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Is Multiple Imputation in Clinical Trials Worth the Effort?

Statistical Consultancy Team

In a case study examined to look at Multiple Imputation (MI) in clinical trials, comparing Active to Placebo treatment (at Weeks 2, 4, 6 and 12 of the trial) in adolescents with acne, drop outs were common.  The primary endpoint was the number of lesions at Week 12.  The factors believed to affect the propensity to be missing included age, side effects and lack of efficacy, and thus missing data patterns differ between groups. 

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Topics: Statistical Programming, FDA, SAS Programming, Statisticians in the Pharmaceutical Industry (PSI), Propensity Scoring, Multiple Imputation

The Use of Propensity Scoring in Pooling Data across Clinical Trials

Statistical Consultancy Team

A member of Quanticate's statistical consultancy team presented a poster on “Using a Propensity-Pairing Algorithm to Reduce Bias due to Imbalances in Covariates: A Case Study Pooling Data from 5 Kidney Transplant Trials” at a conference for statisticians in the pharmaceutical industry (PSI).  This work uses a range of statistical methods including stepwise logistic regression, conditional logistic regression, principal component scores and mixed modeling.

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Topics: Randomization, Specialist Biometrics CRO, Biostatistics Consulting, Propensity Scoring

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