Longitudinal analysis of pre- and post-treatment measurements with equal baseline assumptions in randomized trials

Biometrical Journal. Biometrische Zeitschrift
Ikuko Funatogawa, Takashi Funatogawa

Abstract

For continuous variables of randomized controlled trials, recently, longitudinal analysis of pre- and posttreatment measurements as bivariate responses is one of analytical methods to compare two treatment groups. Under random allocation, means and variances of pretreatment measurements are expected to be equal between groups, but covariances and posttreatment variances are not. Under random allocation with unequal covariances and posttreatment variances, we compared asymptotic variances of the treatment effect estimators in three longitudinal models. The data-generating model has equal baseline means and variances, and unequal covariances and posttreatment variances. The model with equal baseline means and unequal variance-covariance matrices has a redundant parameter. In large sample sizes, these two models keep a nominal type I error rate and have high efficiency. The model with equal baseline means and equal variance-covariance matrices wrongly assumes equal covariances and posttreatment variances. Only under equal sample sizes, this model keeps a nominal type I error rate. This model has the same high efficiency with the data-generating model under equal sample sizes. In conclusion, longitudinal analysis with equal baselin...Continue Reading

References

May 11, 2001·The New England Journal of Medicine·W J RoganUNKNOWN Treatment of Lead-Exposed Children Trial Group
May 29, 2004·Nutrition·Garrett Fitzmaurice
May 26, 2007·Contemporary Clinical Trials·Bjorn WinkensMartijn P F Berger
Sep 3, 2011·Biometrical Journal. Biometrische Zeitschrift·Ikuko Funatogawa, Takashi Funatogawa

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