2021
DOI: 10.1002/sim.9092
|View full text |Cite
|
Sign up to set email alerts
|

Analysis of covariance under variance heteroscedasticity in general factorial designs

Abstract: Adjusting for baseline values and covariates is a recurrent statistical problem in medical science. In particular, variance heteroscedasticity is non‐negligible in experimental designs and ignoring it might result in false conclusions. Approximate inference methods are developed to test null hypotheses formulated in terms of adjusted treatment effects and regression parameters in general analysis of covariance designs with arbitrary numbers of factors. Variance homoscedasticity is not assumed. The distribution… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
references
References 16 publications
0
0
0
Order By: Relevance