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CHILD CARE ADMINISTRATIVE DATA ANALYSIS

儿童保育行政数据分析

基本信息

批准号：
100032
负责人：
CANDY MILLER
金额：
$ 10万
依托单位：
MARYLAND STATE DEPARTMENT OF EDUCATION
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-09-29 至 2014-09-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/100032
关键词：
CHILD CARE ADMINISTRATIVE DATA ANALYSIS

项目摘要

The proposed project will accomplish three objectives: 1) describe longitudinal patterns in subsidy continuity within Maryland, 2) examine the association between continuity in subsidized care arrangements and the use of high quality care, and 3) analyze the association between new guidance regarding the administration of subsidy redetermination periods and subsidy spell length. Specifically, this project will answer the following research questions: 1) What patterns emerge when examining the continuity of subsidy spells? Do these continuity patterns differ across child, family, and community characteristics? 2) Do children in accredited subsidized care arrangements remain in these providers' care longer than children in non-accredited subsidized arrangements? 3) Does the median length of subsidy spells differ before and after implementation of new guidance regarding 12 month redetermination administrative practices? Research questions will be addressed through the analysis of linked child care subsidy administrative data and provider licensing/accreditation data from June 2007- January 2016. These data will be analyzed using rigorous analytic techniques, including person-centered analyses, propensity score matching, and difference-in-differences analyses. Results will be disaggregated by subgroups that are of interest to state policymakers and child care subsidy administrators.

该项目将实现三个目标：1）描述马里兰州内补贴连续性的纵向模式，2）研究补贴护理安排的连续性和高质量护理的使用之间的关联，以及3）分析新的指导方针关于补贴重新确定期和补贴拼写长度的管理之间的关联。具体而言，本项目将回答以下研究问题：1）在审查补贴的连续性时，会出现什么样的模式？这些连续性模式在儿童、家庭和社区特征之间是否存在差异？2)接受经认可的补贴照料安排的儿童在这些提供者照料下的时间是否长于接受未经认可的补贴安排的儿童？3)在实施关于12个月重新确定行政做法的新指导之前和之后，补贴期限的中位数是否不同？研究问题将通过分析2007年6月至2016年1月的相关儿童保育补贴行政数据和提供者许可/认证数据来解决。将使用严格的分析技术分析这些数据，包括以人为中心的分析、倾向评分匹配和差异中差异分析。结果将按州政策制定者和儿童保育补贴管理者感兴趣的子组进行分类。