Marginal and dynamic regression models for longitudinal data

Statistics in Medicine

Volumn 20, Issue 21, 2001, Pages 3295-3311

  Schmid, Christopher H ^a  

^a TUFTS UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGE; ARTICLE; BODY HEIGHT; CHILD; CHRONIC OBSTRUCTIVE LUNG DISEASE; CONTROLLED STUDY; DATA ANALYSIS; FEMALE; FORCED EXPIRATORY VOLUME; GENDER; HUMAN; HUMAN EXPERIMENT; LONGITUDINAL STUDY; LUNG FUNCTION; MALE; REGRESSION ANALYSIS; RISK FACTOR; SMOKING; STATISTICAL MODEL; STATISTICAL PARAMETERS;

ADOLESCENT; BIOMETRY; BODY HEIGHT; CHILD; CHILD, PRESCHOOL; FEMALE; FORCED EXPIRATORY VOLUME; HUMANS; LONGITUDINAL STUDIES; MALE; REGRESSION ANALYSIS; RESPIRATORY TRACT DISEASES; RISK FACTORS; SMOKING;

EID: 0035889476     PISSN: 02776715     EISSN: None     Source Type: Journal    
DOI: 10.1002/sim.950     Document Type: Article

References (15)

1. A parametric family of correlation structures for the analysis of longitudinal data
2. Random-effects models for longitudinal data
3. Newton-Raphson and EM algorithms for linear mixed-effects models for repeated-measures data
4. The use of an autoregressive model for the analysis of longitudinal data in epidemiologic studies
5. Autoregressive modelling for the analysis of longitudinal data with unequally spaced examinations
6. Conditional linear models for longitudinal data
7. An EM algorithm fitting first-order conditional autoregressive models to longitudinal data
8. Effect of parental cigarette smoking on the pulmonary function of children
9. Formulation and estimation of dynamic models using panel data