Table 4

Logistic regression coefficients for the missing data model.

Model

α^A

M_i,j-1

M_i,j-2

M_sp,j

M_sp,j-1

M_sp,j-2

NA_mo

NA_fa

CHOL_ij

WT_ij

OC_i

MS_ij

Visit (j)

1

-3.88

2.390

1.58

1.06

-0.005

0.003

0.093

0.297

0.0256

2

-4.36

2.650

1.85

0.86

3.83

-1.42

-1.13

-0.005

0.003

0.121

0.770

0.0213

3

-3.87

2.380

1.58

1.06

-0.010

-0.005

0.003

0.092

0.297

0.0256

4

-4.35

2.650

1.85

0.86

3.82

-1.14

-1.13

0.054

-0.005

0.003

0.120

0.770

0.0214

5

-1.52

0.919

1.80

0.87

0.88

-0.18

-0.41

-0.005

0.003

0.224

-0.4510

6

-1.71

0.903

1.74

1.710

0.64

0.73

-0.17

-0.31

-0.005

0.003

-0.4490

^Aα, intercept; M_ij, indicator for subject i's visit j being missing (with i replaced by sp, mo, fa, sib for spouse, mother, father, and sib respectively); , average missingness proportion for subject i up to and including visit j (if the second subscript is omitted, the average is taken over the entire history); MS, marital status; NA, indicator for parents' being not available in the data set; OC, only child; CHOL, cholesterol; WT, weight.

Daw et al. BMC Genetics 2003 4(Suppl 1):S3   doi:10.1186/1471-2156-4-S1-S3