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Relationship Analysis

TAO / ANALYSIS SYSTEM · RELATIONAL TESTINGANL / 06 ASSOCIATION UNDER CONTROL
ANL / 06 · RELATION LAYER

Relationship Analysis

Objects do not become related because two lines move together. Relationship analysis tests whether changes, states or positions vary together; specifies the direction and form of that variation; and determines whether it survives conditioning, alternative specifications and independent evidence.

01 DEFINITION

A relationship is structuredco-variation inside a boundary.

The analysis begins only after units, measures, timing and eligible observations are declared. It ends with a bounded relational statement—not an invented mechanism.

A relationship exists when variation in one defined measure corresponds systematically with variation in another, beyond the selected contrast and within stated conditions.

Its credibility depends on measurement quality, overlap, sample structure, timing, functional form, sensitivity and evidence independence. Strength alone cannot repair a misaligned unit or a hidden common driver.

OBJECTSWhat exactly is being related?
MEASURESHow is each object represented?
CONTEXTWhere and when can the link exist?
LIMITWhat conclusion is not licensed?
02 SIX TESTS

One coefficient cannot describethe relationship system.

Every candidate relation passes six separate checks. Failure at one gate changes the interpretation even when the raw association looks strong.

R / 01

Direction

Positive, negative, reciprocal, asymmetric or absent.

ASK / WHICH WAY?
R / 02

Form

Linear, curved, thresholded, clustered, lagged or discontinuous.

ASK / WHAT SHAPE?
R / 03

Strength

Magnitude relative to scale, variation and an appropriate null.

ASK / HOW MUCH?
R / 04

Stability

Persistence across windows, segments, metrics and specifications.

ASK / DOES IT SURVIVE?
R / 05

Conditioning

Change after controlling for composition, time or a shared driver.

ASK / WHAT EXPLAINS IT?
R / 06

Independence

Replication across genuinely separate sources or observations.

ASK / IS SUPPORT DISTINCT?
03 WEIGHTED MATRIX

Inspect the entire field.Do not cherry-pick one edge.

This illustrative adjacency matrix exposes positive and negative links, weak cells, diagonal self-comparisons and the effect of changing the minimum reporting threshold.

WEIGHTED ADJACENCY / ILLUSTRATIVEDISPLAY ≥ 0.30
VISIBLE EDGES18
PAGE ↔ LINK+0.71

Strongest positive relationship in the current field.

PAGE ↔ OUTCOME+0.64

Positive candidate that still requires conditioning.

QUERY ↔ OUTCOME+0.55

Moderate association inside the declared boundary.

QUERY ↔ MARKET−0.18

Weak negative edge; below the default reporting threshold.

Reading rule: color shows direction; intensity shows absolute strength. Hidden cells remain observations—they fall below the current display threshold and must not be reported as zero.

04 CONDITIONING

A strong raw link can collapsewhen the shared driver enters.

Move the confounder control. The example demonstrates why an observed A–B association must be recalculated after plausible common drivers are introduced.

CONDITIONAL RELATIONSHIP FIELDINTERACTIVE
A / DEPTHB / CLICKSZ / AGE
CONDITIONED READOUT

Strong raw association

Deeper pages appear to receive fewer clicks. The raw relationship is visible, but page age may influence both depth and accumulated demand.

RAW r−0.78
PARTIAL r−0.78
RETAINED100%
STATUS / UNCONDITIONED — report as a candidate relationship only.
05 TEMPORAL ORDER

Test when the relation appears.Timing changes meaning.

Contemporaneous movement, leading indicators and delayed responses are different structures. A lag profile helps locate the strongest alignment without pretending it proves direction.

LAG / −20.18

B precedes A by two windows.

LAG / −10.31

B precedes A by one window.

LAG / 00.49

Measures move in the same window.

LAG / +10.67

A best aligns with B one window later.

LAG / +20.38

The alignment weakens after two windows.

06 WORKED EXAMPLES

Three domains.Three bounded readings.

Switch between asset, demand and SERP examples. Each one names the unit, metric, competing explanation and conclusion limit.

EXAMPLE / ASSET GRAPH

Hub distance and discovery frequency

Across eligible canonical pages, greater link distance from the closest hub corresponds with less frequent crawler discovery in synchronized observations.

UNITCanonical page × crawl window
MEASURESHub distance / discovery frequency
CONTROLTemplate, page age and indexability
LIMITAssociation does not establish ranking effect
BOUNDED FINDING / Within the measured site and crawl windows, hub distance retains a negative relationship with discovery frequency after template and age adjustment. Ranking impact is not tested.
07 RELATIONSHIP GATES

Before interpretation,attack the edge.

A relationship becomes credible by surviving tests designed to make it disappear—not by collecting more decorative coefficients.

GATE / A

Unit alignment

Both measures refer to compatible objects, windows and aggregation levels.

PASS / SAME ANALYTICAL GRAIN
GATE / B

Range sufficiency

The sample contains enough variation to reveal or challenge the relationship.

PASS / NO RANGE RESTRICTION
GATE / C

Influence control

No single outlier, dominant domain or duplicated group creates the edge.

PASS / LEAVE-ONE-OUT
GATE / D

Specification stability

Direction and practical magnitude survive reasonable metric and model changes.

PASS / SENSITIVITY BOUNDED
GATE / E

Segment consistency

The aggregate link is not a reversal produced by mixing unlike subgroups.

PASS / STRATA INSPECTED
GATE / F

Temporal integrity

Collection order, shared trends and seasonality do not manufacture alignment.

PASS / TIME TESTED
GATE / G

Negative controls

Variables that should not relate remain weak under the same pipeline.

PASS / PIPELINE SPECIFIC
GATE / H

Independent support

The relation recurs in evidence not derived from the same duplicated source.

PASS / REPLICATION DISTINCT
08 EXECUTION PROTOCOL

From pair selectionto bounded relation.

The procedure keeps discovery separate from confirmation and makes every transformation inspectable.

01

Declare pair

Name objects, measures, units, scope and plausible direction before testing.

02

Align evidence

Join only comparable observations; preserve missingness and collection time.

03

Inspect form

Plot raw structure before reducing it to a single coefficient.

04

Test alternatives

Condition, stratify, lag, resample and remove influential observations.

05

Replicate

Seek the edge in a genuinely independent window, source or population.

06

Bound finding

Report direction, magnitude, uncertainty, conditions and causal limit.

09 OUTPUT CONTRACT

Report the edge.Expose its conditions.

The final statement must contain enough structure for another analyst to challenge or reproduce it.

RELATIONSHIP OUTPUT CONTRACT
Within [scope], measure A varied [direction / form] with measure B at [magnitude]; the relation survived [checks], weakened under [condition], and does not establish [unsupported claim].

The contract prevents a statistically visible edge from becoming an unlimited narrative.

Objects, measures and grain declared
Form inspected before coefficient
Raw and conditioned estimates separated
Thresholds and missing values disclosed
Stability and independence tested
Causal and predictive limits explicit
10 ANALYSIS ROUTER

One root.Twelve analytical nodes.

Relationship Analysis is the sixth node: it tests how defined measures vary together before trend or causal interpretation.

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