The phrase "accommodating missing" is not correct and does not convey a clear meaning in written English.
It may be intended to describe a situation where something is being adjusted or made suitable for something that is absent, but the phrasing is awkward and unclear.
Example: "The report was accommodating missing data by providing estimates based on previous trends."
Alternatives: "adjusting for absence" or "making allowances for missing".
The linear mixed model for repeated measurements is effective in accommodating missing data [ 80].
In order to overcome these limitations, they proposed Kalpha, useable for any number of raters, level of measurement, and sample size, accommodating missing data and controlling for chance agreement.
A General Linear Model (GLM) was used to perform univariate analysis of variance (ANOVA) with an unbalanced design (accommodating missing data by the method of median imputation) to assess each of six different eye movement parameters (response variables) using the statistical software package Minitab v.14 (Minitab Inc., Pennsylvania, USA).
The second approach (CEM) is the constrained EM algorithm developed for accommodating missing observations and measurement errors.
To accommodate missing data, multiple imputation (MI) was applied to all end points where missing data were apparent using, specifically, a two-step imputation process with m = 5 imputations per step (29).
For example, AZOrange transforms data formats, scales descriptor values where appropriate, accommodates missing values and selects stopping criteria.
In the absence of a standard method to accommodate missing values, investigators have used a variety of surrogate measures.
Figure 2 displays the methods used to accommodate missing data in the published RCTs.
It is difficult to evaluate the scope of this problem and the appropriateness of investigators' responses to it because there has been no formal quantitative integration of the published information on dropout rates (DORs) and which methods are most commonly used to accommodate missing data in obesity RCTs.
It can also accommodate missing values, which is not the case for many other methods.
The Bi-Level optimization algorithm was structured so as to accommodate missing information on the network kinetics.
