Specifically, since most missing data required median imputation, the prespecified median imputation rules can be considered to have conservatively favoured the placebo group due to a higher proportion of placebo patients having a score of 0 applied to missing data.
Even though half of the simulated alignments had between 50% and 60% missing data, the median stQD for the NJ and ML trees were 0, and the median stQD for the MP trees was 0.004.
For categorical variables, the description will consist (at minimum) of the sample size; numbers of missing data; valid data, median, upper and lower quartiles; and the frequency and percentage of each category.
L/Es, lower extremities *Percentage may not add up to 100 related to missing data; † Median = 27 days, Q1 = 17 days, Q3 = 40 days, mode = 21 days NWB, no weight bearing; TWB, touch weight bearing; PWB, partial weight bearing; WBAT, weight bearing as tolerated The unadjusted relationships between LOS and all potential predictors are summarized in Table 3.
With the exception of month of questionnaire return, we used missing indicators when covariate data were missing for more than 2% of our sample and replaced missing data with median or mode values when covariate data were missing in less than 2% of our sample.
Regarding their comments on missing data, the median follow-up time after completing treatment seems to have escaped their attention, as it was provided for all survivors and for separate treatment groups in Table 2 of our published article (Willemse et al, 2013).
In no cases were more than 10% of the responses missing [ 21] but when that occurred, median substitution was performed by replacing missing data with the median value within the components of SOC (i.e. Comprehensibility, Manageability and Meaningfulness).
We imputed the missing data with the median value of height, weight, and/or weight gain.
Values in parentheses are percentages unless indicated otherwise; frequency values may not always total 100% due to missing data; †values are median [percentiles].
Our objective was to quantify the effect of different statistical techniques, inclusion/exclusion criteria, and missing data on the predicted median survival age.
