To examine the familial correlations, heritability (h ²) and common environmental components (c ²) of myopia and ocular biometric traits (all treated as continuous outcomes) in families collected through the Genes in Myopia (GEM) family study in Australia. A total of 132 pedigrees (723 participants) were recruited for this study. All individuals completed a risk factor questionnaire and underwent a detailed eye examination including spherical equivalent (SphE) and ocular biometric measurements of axial length (AL), anterior chamber depth (ACD) and corneal curvature (CC). Familial correlations were calculated and h ² and c² were estimated using a variance component model that assumes a multivariate t distribution within each pedigree. Two definitions of common environments (c ²) were considered: nuclear family (current) shared environment (Model 1) and sib-ship (childhood) shared environment (Model 2). Population ascertainment adjustment was performed using the Blue Mountains eye study dataset. The trends observed for familial correlations suggested that SphE is influenced by both environmental and genetic factors whereas AL, ACD and CC are predominantly genetically determined. This was largely confirmed by variance components modelling. Heritability estimates (adjusted for age, sex and years of education) from the best fitting ACE model (Model 2, childhood shared environment) were 0.50 ± 0.05 for SphE, 0.73 ± 0.04 for AL, 0.78 ± 0.04 for ACD and 0.16 ± 0.06 for CC. Childhood environmental effects were significant with c ² estimated to be 0.33 ± 0.04 for SphE, 0.06 ± 0.03 for AL, 0.22 ± 0.04 for ACD and 0.10 ± 0.05 for CC. Age was associated with SphE, total years of education was associated with AL and sex was associated with all traits studied. We used a novel and conservative approach to account for and estimate common environmental effects by specifying either nuclear family or sib-ship environment when estimating heritability estimates and showed that all traits examined (SphE, AL, ACD and CC) are heritable, thus reflecting a genetic component. These traits therefore all represent candidates for quantitative trait linkage analyses.