Statistical analysis of two arm randomized pre-post design with one post-treatment measurement

07/15/2020
by   Fei Wan, et al.
0

Randomized pre-post designs, with outcomes measured at baseline and follow-ups, have been commonly used to compare the clinical effectiveness of two competing treatments. There are vast, but often conflicting, amount of information in current literature about the best analytic methods for pre-post design. It is challenging for applied researchers to make an informed choice. We discuss six methods commonly used in literature: one way analysis of variance (ANOVA), analysis of covariance main effect and interaction models on post-treatment measurement (ANCOVA I and II), ANOVA on change score between baseline and post-treatment measurements, repeated measures and constrained repeated measures models (cRM) on baseline and post-treatment measurements as joint outcomes. We review a number of study endpoints in pre-post designs and identify the difference in post-treatment measurement as the common treatment effect that all six methods target. We delineate the underlying differences and links between these competing methods in homogeneous and heterogeneous study population. We demonstrate that ANCOVA and cRM outperform other alternatives because their treatment effect estimators have the smallest variances. cRM has comparable performance to ANCOVA I main effect model in homogeneous scenario and to ANCOVA II interaction model in heterogeneous scenario. In spite of that, ANCOVA has several advantages over cRM, including treating baseline measurement as covariate because it is not an outcome by definition, the convenience of incorporating other baseline variables and handling complex heteroscedasticity patterns in a linear regression framework.

READ FULL TEXT

Authors

page 1

page 2

page 3

page 4

08/05/2018

Sampling-based randomized designs for causal inference under the potential outcomes framework

We establish the inferential properties of the mean-difference estimator...
10/18/2021

Robustly leveraging the post-randomization information to improve precision in the analyses of randomized clinical trials

In randomized clinical trials, repeated measures of the outcome are rout...
04/11/2021

Nonparametric Method for Clustered Data in Pre-Post Factorial Design

In repeated measures factorial designs involving clustered units, parame...
11/22/2021

Monotonicity assumptions in estimating the treatment effect for a principal stratum

In addition to the treatment effect for all randomized patients, sometim...
01/04/2021

Conditioning on the pre-test versus gain score modeling: revisiting the controversy in a multilevel setting

We consider estimating the effect of a treatment on the progress of subj...
10/30/2020

Representation Learning for Integrating Multi-domain Outcomes to Optimize Individualized Treatments

For mental disorders, patients' underlying mental states are non-observe...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.