#mixedeffects

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

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0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
15
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 15
0.3
Avg reactions / post
Mastodon · last 15

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 18:53 UTC
0
07-21
0
07-22
0
07-23
0
07-24
0
07-25
0
07-26
0
07-27

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 2026-07-27 18:53 UTC
#mixedeffectsmodels
0 uses · 0 accounts / 7d

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 18:53 UTC

Everything below is measured over the latest 15 public posts (spanning ~19802 hours).

Posting hours (UTC) — busiest: 17:00

00:0012:0023:00

Languages: English (15)

Avg boosts / post: 0.7

Top of the latest posts

  • 🚨New preprint on #deception detection analysis 🔍 We provide a tutorial on #Bayesian Mixed Effects Models for veracity data; no more aggregating & converting data to % 😤 (conflating acc w/ bias), just model the lie/truth answers directly!

    Dr Mircea Zloteanu 🌺🌞🍃@[email protected]♥ 3↻ 72023-05-16 16:42 UTCView post →

  • #statstab #51 R Functions for Variance Decomposition {varde} Thoughts: A useful package to get more insight into your mixed effects model. #r #rstats #mixedeffects #lmm #research #modelcomparison https://github.com/jmgirard/varde

    Dr Mircea Zloteanu 🌺🌞🍃@[email protected]♥ 1↻ 02024-03-18 18:58 UTCView post →

  • #statstab #45 Visualizing Hierarchical Models Thoughts: One of the coolest visualisation websites for mixed effects models I had saved. #stats #mixedeffects #hierarchicalmodels #rstats #MLM http://mfviz.com/hierarchical-models/

    Dr Mircea Zloteanu 🌺🌞🍃@[email protected]♥ 1↻ 02024-03-08 18:15 UTCView post →

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/mixedeffects