Rank Nonoverlap vs Mean Level Change: Clinical Guide

Rank nonoverlap versus mean level change compares two different summaries. Rank metrics ask how often intervention values order better than baseline values. Mean level change subtracts phase means and retains distance, while remaining sensitive to extremes and distribution shape. Use one locked dataset and direction, report both calculations with raw phases, and explain why neither result substitutes for visual or design analysis.

Lock one dataset and direction

Resolve invalid points and phase labels before computing either metric. Use the same improvement direction and source values.

Calculate rank ordering

Score all cross-phase pairs as improvement, deterioration, or tie. Report pair counts and the signed coefficient.

Calculate mean distance

Find each phase mean and subtract in the stated direction. Report the result in the original unit and retain phase SD or range when helpful.

Trace divergence

Identify which ranks and distances drive the difference. Check extreme values, skew, bounds, unequal spacing, and small phase sizes.

Match metrics to questions

Use rank separation for ordering and mean change for average distance only when their assumptions and sensitivities fit. Neither alone establishes causation or clinical value.

Build Yuki's two-metric reconciliation sheet

Start with a locked worklist for Yuki. Record the review question, metric name, formula version, phase labels, improvement direction, planned and valid observations, missing or invalid states, tie handling, trend handling, source timestamps, calculation owner, and review date. The rank-versus-mean comparison result should be reproducible from this worklist without relying on an unlabeled dashboard value. Keep the data in their original unit so reviewers can connect the supplement to the graph and to the actual outcome. For the rank nonoverlap versus mean level change question, Yuki's reviewer also records the release criterion, expected evidence, unresolved limitations, and exact action that the result may inform. This small decision log prevents a calculation from becoming an open-ended label and lets a later reviewer distinguish the observed value from the judgment made with it.

Work the calculation for Yuki

Yuki's baseline values are 1, 2, and 100; intervention values are 3, 4, and 5; higher is preferred. Six of nine cross-phase pairs improve and three deteriorate, so uncorrected Tau is (6 minus 3)/9, or 0.333. Baseline mean is 34.33 and intervention mean is 4.00, so mean level change is minus 30.33. Show every intermediate count or statistic at enough precision to reproduce the displayed result. Keep the raw phase values in chronological order beside any sorted, paired, or transformed table. The fictional arithmetic illustrates the method; it does not create a clinical threshold, minimum phase size, or promised treatment effect.

Audit Yuki's denominator and formula

Yuki's sheet shows that each intervention value exceeds baseline 1 and 2 but remains below 100. It reconciles six positive and three negative pairs, then traces the negative mean change to the single value 100. Both calculations use exactly three valid points per phase. The audit also checks duplicate timestamps, silent imputation, phase-boundary drift, direction reversal, premature rounding, spreadsheet ranges, software version, and correction history. Any unresolved source discrepancy stays on hold with an owner and due date instead of being converted into a convenient zero or exclusion.

Watch for the main failure mode in Yuki's review

Calling the metrics contradictory without inspecting their information targets misses the reason for divergence. The rank result ignores distance, while the mean result gives the outlier substantial weight. Yuki's report describes both rather than averaging them. Reviewers should be able to see how one point, tie, extreme, missing observation, or phase-length decision affects the result. A sensitivity example is labeled as hypothetical and never mixed with observed evidence.

Integrate the metric with visual and design analysis for Yuki

The responsible reviewer validates the value 100, inspects medians, ranges, trend, and context, and decides which supplemental summary fits the predeclared question. The graph and original measurement unit remain primary for discussing magnitude with Yuki. The WWC Version 5.0 handbook is a research evidence standard, so its design criteria are not a universal clinical protocol. In care, the responsible clinician also considers current assessment evidence, professional scope, the treatment plan, ordinary supports, risk, and the person's choices.

Protect client relevance and access for Yuki

During Yuki's pair ordering compared with arithmetic mean distance review, keep augmentative and alternative communication, interpreters, mobility, food, water, bathroom use, prescribed care, health support, rest, relationships, and emergency help available. Use accessible communication to ask whether the goal, direction, magnitude, burden, and observed change matter to Yuki. A favorable coefficient cannot repair an unwanted target, inaccessible measurement process, unsafe plan, or missing consent and assent process.

Use current evidence within scope for Yuki

For Yuki's rank-versus-mean comparison review, the BACB ethics hub and CASP public summary provide professional context, while the BCBA Test Content Outline supplies examination scope for measurement, graphing, interpretation, experimental design, and data-based evaluation. A single-case methods review describes common overlap, Tau, and two-SD calculations. Decision-accuracy research shows why phase size and design structure matter and why overlap percentages do not measure distance. A reproducibility tutorial documents ambiguity among Tau-U implementations and baseline corrections. Nonoverlap and mean-difference methods explain their distinct information targets. ASHA supports continuous access to AAC tools or devices.

Close Yuki's supplemental analysis review

Review the two-metric reconciliation sheet with Yuki and the responsible qualified clinician. Preserve source data, graph, phase definitions, calculation specification, coverage, ties, uncertainty, limitations, client input, selected action, owner, and next review date. Reopen the analysis when the measure, phase, context, access, health, goal, software, or design changes. The final note should make clear which conclusions are supported, which remain uncertain, and which require different evidence.

How to Compare Rank Nonoverlap With Mean Level Change