Karin Groothuis‐Oudshoorn
Biographic Data
| ID | 4976049 |
|---|---|
| NAME | Karin Groothuis‐Oudshoorn |
| GIVEN NAMES | Karin |
| FAMILY NAME | Groothuis‐Oudshoorn |
| SIGNATURE | OUDSHOORN K G |
| AFFILIATIONS | University of Twente |
| ORCID | 0000-0002-4875-5379 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2006 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 0 |
The Icecap-A instrument for capabilities
In summary, results suggest adequate test-retest reliability and construct validity and indicate that the ICECAP-A might be of added value, especially when considering areas outside of the traditional health intervention model
Statistical Methods for the Analysis of Discrete Choice Experiments
Insufficient vitamin D supplement use during pregnancy and early childhood
Vitamin D insufficiency during pregnancy is associated with disturbed skeletal homeostasis during infancy. Our aim was to investigate the influence of adherence to recommendations for vitamin D supplement intake of 10 μg per day (400 IU) during pregnancy (mother) and in the first months of life (child) on the occurrence of positional skull deformation of the child at the age of 2 to 4 months. In an observational case-control study, two hundred se…
Mice
The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R package. mice 1.0 introduced predictor selection, passive imputation and automatic pooling. This article documents mice, which extends the functionality of mice 1.0 in several ways. In mice , the analysis of imputed data is made completely general, whereas the range of models under…
Fully conditional specification in multivariate imputation
The use of the Gibbs sampler with fully conditionally specified models, where the distribution of each variable given the other variables is the starting point, has become a popular method to create imputations in incomplete multivariate data. The theoretical weakness of this approach is that the specified conditional densities can be incompatible, and therefore the stationary distribution to which the Gibbs sampler attempts to converge may not e…
No prominent works on this page.
Fully conditional specification in multivariate imputation
The use of the Gibbs sampler with fully conditionally specified models, where the distribution of each variable given the other variables is the starting point, has become a popular method to create imputations in incomplete multivariate data. The theoretical weakness of this approach is that the specified conditional densities can be incompatible, and therefore the stationary distribution to which the Gibbs sampler attempts to converge may not e…
Mice
The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R package. mice 1.0 introduced predictor selection, passive imputation and automatic pooling. This article documents mice, which extends the functionality of mice 1.0 in several ways. In mice , the analysis of imputed data is made completely general, whereas the range of models under…
Insufficient vitamin D supplement use during pregnancy and early childhood
Vitamin D insufficiency during pregnancy is associated with disturbed skeletal homeostasis during infancy. Our aim was to investigate the influence of adherence to recommendations for vitamin D supplement intake of 10 μg per day (400 IU) during pregnancy (mother) and in the first months of life (child) on the occurrence of positional skull deformation of the child at the age of 2 to 4 months. In an observational case-control study, two hundred se…
Statistical Methods for the Analysis of Discrete Choice Experiments
The Icecap-A instrument for capabilities
In summary, results suggest adequate test-retest reliability and construct validity and indicate that the ICECAP-A might be of added value, especially when considering areas outside of the traditional health intervention model
Computer Science (3 works) · Econometrics (2 works) · Imputation (statistics) (2 works) · Mathematics (2 works) · Medicine (2 works) · Missing data (2 works) · Multivariate statistics (2 works) · Statistical Methods and Bayesian Inference (2 works) · Statistics (2 works) · Advanced Statistical Methods and Models (1 work)