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Statistical analysis of two arm randomized pre-post designs with one post-treatment measurement
by
Wan, Fei
in
Analysis of covariance
/ ANCOVA
/ ANOVA
/ Change score
/ Design
/ Health Sciences
/ Medical research
/ Medicine
/ Medicine & Public Health
/ Pre-post design
/ Repeated measures
/ Research methodology
/ Statistical methods
/ Statistical Theory and Methods
/ Statistics for Life Sciences
/ Theory of Medicine/Bioethics
/ Treatment effect
/ Variance analysis
/ Within-subjects design
/ Women
2021
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Statistical analysis of two arm randomized pre-post designs with one post-treatment measurement
by
Wan, Fei
in
Analysis of covariance
/ ANCOVA
/ ANOVA
/ Change score
/ Design
/ Health Sciences
/ Medical research
/ Medicine
/ Medicine & Public Health
/ Pre-post design
/ Repeated measures
/ Research methodology
/ Statistical methods
/ Statistical Theory and Methods
/ Statistics for Life Sciences
/ Theory of Medicine/Bioethics
/ Treatment effect
/ Variance analysis
/ Within-subjects design
/ Women
2021
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Statistical analysis of two arm randomized pre-post designs with one post-treatment measurement
by
Wan, Fei
in
Analysis of covariance
/ ANCOVA
/ ANOVA
/ Change score
/ Design
/ Health Sciences
/ Medical research
/ Medicine
/ Medicine & Public Health
/ Pre-post design
/ Repeated measures
/ Research methodology
/ Statistical methods
/ Statistical Theory and Methods
/ Statistics for Life Sciences
/ Theory of Medicine/Bioethics
/ Treatment effect
/ Variance analysis
/ Within-subjects design
/ Women
2021
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Statistical analysis of two arm randomized pre-post designs with one post-treatment measurement
Journal Article
Statistical analysis of two arm randomized pre-post designs with one post-treatment measurement
2021
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Overview
Background
Randomized pre-post designs, with outcomes measured at baseline and after treatment, 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 designs. It is challenging for applied researchers to make an informed choice.
Methods
We discuss six methods commonly used in literature: one way analysis of variance (“
ANOVA”
)
, analysis of covariance main effect and interaction models on the post-treatment score (“
ANCOVA
I
” and “
ANCOVA
II
”),
ANOVA
on the change score between the baseline and post-treatment scores (“
ANOVA-Change
”), repeated measures (“
RM”
) and constrained repeated measures (“
cRM”
) models on the baseline and post-treatment scores as joint outcomes. We review a number of study endpoints in randomized pre-post designs and identify the mean difference in the post-treatment score as the common treatment effect that all six methods target. We delineate the underlying differences and connections between these competing methods in homogeneous and heterogeneous study populations.
Results
ANCOVA
and
cRM
outperform other alternative methods because their treatment effect estimators have the smallest variances.
cRM
has comparable performance to
ANCOVA
I
in the homogeneous scenario and to
ANCOVA
II
in the heterogeneous scenario. In spite of that,
ANCOVA
has several advantages over
cRM:
i) the baseline score is adjusted as covariate because it is not an outcome by definition; ii) it is very convenient to incorporate other baseline variables and easy to handle complex heteroscedasticity patterns in a linear regression framework.
Conclusions
ANCOVA
is a simple and the most efficient approach for analyzing pre-post randomized designs.
Publisher
BioMed Central,Springer Nature B.V,BMC
Subject
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