Mellio brings your data to life. Run an analysis in the browser, or send one from R, and read the result in a nutshell. APA-style tables and figures, editable in place, are each just one click away.
> fit <- lm(score ~ hours, data = study) > mellio_open(fit) ✔ sent to Mellio
| Predictor | b | SE | t | p |
|---|---|---|---|---|
| Intercept | 61.40 | 2.10 | 29.2 | <.001 |
| Hours | 2.94 | 0.61 | 4.82 | <.001 |
Send a model or test — from R, or from Mellio Analyzer — and it lands as a Result Card: the estimate, the call that produced it, and a plain-language summary you can reword and copy straight into your manuscript.
lm(score ~ hours, data = study)
b = 2.94, SE = 0.61, t(46) = 4.82, p < .001, R² = .34, 95% CI [1.71, 4.17]
Hours studied significantly predicted exam score, b = 2.94, SE = 0.61, t(46) = 4.82, p < .001, 95% CI [1.71, 4.17]. The model explained 34% of the variance (R² = .34).
Switch between the bare statistic — formatted for quick review and copying — and a nutshell summary of what your data found. Try the toggle on the card.
The exact call that produced it stays attached to the card, so any number traces straight back to where it came from.
Open the same result as an editable table or figure you can refine for your reporting style.
Send a result from Stats, bring a table over from R, or paste straight from SPSS, Excel, or JASP. Mellio lays it out in APA 7 or IEEE — the rounding, italics, and rules already right — and copies into Word as a table you can still edit.
| Predictor | b | SE | t | p |
|---|---|---|---|---|
| Intercept | 61.40 | 2.10 | 29.2 | <.001 |
| Hours | 2.94 | 0.61 | 4.82 | <.001 |
A Stats result lands with its source attached. Paste from SPSS, Excel, JASP, or Word and Mellio reads the structure — and R tables come straight over.
Switch styles and the caption, rules, and italics follow. Tune decimals, p-values, significance stars, and which symbols stay italic. Try the toggle on the card.
Copy into Word or Google Docs as an editable table — not an image — or take it as Markdown or LaTeX for Overleaf.
Send a result from Mellio Analyzer or R, then open it in Figures. Mellio builds the plot from computed estimates and intervals, so labels, colors, captions, and layout stay editable without changing the statistics. If the figure starts from a file, supported xlsx data or result-table ranges can open too.
A regression result can become this fitted-line figure; other analyses can open coefficient plots, mean plots, or interval figures when the result contains them. Workbook uploads are supported too when Mellio detects a figure-ready range.
Titles, labels, ticks, colors, ordering, significance brackets, and reference lines stay editable while the computed estimates and confidence intervals remain tied to the result.
Copy into Word or Google Docs as an image with its caption, or export a PNG with the print DPI already embedded.
Drop in a spreadsheet and click any variable — Mellio has already read it. Numbers get their mean, SD, median and range; categories get their level frequencies; a built scale gets its Cronbach's α. All on your device, before you run a single test.
Mellio recognises an ID column and keeps it out of your analyses.
Select a variable and the summary is already there — descriptives for numbers, frequencies for categories, reliability for scales. No formulas, no waiting.
Retype, recode, reverse-score, derive new columns, or build a scale from its items — the quick actions for whatever you select.
Pick an analysis, drop the variables in, and the result lands as a Result Card — assumption checks shown as context, all in the browser.
Every number is golden-tested against R — pinned to R's own output, to a tolerance of 10−8.
Already fit in R? mellio_open(fit) sends any result to Mellio —
t-tests to mixed models to lavaan path diagrams. Only the result travels,
inside the URL itself: your data never touches a server.
> > ✔ result encoded — opening Mellio
Linear, mixed, and generalized models; ANOVA and post-hoc; correlation, factor, survival, SEM, Bayesian, and time-series fits — lm, lmer, brms, lavaan, coxph, Arima and more — with a graceful fallback for the rest.
Use melliotab() when you want the table to live in your R workflow first:
give it a title, table number, and note in the call, then add extras like
significance stars only when they fit the manuscript. Copy to Word, knit in
Quarto, or open the same table in Mellio.
Statistical results land in Stats, ready to narrate. Plain data frames land in Tables, ready to format.
Send a lavaan fit and get an editable structural diagram — nodes drag, path labels edit.
Tables drop into R Markdown and Quarto and render on knit, in HTML or LaTeX output.
Every handoff records the package versions that produced it, so a result stays traceable — and citable — back to the exact software behind it.
Mellio for R supports selected models, tests, model comparisons, tables, and figures. Please review outputs before publication, especially for complex models or optional-package results.
Install from GitHub while CRAN submission is in progress:
install.packages("remotes") # if needed
remotes::install_github("NicoMel1907/mellio-r")
library(mellio)
Every result you keep lands in a library that remembers. Folders, color labels, memos that @-mention other cards — and when reviewer two asks how Study 1 compared, the answer is two clicks, not an afternoon.
Select any two results for a quick comparison — try it on the cards to the right.
Merge figures into a multi-panel composite, or gather results into one card.
Notes can @-mention tables, figures, and stats — so context stays attached to evidence.
Trash keeps deleted work restorable. Search and sort cover the rest.
| Predictor | b | p |
| Intercept | 61.40 | <.001 |
| Hours | 2.94 | <.001 |
Spreadsheets are parsed in your browser, and supported analyses run in your browser. Mellio does not sell your data, does not use ad tracking, and does not expose AI parsing in the current product.
By default, Mellio is local-first: your library lives in this browser. Sign in and turn on sync when you want saved tables, figures, and results backed up to your account too - and turn it off whenever you like.
Results sent with mellio_open() travel in the URL hash.
Treat those URLs as analysis data: they can include model summaries,
table data, plot images, selected point-level figure data, and
provenance metadata.
What you have today — analysis, tables, figures, and clean output — is the foundation, and it keeps growing: new statistical tests are landing in the Analyzer all the time. From here I'm building toward a fuller research workspace — collaborative writing, a reference manager, and AI that assists without taking over your judgment.
Some of what comes next will be paid — that's what lets me keep building it. But Mellio will always keep a meaningful free core, and keeping it within reach for the people whose work holds communities together — non-profits and public-interest research — will always be a priority. I'm putting that here on purpose, so it's a commitment I'm held to.
Has Mellio helped your work? I'd love to hear — hello@mellioapp.com.
In public beta — if something is unclear or a feature would help your research, tell me at hello@mellioapp.com.