Table 2.
Coefficients of the covariate adjustment models
| Model | Predictor | Estimated coefficient | 95%a confidence interval |
|---|---|---|---|
| SpAvg | Intercept | 87.71 | (84.47, 90.95) |
| Age (months) | 0.06 | (0.04, 0.08) | |
| Cohort | 12.28 | (7.62, 16.93) | |
| Sex | −6.88 | (−8.11, −5.65) | |
| (Age)(Cohort) | −0.05 | (−0.07, −0.03) | |
| SpAvg(VIQ) | Intercept | 26.73 | (21.08, 32.39) |
| Age (months) | 0.08 | (0.06, 0.10) | |
| Cohort | 19.92 | (15.84, 24.00) | |
| Sex | −7.04 | (−8.11, −5.98) | |
| (Age)(Cohort) | −0.08 | (−0.10, −0.06) | |
| VIQ | 0.53 | (0.49, 0.58) |
a
Because we do not account for relatedness in the linear adjustment model, the variance of the regression coefficients is underestimated, and the true coverage of the confidence intervals is likely to be less than 95%. The estimates of the coefficients themselves are not affected