Common Workflows by Dataset Shape

Overview

Use this page when the shape of the table is easier to recognize than the statistical method name. The goal is not to route you automatically. The goal is to help you pick the next cautious docs page to read.

This page is an orientation layer. The value is not the row match itself. The value is that each suggested next page points you toward a bundle of figures, analysis families, quality checks, and reporting cautions that are more likely to fit the dataset shape you have.

It is therefore a reading guide, not a product diagnosis. Licklider is not inferring the final method from this page. This page helps a human reader move from "my table looks like this" to "this is the next docs bundle I should inspect."

What you usually get next

When this page helps you choose the next workflow bundle, the next page usually helps you narrow toward one or more of the following:

candidate figures, such as heatmaps, volcano plots, Kaplan-Meier curves, or repeated-measures views
candidate analysis families, such as regression, survival analysis, multiplicity-aware screening, or repeated-measures methods
quality checks or design warnings, such as independence, compositionality, censoring, or multiplicity review
a clearer boundary on whether the current guidance is active, partial, planned, or still low-claim

This means the practical output of this page is not a p-value or a final verdict. The practical output is a safer next reading path that helps you reach the right figures, methods, and checks faster.

In practice, that often means reaching the next page with a clearer expectation of what Licklider may produce there: for example, a volcano-style figure, a survival-oriented workflow, an independence check, or a repeated-measures analysis path.

Who this is for

Readers who can describe the dataset pattern but have not yet decided which workflow page to open
Readers who want a domain-shaped starting point before choosing methods, figures, or checks
Readers who need a low-claim orientation page rather than one deterministic decision tree

First step

Match your dataset to the closest row below.
Open the suggested workflow bundle or analysis hub.
Confirm the support boundary before turning the suggestion into a stronger public claim.

Do not treat the table below as an automatic triage engine. Treat it as a cautious shortcut into the next layer of docs.

Suggested starting points by dataset shape

Dataset shape or problem pattern	Suggested next page	What you will usually get there	Why this is the next page
Dose-response-like table with concentration and response values	Dose-response Curves	Non-linear fit guidance, regression-style figures, and dose-response-specific interpretation cautions	This is the closest domain bundle for non-linear fit review and regression-style figures, even though it is still low-claim guidance
High-dimensional cell-feature matrix or exploratory cytometry-style table	Flow Cytometry Data Analysis	PCA-style views, clustering-style views, heatmaps, and cautions about composition and interpretation	This page bundles PCA-style views, clustering-style views, heatmaps, and compositional caution without claiming a dedicated flow-cytometry pipeline
Omics-style matrix with many features under screening	Multi-omics and Compositional Data	Volcano- and heatmap-oriented guidance plus multiplicity review and compositional warning	This page is the closest current bundle for volcano plot, heatmap, multiplicity review, and compositional warning
Time-to-event table with censoring-oriented questions	Clinical Trial Endpoints	Kaplan-Meier and Cox-adjacent guidance, survival-focused checks, and reporting cautions around censoring	This is the nearest cautious entrypoint for Kaplan-Meier-, Cox-, and survival-adjacent pages
Repeated-measures table with timepoint or within-subject structure	Repeated Measures Experiments	Repeated-measures guidance, within-subject design checks, and independence-related cautions	This page is the nearest current bundle for repeated-measures guidance and independence checks
Dataset already framed as a standard analysis family	Analysis Workflow Hubs	A method-centered path to the next figure, test, and quality-check pages	Use the method-centered hubs first when the domain framing is less important than the analysis family

Reading note

These are orientation hints, not automatic workflow choices.
A similar table can still require different methods depending on design, censoring, repeated structure, compositional behavior, or reporting goals.
Licklider cannot determine from dataset shape alone whether your study has hidden pairing, pseudoreplication, nested sampling, batch confounding, confirmatory versus exploratory multiplicity plans, or censoring assumptions that change the correct workflow.
If those design facts are missing or misread, a dataset can be routed to a page that looks plausible while still leading you toward the wrong figures, methods, or reporting claims.
Example: two tables can both look like ordinary group-comparison data, but if one contains repeated measurements from the same subjects and the other contains independent samples, they should not follow the same downstream workflow.
Keep Known Limitations nearby when the page you open next is still guidance-only, partial, or planned.

What this page does not do

It does not produce a statistical result by itself.
It does not automatically choose the correct method from table shape alone.
It does not guarantee that the next page reflects your real study design until you verify pairing, independence, censoring, compositional behavior, and reporting intent.

TODO (Phase02+)

Expand only if dataset-shape guidance later gains clearer evidence-backed branching rules.