title: Tips on overlapping confidence intervals and univariate linear models.
abstract: In randomised controlled trials, an overlap of confidence intervals is often cited as evidence of 'no statistically significant difference' between intervention groups. This paper illustrates the limitations of this strategy and compares different univariate linear regression models with baseline and follow-up response measures. The researchers also demonstrate that using 'change in response' or exit score as a function of the baseline response in clinical studies leads to the same results. Further, using a model that includes baseline response as covariate leads to more precise estimates. The implications for future trials are discussed.
authors: Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada.
authors: Adefowope
authors: A
authors: Odueyungbo
authors: Lehana
authors: L
authors: Thabane
authors: Maureen
authors: M
authors: Markle-Reid
mesh_terms: D000704:Analysis of Variance; D015982:Bias; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D006801:Humans; D016014:Linear Models; D015399:Nursing Research; D016032:Randomized Controlled Trials as Topic; D015203:Reproducibility of Results; D012107:Research Design