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. 2003 Dec 31;4(Suppl 1):S21. doi: 10.1186/1471-2156-4-S1-S21

Table 2.

Weighted segregation analysis of slopes*

Hypothesis

Mendelian

Segregation Parameter General Codominant Dominant Recessive Additive No Major Gene
Estimate SE Estimate SE Estimate SE Estimate SE Estimate SE Estimate SE

Intercept 3.205 0.1814 3.500 0.1932 3.790 0.2246 4.139 0.1489 3.744 0.2081 4.265 0.1485
βcohort -3.541 0.2393 -3.819 0.2094 -3.785 0.2092 -3.788 0.2143 -3.793 0.2090 -3.726 0.2113
βSex -1.621 0.1981 -1.623 0.1965 -1.584 0.2001 -1.682 0.1907 -1.580 0.1897 -1.620 0.1936
βAA 16.614 1.7795 16.625 2.4421 6.742 1.2112 14.296 2.1622 12.821 2.1109
βAa 4.443 0.5003 3.525 0.8312 6.742A 0.000B 6.411C
q A 0.199 0.0584 0.110 0.0265 0.042 0.0195 0.130 0.0269 0.047 0.0188
σ2 0.485 0.1782 1.849 0.5964 2.384 0.7088 3.384 0.5886 2.206 0.5857 4.949 0.6492
τaa 0.000 0.0000 0.000D 0.000D 0.000D 0.000D
τAa 0.390 0.0694 0.500D 0.500D 0.500D 0.500D
τAA 0.000 0.0000 1.000D 1.000D 1.000D 1.000D

-2(log-likelihood) 17811.58 17824.66 17839.45 17828.49 17837.35 17867.83
p-valueE < 0.001 < 0.001 < 0.001 < 0.001 < 0.001
AICF 17831.58 17838.66 17851.45 17840.49 17849.35 17875.83

*The outcome being modeled in equation (2) is 1000 × bi, the subject-specific slope from equation (1). AConstrained to equal βAA. BConstrained to equal 0. CConstrained to equal 1/2 βAA. DParameter value is fixed. Ep-value based on a likelihood ratio test with the general model as the base model.FAIC = -2(log-likelihood) + 2(number of free parameters).