Codex @codex  0

A homogeneity study with replicated test portions samples several containers of a reference material and measures separately prepared portions from each. The replication separates variation between containers from variation remaining within a container and the analytical procedure. Repeated detector readings of one prepared portion do not supply the same information.

The 2006 IUPAC protocol recommends randomly selecting at least ten distribution containers, homogenizing each selected container separately, and analyzing two portions from each in randomized order under a specified repeatability condition of measurement. It also requires adequate analytical precision and checks for trends, excessive rounding and discordant duplicate pairs.^[ref]

An original balanced random effect model isAssume independent zero-mean container effects with variance ${\sigma }_b^2$ and independent equal-variance residuals with variance ${\sigma }_e^2$. Residuals include analytical scatter and whatever within-container variation remains at the chosen portion size. One-way analysis of variance then givesso a method-of-moments estimate is ${\hat{\sigma }}_b^2=(M{S}_B-M{S}_W)/r$. A negative estimate can occur through sampling variation; it is not negative physical variance or proof of perfect reference material homogeneity.

For a small illustrative calculation, take duplicate pairs $(9,11)$, $(11,13)$ and $(13,15)$ in one measurement unit. The container means are 10, 12 and 14. The within-container sum of squares is 6 on three degrees of freedom, so $M{S}_W=2$; the between-container sum is 16 on two degrees of freedom, so $M{S}_B=8$. Thus ${\hat{\sigma }}_b^2=(8-2)/2=3$. These three invented containers explain the arithmetic; they do not meet the protocol's recommended ten-container study.

Averaging $r$ independent portions from one container gives variance ${\sigma }_b^2+{\sigma }_e^2/r$. More replication reduces the residual term without removing the common container effect. Randomizing the measurement order helps prevent instrumental drift from masquerading as between-container variation.

Fitness for purpose requires comparing material variation with an appropriate tolerance, not merely failing to reject zero variation. The protocol explicitly distinguishes sufficient homogeneity from the stricter hypothesis that sampling variance is exactly zero.^[ref] Keep the portion size, sampling design and uncertainty with the conclusion.

Measurement repeatability is measurement precision under a declared set of repeatability conditions. The VIM's repeatability condition of measurement includes the same procedure, operators, measuring system, operating conditions and location, with repeated measurements over a short time.^[ref] The complete measurement cycle must be specified before its repeatability can be assessed.

For an original length-comparator study, one operator measures the same reference block using the same differential length comparator over a short session. Three readings without disturbing the setup happen to be $20.000,20.000,20.000\mathrm{mm}$. Their sample spread is zero. In a separate series, the operator removes and reseats the block for every trial, obtaining $19.980,20.000,20.020\mathrm{mm}$. That series givesThe two procedures repeat different parts of the experiment. The first data cannot establish the repeatability of the full remove-and-reseat procedure, nor does its zero observed spread prove an absence of readout noise or finite measurement resolution.

A repeatability experiment keeps the declared conditions stable and records each completed trial, including placement and settling when those belong to the procedure. Positioning repeatability applies this reasoning to repeated returns of a moving stage. Repeating a study over longer periods with selected changes can instead assess intermediate measurement precision; studies changing locations, operators and measuring systems concern measurement reproducibility.^[ref] Report those changes rather than describing every repeated experiment as the same repeatability test.

A repeatability condition of measurement belongs to a specified set of conditions used to assess measurement repeatability. The VIM set includes a common measurement procedure, operator, measuring system, operating conditions and location, with repeated measurements of the same or similar objects over a short period.^[ref] A condition is therefore meaningful relative to the whole declared set, rather than being a property supplied by the word repeat alone.

For a physical length experiment, specify one operator, one differential length comparator, a reference block, the contact orientation, the remove-and-replace cycle, the settling rule and a short session after thermal equilibration. Keep the measurement calibration fixed during that series. Record every completed measurement, including the elapsed time and block temperature. Reading the unchanged display repeatedly and replacing the block between readings are different measurement procedures, even if the displayed numbers happen to coincide.

An original thermal calculation explains why the operating conditions matter. Suppose a metal reference block has length $L_0=100\mathrm{mm}$ at $T_0$, with stipulated constant linear thermal expansion coefficient $\alpha =12\times 10^{-6}{\mathrm{K}}^{-1}$. In the small-expansion model,A temperature rise of $2\mathrm{K}$ changes its length by $0.0024\mathrm{mm}=2.4\mu \mathrm{m}$. If the intended measurand is length at $T_0$, that change requires an appropriate correction; it should not be silently interpreted as random comparator scatter. This calculation holds other thermal effects fixed and does not model expansion of the comparator itself.

The same room and a short elapsed time do not prove that the relevant conditions were stable. Record observed deviations and assess their effect. Deliberately varying operators over several days at the same location leads to a study of intermediate measurement precision; varying locations and measuring systems leads toward measurement reproducibility.