The fallacy of single imputation for trait databases: Use multiple imputation instead
Abstract The past few years have seen the publication of many new trait databases. A common problem with large databases is a lack of completeness, or inversely, the high prevalence of missing values. Biologists have developed several methods to impute (fill in) missing values. This allows ordinary...
Saved in:
| Main Authors: | Simone P. Blomberg, Orlin S. Todorov |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-04-01
|
| Series: | Methods in Ecology and Evolution |
| Subjects: | |
| Online Access: | https://doi.org/10.1111/2041-210X.14494 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
How much missing data is too much to impute for longitudinal health indicators? A preliminary guideline for the choice of the extent of missing proportion to impute with multiple imputation by chained equations
by: K. P. Junaid, et al.
Published: (2025-02-01) -
Bridging the Gap: Missing Data Imputation Methods and Their Effect on Dementia Classification Performance
by: Federica Aracri, et al.
Published: (2025-06-01) -
Two-stage multiple imputation with a longitudinal composite variable
by: Xuzhi Wang, et al.
Published: (2025-05-01) -
Navigating the missing data maze: exploring multiple imputation techniques for environmental performance index data
by: Muhammed Haziq Muhammed Nor, et al.
Published: (2025-01-01) -
Evaluating Performance of Missing Data Imputation Methods in IRT Analyses
by: Ömür Kaya Kalkan, et al.
Published: (2018-09-01)