An efficacy evaluation method for non-normal outcomes in randomized controlled trials

Scientific Reports
Yang LiFang Lu

Abstract

Randomized controlled trials (RCT) are widely used in clinical efficacy evaluation studies. Linear regression is a general method to evaluate treatment efficacy considering the existence of confounding variables. However, when residuals are not normally distributed, parameter estimation based on ordinary least squares (OLS) is inefficient. This study introduces an exponential squared loss (ESL) model to evaluate treatment effect. The proposed method provides robust estimation for non-normal data. Simulation results show that it outperforms ordinary least squares regression with contaminated data. In the mild cognitive impairment (MCI) efficacy evaluation study with traditional Chinese medicine, our method is applied to construct a linear efficacy evaluation model for the difference in Alzheimer's disease assessment scale-cognitive (ADAS-cog) scores between the final and baseline records (ADASFA), with the existence of confounding factors and non- normal residuals. The results coincide with existing medical literatures. This proposed method overcomes the limitation of confounding variables and non-normal residuals in RCT efficacy studies. It outperforms OLS on estimation efficiency in situations where the percentage of non-norma...Continue Reading

References

Apr 15, 2005·The New England Journal of Medicine·Ronald C PetersenUNKNOWN Alzheimer's Disease Cooperative Study Group
Apr 25, 2006·Lancet·Serge GauthierUNKNOWN International Psychogeriatric Association Expert Conference on mild cognitive impairment
May 12, 2009·Alzheimer's & Dementia : the Journal of the Alzheimer's Association·UNKNOWN Alzheimer's Association
Aug 6, 2013·Journal of the American Statistical Association·Xueqin WangHeping Zhang
Apr 24, 2014·Movement Disorders : Official Journal of the Movement Disorder Society·Murat EmreErgun Y Uç

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