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The Prevention and Treatment of Missing Data in Clinical Trials
ity analysis and principled decision making based on the results fromsensitivity analyses, (2) analysis of data where the missingness patternis nonmonotone, (3) sample size calculations in the presence of missingdata, (4) design of clinical trials, in particular plans for follow-up aftertreatment discontinuation (degree of sampling, how many attempts aremade, etc.), and (5) doable robust methods, to more clearly understandtheir strengths and vulnerabilities in practical settings. The development of software that supports coherent missing data analyses is alsoa high priority.