儿童的发育是整个生命过程中健康的一个基本决定因素。最初的生命年构成了一个阶段，在这个阶段，儿童有相当大的机会易受伤害，并成长为受到伤害的人。儿童的发展轨迹是通过韧性来源和脆弱性来形成的(Hoddinott et al.， 2008)。与具有保护作用的个人风险或因素相比，累积经验是儿童幸福发展的一个重要决定因素。早期发展的机会为儿童的学业成功、健康和共同福祉奠定了必不可少的基础。以儿童发展为基础的关键维度提供了个性化的规则，允许儿童形成早期的关系，即定位、获取知识和专注于特定技能的发展。
本研究采用的主要研究设计为回归不连续设计。本设计是基于测试前后的数据实验，得出干预措施之间的因果关系，帮助分配截止点或阈值点。从这个角度，我们比较了来自任何一个截止阈值点的观察结果，以估计干预和治疗的影响(Engle et al . 2011)。这样的设计为本研究提供了不同的好处，因为他们提供了稳健性，令人信服的估计因果影响在相当弱的情况下或最小假设考虑。例如，RDD来自研究数据，其中需要对x轴进行连续评分。这个x轴与边界的距离是特定的。此外，作为一种方法，RDD有助于评估参与的影响以及所涉及的因变量和自变量之间的关系。这种方法是灵活的，因为它提供了评估长期或短期结果的能力，即使它可以与经度的另一个组件协作(Almond et al.， 2011)。该方法在该领域得到了广泛的应用，取得了较好的效度和信度。这些措施之间的有效性是通过比额表项目与项目评分之间较高的关系得到支持的。这对于从国家认可的专家小组的角度，以及通过专家进行的量表评分和课堂评分之间的理解具有特殊的意义。内部一致性，通过Cronbach alpha评估工具测量，通过有效范围小于1的作者报告。
Development in children is an essential determinant of health throughout the course of life. The initial life years constitute a phase wherein there are considerable opportunities for children to be vulnerable and grow towards harm. Developmental trajectories in children are shaped through resilience sources along with vulnerabilities (Hoddinott et al., 2008). The buffers cumulative experience is an essential determining factor for well-being development of children in comparison to individual risks or factors that are protective. Opportunities for early development result in establishing an essential base for academic success, health and common well-being of children. Child development based critical dimensions offer individual regulations which allow the children to form early relationships that are position, acquire knowledge and focus on specific skills development.
Main research question
Contribution of project to literature
Research design and empirical strategy
Programs for early childhood development have been recommended based upon strong evidence of their effective implementation in the context of Bolivia.
The key research design adopted for the purpose of this research is regression discontinuity design. This design is based on experimentation of data before and after the test to draw out causal relationship between interventions that help assign cut-offs or points for threshold. With this perspective, the observations have been compared from any of the cut-off threshold points to estimate the influence of intervention and treatment (Engle et al 2011). Such a design has offered diverse benefits to this study as they offered robustness, convincing estimates for causal influence under fairly weaker circumstances or minimum assumption considered. For example, RDD is from the study’s data wherein continuous scoring requires to be done for the x-axis. This x axis is at a specific distance from border. Furthermore, RDD as a methodology helps in assessing the influence of participation and the relationship between the dependent and independent variables involved. The approach is flexible in the sense that it provides an ability to either estimate long term or short term results, even though it can be collaborated with another component for longitude (Almond et al., 2011). The method has been used in this field in an extensive manner and has results in allowing the research a better validity and reliability. The validity between the measures is supported through higher relationships between the scale items and item ratings. This is of specific significance when understanding from the perspective of nationally recognized panel experts and between scores for scaling as well as classroom ratings through experts. Consistency internally, as measured through the tool for Cronbach alpha assessment, was reported through authors with a valid range of less than 1.