Multivariate logistic regression for familial aggregation of two disorders. I. Development of models and methods

American Journal of Epidemiology

Volumn 153, Issue 5, 2001, Pages 500-505

  Hudson, James I ^a,b,c   Laird, Nan M ^c   Betensky, Rebecca A ^c  

^a MCLEAN HOSPITAL   (United States)

^b HARVARD MEDICAL SCHOOL   (United States)

^c HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

Family; Family characteristics; Generalized estimating equation; Logistic models

Indexed keywords

ARTICLE; CASE CONTROL STUDY; COMPUTER PROGRAM; FAMILIAL DISEASE; REGRESSION ANALYSIS; RISK ASSESSMENT; STATISTICAL MODEL;

FAMILY; GENETIC PREDISPOSITION TO DISEASE; HUMANS; LOGISTIC MODELS; MULTIVARIATE ANALYSIS; PREDICTIVE VALUE OF TESTS;

EID: 0035283435     PISSN: 00029262     EISSN: None     Source Type: Journal    
DOI: 10.1093/aje/153.5.500     Document Type: Article

References (19)

1. Methods in psychiatric genetics
2. Multivariate regression for familial aggregation of two disorders: II. Analysis of studies of eating and mood disorders
3. The analysis of case-control data: Epidemiologic studies of familial aggregation
4. Bias in using family history as a risk factor in case-control studies of disease
5. Longitudinal data analysis using generalized linear models
6. Analysis of longitudinal data
7. Analysis of case-control/family sampling design
8. Combined association and aggregation analysis of data from case-control family studies
9. Correlated binary regression using a quadratic exponential model
10. An analysis of correlated multivariate binary data: Application to familial cancers of the ovary and breast
11. Genetic analysis workshop II: Pedigree analysis of a binary trait without assuming an underlying liability
12. Conditional logistic regression models for correlated binary data
13. Logistic regression of family data from case-control studies
14. A controlled family history study of bulimia
15. The relationship between panic disorder and major depression: A new family study
16. Familial transmission of substance use disorders
17. An exponential family model for clustered multivariate binary data
18. Is seeking treatment for depression predicted by a history of depression in relatives? Implications for family studies of affective disorder