An imputed quitting outcome is a modeled value, not a recovered observation

Distinguish three routes to a completed table

A study can obtain an actual delayed response, analyze only available outcomes, or use a method that addresses missing values. Those routes are not equivalent simply because the final analysis includes a number for every participant. Find the methods behind the table before describing all its values as collected follow-up observations.

Cochrane’s analysis chapter separates available-data analysis, replacement approaches and models that account for missing data under assumptions. That distinction supports this reading task, not a judgment about a named trial. There is no universal rule here that every imputation is good, bad or equivalent to observing what was originally unknown.

Cochrane: Cochrane Handbook Chapter10, sections10.12.2–10.12.3

Create an observed-and-modeled inventory

For an original worksheet, draw two columns: actually measured outcomes and analytically represented missing outcomes. Under the second, write the method stated by the report and the information it uses. Include the target follow-up and outcome definition. Do not invent individual replacement values from a group result or ask for identifiable participant histories to populate the worksheet.

Consider a fictional study that lacks some follow-up responses and reports multiple imputation. A reader should not say the investigators found those participants and verified their outcomes. Nor should the reader assume that every missing response received the same fixed value. Preserve the method’s name until the report or qualified interpretation explains its actual use. No real study or finding is described.

Ask which assumptions remain unobserved

A replacement method can depend on relationships between available information, missingness and the unobserved outcome. Those assumptions need explanation; a software label alone cannot verify them. Check whether the report states why its approach fits the missing-data circumstances and how the analysis reflects uncertainty associated with values that were not measured.

Alternative-assumption analyses can show how results change under specified choices, but they do not reveal the true missing outcomes. A stable result across the reported checks is evidence about those checks, not proof that every possible missingness process was covered. Avoid choosing a method from the headline or calculating your own corrected quitting percentage.

Keep the interpretation honest at both levels

Your final note can distinguish the number with observed follow-up from the analysis that includes modeled missing values. Retain the estimate and uncertainty as the authors report them, along with the missing-data method and unresolved assumption. It is reasonable to ask for an explanation when an apparently complete table conceals how its entries were obtained.

Personal progress records serve a different task. A blank day remains unknown unless you can recover actual information; borrowing a statistical term does not turn a guess into a measurement. For health decisions involving the paper, seek qualified interpretation of the full evidence. This guide’s output is provenance for analyzed values, not a new analysis or a clinical conclusion.