Ned A Dochtermann
Biographic Data
| ID | 10708473 |
|---|---|
| NAME | Ned A Dochtermann |
| GIVEN NAMES | Ned A |
| FAMILY NAME | Dochtermann |
| SIGNATURE | DOCHTERMANN N A |
| AFFILIATIONS | North Dakota State University |
| ORCID | 0000-0002-8370-4614 |
| VERIFIED | No |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 1 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2020 |
| H-INDEX | 0 |
Robustness of linear mixed‐effects models to violations of distributional assumptions
Linear mixed‐effects models are powerful tools for analysing complex datasets with repeated or clustered observations, a common data structure in ecology and evolution. Mixed‐effects models involve complex fitting procedures and make several assumptions, in particular about the distribution of residual and random effects. Violations of these assumptions are common in real datasets, yet it is not always clear how much these violations matter to ac…
No prominent works on this page.
Robustness of linear mixed‐effects models to violations of distributional assumptions
Linear mixed‐effects models are powerful tools for analysing complex datasets with repeated or clustered observations, a common data structure in ecology and evolution. Mixed‐effects models involve complex fitting procedures and make several assumptions, in particular about the distribution of residual and random effects. Violations of these assumptions are common in real datasets, yet it is not always clear how much these violations matter to ac…
Algorithm (1 work) · Artificial Intelligence (1 work) · Best linear unbiased prediction (1 work) · Computer Science (1 work) · Ecology and Vegetation Dynamics Studies (1 work) · Econometrics (1 work) · Heteroscedasticity (1 work) · Mathematics (1 work) · Mixed model (1 work) · Plant and animal studies (1 work)