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This tackles the missing value issue in microarrays in a probabilistic framework and still enables a posteriori inference of incomplete observations without imposing any pre-processing of the data.
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A detailed statistical analysis plan (SAP) will be defined in advance to the final analysis, to fix detailed statistical considerations with regard to further data analyses, multiple test issue, missing value imputation and sensitivity analyses.
g1 missing value.
*One missing value.
* One missing value LIPUS.
In other cases, the conversion of biological data can be more challenging, due to for example the complex structure of many biological datasets, their often stochastic nature, the presence of missing values and scaling issues.
In the time-point approach, however, the input file is the list of genes that belong to a specific time-point, in which case the number of missing values is not an issue.
As observed in our previous studies, missing values are a serious issue for scoring function optimization.
Missing values are an inevitable issue in many proteomics studies.
Missing values became a significant issue at the 30-month follow-up assessment, thus potentially diminishing the randomized treatment group comparison.
However, due to missing values, secondary to technical issues, data from only 18 subjects were included in %MHR calculations.
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