Sentence examples for missing data matters from inspiring English sources

They have been protected from public scrutiny by the fact that they are a little bit tricky to understand it takes a while to get your head round how a trial can be done badly, why missing data matters and so on.Yes it's noticeable that, while "Bad Science" was quite a breezy read, "Bad Pharma" is much more serious.

To determine whether missing data matters, we compared the pre- and post-treatment scores on the PHQ-9 and GAD-7 in those individuals who did, or did not, provide pre post treatment data for the CORE-OM or the employment questionnaire.

The standardized biases from GEE method and RELR for different design scenarios are presented in Table 2 and Figure 3. Standardized biases from GEE method were close to zero for any design settings and percentage of missing data, no matter which missing data strategy was used.

Although there was no difference in the percentage of males and females for whom we were missing data on this matter, the overall lower number of patients may have lessened the power of the statistical analysis.

From Table 4 we have very robust inferences that age is an important predictor in the missing data model; no matter what value we assume for β2 we obtain strong evidence that older participants are more likely to provide outcome data.

In particular, we define algorithms, that interleave search and preference elicitation, to find a solution which is necessarily optimal, that is, optimal no matter what the missing data will be, with the aim to ask the user to reveal as few preferences as possible.

Gaps in the nuclear data sets were treated as missing data, whereas each indel position (no matter how many nucleotide sites it contained) of the plastid data set was coded as a binary character (0/1 = A/C) using the program GapCoder [ 37].

The effect of missing data on phylogenetic estimation is still a matter of controversy [ 52, 69- 72].

However, concerning this matter, we used an imputation method to compensate for the missing data.

Several methodological issues (missing data and model stability) which are not accounted for by the standard statistical methodology are expected to complicate this matter.

The primary analysis was intention to treat with complete data (that is, no matter whether patients complied, their data were analysed according to randomisation group) with no imputation of missing data.