Why analysts choose Statistico

Instead of isolated statistical outputs, Statistico keeps every stage of Meta-Analysis connected — without leaving the analytical workflow.

From study rows to statistical reasoning — this is Interactive Statistical Computing, not a sequence of static outputs.

Study rows

Pooled effect

Forest plot

Bias checks

What the module provides

Continuous effects (Hedges’ g / SMD)

Binary effects (odds and risk ratios)

Correlations and precomputed effect + SE

Fixed and random effects (REML / DL, Hartung–Knapp)

Forest plot with study weights

I² / Q heterogeneity diagnostics

Funnel plot and Egger’s test

AI-assisted interpretation

Interactive workflow

One synthesis. Connected views.

Click a stage to inspect it — each view stays inside the same pooled analysis, so there's no re-running the meta-analysis to move between them.

Summary

Start with the pooled effect, confidence interval, and model choice in one opening narrative.

Forest Plot

See each study’s effect, confidence interval, and weight beside the pooled diamond.

Heterogeneity

Inspect I², Q, and τ² so between-study variation is visible before you report a single number.

Small-study Effects

Review the funnel plot and Egger’s regression for funnel asymmetry and small-study skew.

Study Details

Audit study-level rows, weights, and sensitivity notes from the Active Range.

AI Interpretation

Plain-language summary of the pooled effect, heterogeneity, and bias checks — see the caution below.

Pooling

Study effects stay in one synthesis story

Switching fixed versus random effects updates the pooled estimate, forest weights, and heterogeneity together, so model choice remains visible rather than buried in a separate printout.

Hedges’ g Odds / risk ratios REML / DL Hartung–Knapp Forest weights Pooled CI

Evidence assessment

Assess heterogeneity and small-study effects

I² / Q, the funnel plot, and Egger’s test sit alongside the pooled estimate so consistency and bias checks are inspectable before reporting.

I² Cochran’s Q τ² Funnel plot Egger’s test Study weights Sensitivity

Study audit

Move from pooled estimate to study-level rows

Study Details keeps weights, effects, and source rows tied to the same synthesis, so audit and leave-one-out checks do not restart the workflow.

Interpretation

Interpretation within the analytical workflow

Statistico's AI-assisted assessment summarizes the pooled effect, heterogeneity, and small-study findings from the same meta-analysis output already in the workspace.

AI-assisted interpretation supports, but does not replace, statistical judgment.

Why Statistico

Built for analysts who already know the method

Excel remains the working data environment.

Statistical outputs remain visible and inspectable.

Interaction supports analysis rather than hiding it.

Related modules

Explore Meta-Analysis as an interactive module

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