Predicting pregnancy outcomes using longitudinal information: a penalized splines mixed-effects model approach-Reference-Cited by-同舟云学术

Predicting pregnancy outcomes using longitudinal information: a penalized splines mixed-effects model approach

Published:2017-02-19 Issue:13 Volume:36 Page:2120-2134
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statist. Med.

Author:

De la Cruz Rolando¹^ORCID,Fuentes Claudio²,Meza Cristian³,Lee Dae-Jin⁴,Arribas-Gil Ana⁵

Affiliation:

1. Instituto de Estadística; Pontificia Universidad Católica de Valparaíso; Valparaíso Chile

2. Department of Statistics; Oregon State University; Corvallis OR U.S.A.

3. CIMFAV - Facultad de Ingeniería; Universidad de Valparaíso; Valparaíso Chile

4. BCAM - Basque Centre for Applied Mathematics; Bilbao Basque Country Spain

5. Departamento de Estadística; Universidad Carlos III de Madrid; Getafe Spain

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

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3. Doubling time of human chorionic gonadotropin (HCG) in early normal pregnancy: relationship to hcg concentration and gestational age;Frits;Fertility and Sterility,1987

4. Functional data analysis for sparse longitudinal data;Yao;Journal of the American Statistical Association,2005

5. Functional linear regression analysis for longitudinal data;Yao;Annals of Statistics,2005

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