DATA ANALYSIS AND STATISTICAL PROGRAMING SUPPORT (BASE CONTRACT) COMPANY: PROSPECTIVE GROUP

数据分析和统计编程支持（基础合同）公司：PROSPECTIVE GROUP

• 批准号: 9923501
• 负责人: PAUL CONVERTI
• 金额: $ 227.95万
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-22 至 2020-04-21
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9923501
• 关键词: Accelerometer; Adolescent; Age; Area; Aspirin; Automobile Driving; Behavioral; Bioconductor; Bioinformatics; Biological Markers; Biometry; Child; Clinic; Clinical; Cloud Computing; Cohort Studies; Collaborations; Collection; Complex; Complex Variables; Computer software; Congenital Abnormality; Contracts; Couples; Data; Data Analyses; Data Collection; Data Set; Data Storage and Retrieval; Databases; Development; Diabetes Mellitus; Diagnosis; Documentation; Effectiveness; Environment; Epidemiologist; Epidemiology; Family; Fertility; Fetal Growth; Folic Acid; Genetic Determinism; Genetic study; Genomics; Goals; Health; Health Promotion; Healthy Eating; High-Risk Pregnancy; Human Characteristics; Image; Insulin-Dependent Diabetes Mellitus; Intervention Studies; Intervention Trial; Investigation; Joints; Journals; Knowledge; Lead; Longitudinal Studies; Longitudinal cohort study; Manuscripts; Marketing; Measurement; Measures; Methods; Modeling; National Institute of Child Health and Human Development; Natural History; Nature; Observational Study; Operative Surgical Procedures; Outcome; Paper; Participant; Performance; Personal Satisfaction; Planned Pregnancy; Polysomnography; Population; Population Study; Pregnancy; Prospective cohort study; Proteomics; Protocols documentation; Public Health; Publications; Publishing; Quality Control; Randomized; Records; Registries; Reporting; Reproduction; Research; Research Design; Research Methodology; Research Personnel; Risk Behaviors; Running; Sampling; Schedule; Science; Scientist; Secure; Site; Statistical Methods; Structure; Subgroup; Target Populations; Techniques; Teenagers; Telephone; Testing; Triad Acrylic Resin; Ultrasonography; Update; Woman; Women' s Health; Work; Youth; Zinc supplementation; base; biobehavior; data format; data management; data sharing; data structure; diabetes management; digital video recording; endometriosis; epigenome-wide association studies; experimental study; family management; genome-wide; genomic data; high dimensionality; medical schools; medical specialties; metabolomics; multidimensional data; next generation; novel; population based; population health; programs; prospective; randomized trial; reproductive; research and development; research study; simulation; web site

