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Because of the missing baseline assessment in all studies mentioned above, none of these studies can distinguish between selection and program effects.
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Missing baseline assessments were replaced by the median of the baseline assessments and missing post-baseline data were imputed using the last observation carried forward (LOCF) technique.
This method of feature extraction blunts the influence of subject-specific measurement variability and also enables use of data from subjects with missing baseline assessments.
The screening questionnaire, if available, was used in place of a missed baseline assessment.
The 17 patients who were missing baseline LCSS assessments were excluded from the ASBI subgroup analyses.
Patients with missing baseline or week 9 assessments were excluded from the CGI S shift tables.
We excluded re-admissions and cases with missing baseline data.
Firstly, overall mean scores at baseline substituted missing baseline scores.
There were 258 missing baseline viral loads and 25 missing baseline CD4 counts.
Patients with missing baseline values were excluded from these analyses.
Patients missing baseline clinical data were imputed using median values.
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