Longitudinal analysis of pre‐ and post‐treatment measurements with equal baseline assumptions in randomized trials
| Autor: | Takashi Funatogawa, Ikuko Funatogawa |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Statistics and Probability
Biometry Bivariate analysis 01 natural sciences law.invention repeated measure 010104 statistics & probability 03 medical and health sciences 0302 clinical medicine Randomized controlled trial law Statistics pretest Humans 030212 general & internal medicine Longitudinal Studies 0101 mathematics Baseline (configuration management) Pre and post Mathematics analysis of covariance Randomized Controlled Trials as Topic Analysis of covariance posttest Estimator longitudinal analysis General Medicine Research Papers Sample size determination unequal variance Statistics Probability and Uncertainty Type I and type II errors Research Paper |
| Zdroj: | Biometrical Journal. Biometrische Zeitschrift |
| ISSN: | 1521-4036 0323-3847 |
| Popis: | 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 baseline means performed well in large sample sizes. We also compared asymptotic properties of longitudinal models with those of the analysis of covariance (ANCOVA) and t‐test. |
| Databáze: | OpenAIRE |
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