Data were examined by multilevel modeling for repeated measures. This method was chosen, because different observations of the same child may be dependent, and simple regression analysis would not correct for the lack of independence between observations. Many methods for analyzing longitudinal data require the same number of measurements to be collected from every subject (e.g., repeated measures analysis of variance), and for each subject to attend at every period. In a clinical setting, this would have been unrealistic. Therefore, this more appropriate analytical technique was used.
All statistical analysis was performed on computer (SAS, ver. 8; SAS, Cary, NC, for SunOS using the Proc Mixed procedure). Multilevel regression models were used to look at the relationships between AXL, ACD, LT, CC, and RE and age. In addition, the relationship between AXL and RE, ACD and RE, LT and RE, and CC and RE, controlling for age, was analyzed. The multilevel regression methodology allowed for fitting of a linear relationship or a quadratic relationship, as appropriate. Once an appropriate model had been found for the biometric parameters and refractive state, each model was refitted including gender, to identify if at this early stage of ocular development, there was any effect due to gender difference.
Estimates of the intercept (value at term) and slope coefficients (rate of growth) of the fitted relationship are presented with their standard errors. Only the results for the final model for each variable have been presented. The data have been centered so that the intercept parameter always indicates the mean value of the variable of interest at term, namely 40 weeks postmenstrual age. The slope parameter in a linear model indicates the rate of change of the variable, the number of millimeters of change occurring per week. When a quadratic term is included in the model, the coefficient is indicated by how much the rate of change is changing. To find the predicted value of a parameter
y at a given postmenstrual age
x, given the intercept
a the slope coefficient
b and quadratic term
c:
\[y{=}a{+}b\mathrm{(}x{-}\mathrm{40)}{+}c(x{-}\mathrm{40)^{2}}\]
For a linear relationship, the last part of the equation is excluded.