Sentence examples for missing data allocation from inspiring English sources

A last observed carried forward strategy was used, and sensitivity analysis was carried out by comparing with results based on two other missing data allocation techniques (summary statistics and mixed model analysis).

We tested stability of the results using all trials, excluding and including debatable trials, by comparing the results of full intention to treat with restricted intention to treat and per protocol analysis and by comparing the last observation carried forward with missing data allocation based on summary statistics.

Recruitment numbers, reasons for not being eligible or enrolled as well as allocation, missing data and reasons for missing data are reported in the CONSORT flow diagram.

In order to investigate how the quality of the allocations (measured by the standard deviation between the means of the groups) depends on the percentage of missing answers, we compared the quality of the allocations without missing data to the quality of the allocations obtained when removing a percentage of answers for relationships or prognostic factors.

After excluding such patients and those with missing data, 2,673 people fulfilled the criteria for allocation to subgroups.

The general approach for between-group comparisons was to analyse participants according to allocation without imputation of missing data.

The 11 included trials were of variable methodological quality; the major methodological defects being the failure to provide details of allocation concealment, addressing the missing data etc.

Many RCTs had missing data especially on the domains of sequence generation, allocation concealment and blinding.

The specific data extracted on study design included evaluation of adequacy of methods of randomization (sequence generation), allocation concealment, blinding and dealing with missing data.

The risk of bias for each study can be determined by assessing the following six domains: 1. sequence generation, 2. allocation concealment, 3. blinding, 4. missing data, 5. selective outcome reporting, and 6. other sources of bias [ 31].

The correlation between the risk of bias tool and the Schulz or Jadad approaches was significant in some domains (sequence generation or randomisation, allocation concealment, blinding) but not others (missing data, overall scores).