Sending R results to Mellio

The Mellio R bridge moves statistical results from R into Mellio’s Stats workspace as structured Result Cards that can be saved, formatted, and used in a manuscript.

Setup

By default, mellio_open() opens the hosted Mellio app at https://www.mellioapp.com.

# Advanced users can point this at a trusted Mellio deployment:
# options(mellio.editor_url = "https://www.mellioapp.com")

The R payload is encoded in the URL fragment. URL fragments are not sent as HTTP requests to the server, but the full URL can still be visible to the browser, the opened web app, browser history, extensions, and anyone the URL is shared with.

Opening a result in Mellio

mellio_open() builds a Result Card from a supported R object and opens it in your browser.

t-tests, correlations, non-parametric tests

library(mellio)

# Welch's two-sample t-test
mellio_open(t.test(extra ~ group, data = sleep))

# Pearson correlation
mellio_open(cor.test(mtcars$mpg, mtcars$wt))

# Chi-squared
M <- matrix(c(10, 20, 30, 40), nrow = 2)
mellio_open(chisq.test(M))

The card shows the test statistic, df, p-value, and effect when available, formatted in APA 7 style.

Regression and ANOVA

m1 <- lm(mpg ~ wt + cyl, data = mtcars)
mellio_open(m1)

m2 <- lm(mpg ~ wt + cyl + hp, data = mtcars)
mellio_open(anova(m1, m2))  # nested model comparison

Mixed models

library(lme4)
mellio_open(lmer(Reaction ~ Days + (Days | Subject), data = sleepstudy))

lmer and glmer cards show AIC, logLik, and N inline (lavaan gets full fit indices below).

CFA / SEM / mediation (lavaan)

library(lavaan)
HS.model <- "visual  =~ x1 + x2 + x3
              textual =~ x4 + x5 + x6
              speed   =~ x7 + x8 + x9"
fit <- cfa(HS.model, data = HolzingerSwineford1939)
mellio_open(fit)

You’ll see a structural card with two zones:

Report zone — fit indices (χ², CFI, TLI, RMSEA + CI, SRMR, AIC, BIC) with quality badges
Inspection zone — full parameter table, grouped by lavaan operator (=~ loadings, ~ regressions, ~~ (co)variances, ~1 intercepts, := defined parameters)

Pre-mark focal paths so they surface in the report zone:

mellio_open(fit, focal = c("visual =~ x1", "textual =~ x4"))

Descriptives

For variable summaries:

mellio_open(mtcars$mpg, name = "Fuel efficiency (mpg)")
# Or from summary() output
mellio_open(summary(mtcars$mpg))

The card shows M, SD, N, and range.

What’s on the card

Each Result Card carries:

Type + call — what test you ran, deparsed exactly
Extracted fields — statistic, p, df, estimate, etc.
Formatted preview — APA 7 inline string, copyable
Provenance — R and package versions, plus data fingerprints when available
Raw R output — verbatim print() for audit

Local provenance fields such as user name, host name, working directory, git state, and script path are opt-in:

options(mellio.provenance = "full")

Set options(mellio.provenance = FALSE) to omit provenance metadata.

Saving to Library

The Save to Library button on the card persists it. When you’re signed into Mellio, cards sync to your account and follow you across devices. When you’re not signed in, cards live in browser localStorage.

The Library lists everything you’ve saved with search and type filters. Click any card to reopen it.

Methods paragraph and reproducibility export

From the Library view:

Methods generates an APA-style Methods paragraph from your saved cards, citing the R packages you actually used (lavaan, lme4, etc.) with versions.
Export downloads either the full JSON (lossless) or a flattened CSV for inclusion in a reproducibility statement.

RStudio addin

Once mellio is loaded, RStudio’s Addins menu gets a Send to Mellio entry. Highlight an R expression (t.test(...)) and run the addin — same effect as typing mellio_open().

Non-interactive use

mellio_open() opens a browser, which is interactive. For scripts and knitr documents, use mellio_payload() to get the JSON payload directly without launching a browser:

p <- mellio_payload(t.test(extra ~ group, data = sleep))
mellio_to_json(p, pretty = TRUE)

Use citation("mellio") for the package citation.