Compare before and after¶

Question¶

How did the same subjects change between two visits?

See every package-generated example · Read the complete analysis pipeline

When to use¶

Use this when the same subjects have measurements before and after an intervention.

Example figure¶

Compare before and after output generated by Circadian Workbench

This deterministic example is calculated by the paired_measures action and drawn by render_paired_measures_workbench_svg, the same renderer used for publication export. Empty or withheld elements are therefore visible exactly as they are in a real result.

import circadian_workbench as cw

cw.call("paired_measures", epochs=visits)

Required inputs and controls¶

The public function is the registered action below. settings= is accepted as a friendlier alias for config= by cw.call; the calculation stores the complete normalized config in provenance.

Function reference¶

cw.call("paired_measures", epochs, config=None, circular_measures=None)

Arguments and parameters¶

Name	Type	Required	Default	Units	Meaning
`epochs`	object	yes	—	-	The epochs of one study, each a list of subject entries: {"baseline": [{"subject_id": "m01", "measures": {"period_hours": 23.8}}, ...], "treatment": [...]}. Pairing is by subject_id, so a subject missing from any epoch is dropped and named. `paired_measures` takes exactly two and `longitudinal_measures` three or more; each refuses the other's shape by name.
`config`	object	no	`null`	-	Partial scientific settings. Omitted or None values use the shared installed defaults; invalid fresh values are rejected. Run describe_config for names, meanings, units, bounds and choices. Explicitly load old saved mappings with load_saved_settings to report compatibility conversions.
`circular_measures`	array	no	`null`	-	Which measure names are clock times rather than plain numbers, e.g. ["acrophase_hours"]. Those are differenced round the circle -- 23.5 h to 00.5 h is +1 h, not -23 h -- and tested with a Rayleigh test. Nothing is inferred from a name.

Every nested config key, default, allowed value, and purpose is listed in the complete configuration reference.

How it works¶

Subjects are matched by identifier before within-subject differences and tests are calculated.

$$ d_i=y_{i,\mathrm{after}}-y_{i,\mathrm{before}} $$

Implementation: repeated.py::paired_measures.

Outputs and interpretation¶

The result reports paired means, differences, intervals, tests and dropped subjects.

cw.call returns a Result: use .data for calculated values, .warnings for scientific qualifications, .provenance for version and input identity, .script for an equivalent replay script, and .files for saved outputs.

Limitations¶

Unmatched subjects are dropped; circular measures must be declared before comparison.

Example¶

The figure above is a real package result from a seeded, redistributable synthetic dataset. The flat gallery bundle retains figure_data_paired-measures.csv, a standalone plot_paired-measures.py, source hashes, an editable SVG, and a rendered preview.

Methods text¶

Before and after values were paired by subject identifier and tested within subjects.