Parenting behaviors are commonly targeted in early interventions to improve children's language development. Accurate measurement of both parenting behaviors and children's language outcomes is thus crucial for sensitive assessment of intervention outcomes. To date, only a small number of studies have compared parent-reported and directly measured behaviors, and these have been hampered by small sample sizes and inaccurate statistical techniques, such as correlations. The Bland-Altman Method and Reduced Major Axis regression represent more reliable alternatives because they allow us to quantify fixed and proportional bias between measures. In this study, we draw on data from two Australian early childhood cohorts (N = 201 parents and slow-to-talk toddlers aged 24 months; and N = 218 parents and children aged 6-36 months experiencing social adversity) to (1) examine agreement and quantify bias between parent-reported and direct measures, and (2) to determine socio-demographic predictors of the differences between parent-reported and direct measures. Measures of child language and parenting behaviors were collected from parents and their children. Our findings support the utility of the Bland-Altman Method and Reduced Major Axis regression in comparing measurement methods. Results indicated stronger agreement between parent-reported and directly measured child language, and poorer agreement between measures of parenting behaviors. Child age was associated with difference scores for child language; however, the direction varied for each cohort. Parents who rated their child's temperament as more difficult tended to report lower language scores on the parent questionnaire, compared to the directly measured scores. Older parents tended to report lower parenting responsiveness on the parent questionnaire, compared to directly measured scores. Finally, speaking a language other than English was associated with less responsive parenting behaviors on the videotaped observation compared to the parent questionnaire. Variation in patterns of agreement across the distribution of scores highlighted the importance of assessing agreement comprehensively, providing strong evidence that simple correlations are grossly insufficient for method comparisons. We discuss implications for researchers and clinicians, including guidance for measurement selection, and the potential to reduce financial and time-related expenses and improve data quality. Further research is required to determine whether findings described here are reflected in more representative populations.