
0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
8
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 8
0
Avg reactions / post
Mastodon · last 8
—
Reddit posts / month
Reddit search
—
Open-web mentions
hashtag.org Firehose

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-10-16 12:04 UTC
0
10-10
0
10-11
0
10-12
0
10-13
0
10-14
0
10-15
0
10-16

0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.

Related hashtags

measured · fosstodon.org (Mastodon public search API) · fetched 2026-10-16 12:04 UTC

No related tags with measured usage found for #confounders.

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-10-16 12:04 UTC

Everything below is measured over the latest 8 public posts (spanning ~20233 hours).

Top of the latest posts

  • 'Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding', by Jiajing Zheng, Alexander D'Amour, Alexander Franks. http://jmlr.org/papers/v26/22-0372.html #confounders #copula #confounding

    JMLR@[email protected]♥ 0↻ 02025-04-17 09:01 UTCView post →
  • 'A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment', by Robert Hu, Dino Sejdinovic, Robin J. Evans. http://jmlr.org/papers/v25/21-1409.html #confounders #causal #inference

    JMLR@[email protected]♥ 0↻ 02024-06-14 21:01 UTCView post →
  • .@carl_veller & @gcbias present a theoretical analysis of the influence of #confounders in population- & family-based #GWAS, showing that family-based studies, though more rigorous, still carry subtle issues that arise from confounding. #PL

    PLOS Biology@[email protected]♥ 0↻ 32024-04-11 20:07 UTCView post →

What “confounders” means

Wikipedia

In causal inference, confounding is a form of systematic error that can distort estimates of causal effects in observational studies. A confounder is traditionally understood to be a variable that (1) independently predicts the outcome, (2) is associated with the exposure, and (3) is not on the causal pathway between the exposure and the outcome. Failure to control for a confounder results in a spurious association between exposure and outcome.

“Confounding” on Wikipedia (CC BY-SA) →

#confounders across platforms

every network with a public tag surface

Follow #confounders straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.

Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/confounders