The Division’s research often involves targeted population subgroups including couples of reproductive age of which some may be planning pregnancies, women with low and high-risk pregnancies, or children and adolescents with risky behaviors along. Sampling frameworks utilized by the Division typically include population-based strategies (e.g., registries, marketing databases) and clinically based sampling (e.g., billing and clinic records, surgical schedules). To the extent feasible, the referent population is delineated for all sampling frameworks including those implemented within clinical facilities. The Division’s research is often conducted with nongovernmental investigators from either schools of medicine and biomedical sciences or public health via research and development contracts. All Division research is highly collaborative and trans-disciplinary reflecting the complexity of our research questions, novel study protocols and our passion for answering critical data gaps with the ultimate goal of promoting the health and well-being of populations. Of note is the dual publication track record for much of the Division’s research. For example, biobehavioral and epidemiological investigators will publish the results in their respective journals, while the biostatistical investigators will use this work to motivate original methods research and to publish methods papers in statistical journals. In addition, Division investigators publish their research in subject matter specialty and population health journals. The Division’s research includes both observational and experimental study designs, with most research being prospective in nature and with longitudinal data capture including the collection of biospecimens and in some studies, imaging data (e.g., digital video recording, pregnancy ultrasounds). Of note is the hierarchical data structure underlying much of our work either from the use of triads/diads or genome wide analytic studies (GWAS) or multiscale data from study participants (e.g., day, cycle, woman and couple level data collection for fecundity and fertility research). The highly timed and conditional nature of human reproduction and development is well suited for statistical methods such as joint modeling. Examples of prospective cohort studies with longitudinal measurement and biospecimens and a hierarchical data structure include: the NICHD Fetal Growth Studies (FGS), Longitudinal Investigation of Fertility & Environment (LIFE Study), Next Generation Health Study (NEXT), and the Diabetes and Women’s Health Study. Examples of studies with high dimensional data requiring GWAS and EWAS techniques include: Endometriosis: Natural History, Diagnosis, and Outcomes (ENDO) and genetic determinants of birth defects. Examples of our randomized trials include: Cultivating Healthy Eating in Families of Youth with Type 1 Diabetes (CHEF Trial), Family Management of Diabetes (FMOD); The Teen Passenger Simulation Study; Effects of Aspirin on Gestation and Reproduction Trial (EAGeR), and the recently completed Folic Acid and Zinc Supplementation Trial (FAZST). A description of all studies with publications to date can be found at the Division’s website https://www.nichd.nih.gov/about/org/diphr/Pages/default. Our current research portfolio has approximately 20 large population-based studies ranging from randomized intervention trials (n=260) to large cohort studies (n=3600). Investigators in the Biostatistics and Bioinformatics Branch lead the development of the analytic plans for Division research in collaboration with investigators from other branches. With guidance from Division Investigators, the Contract staff will implement the analytic plans. Objective/Specific Aims The purpose of this contract is to provide program support for Epidemiologists, Biostatisticians and Behavioral Scientists in the Division to enable their effectiveness. The proposed work includes program support for statistical programming, data collection, management, analysis and reporting. • Perform programming with high level knowledge of SAS and R; • Use, when available, public free-ware for data management and analysis; • Condense, merge and reformat data into files that are appropriate for data analysis (e.g., R,SAS, Stata, SPSS, MPlus, PLINK, Bioconductor); • Condense, merge and reformat data into files that are appropriate for data sharing; • Combine original data that have formats such as ASCII, Excel, data from labs, including genomics and proteomics testing, image data, as well as other formats; • Use a facility with cloud computing and data storage; • Create complex variables using longitudinal data; • Handle genomics data such as metabolomics and proteomics, in situations where the data is measured longitudinally; • Store and retrieve “omics” data studies with a very large number of participants and store longitudinal metabolomic profiles; • Store and retrieve sonographic images from complex multicenter longitudinal studies; • Store and retrieve longitudinal ultrasound images in studies with a very large number of participants; • Condense, merge and format data collected from genetic studies for analytic programs such as R, SAS, Stata, Bioconductor, and Plink. Original data have formats such as ASCII, Excel, data from labs, including genomics and proteomics testing, image data, and other formats. Emphasis shall be placed on using publicly available software for data storage; • Create complex variables using longitudinal data; • Create unique data bases and perform error checking, cleaning and running summaries. Examples include quality control for large longitudinal cohort studies to smaller intervention studies. All studies have complex data structures including, but not limited to, imaging, high-dimensional biomarkers, accelerometer and sleep measurements, driving performance as measured from simulations and naturalistic driving studies; • Prepare de-identified datasets and documentation specifically for datasharing; • Interact with web sites used for sharing data and information. Types of web sites include: Web sites for disseminating information to the public as in our CheckPoints site, https://checkpoints.nichd.nih.gov; Web sites for collaborative work; Web sites for sharing data with the research public; example https://brads.nichd.nih.gov; • Create or update websites for studies or datasharing with password-protected areas to facilitate secure sharing of manuscripts, access to data, and sharing of findings, as needed; • Create phone applications for research studies, as needed.

该部门的研究通常涉及有针对性的人群亚组，包括生殖年龄的夫妇，其中一些人可能正在计划怀孕，低风险怀孕和高危妊娠的妇女，或者持续有风险行为的儿童和青少年。该部门使用的抽样框架通常包括基于人群的策略（例如，注册表，营销数据库）和基于临床的抽样（例如计费和临床记录，手术时间表）。在可行的范围内，针对所有抽样框架（包括临床设施中实施的框架）划定了参考人群。该部门的研究经常与来自医学和生物医学学院或公共卫生的非政府研究人员通过研发合同进行。所有部门研究都是高度协作和跨学科的，反映了我们研究问题的复杂性，新颖的研究协议以及我们对回答关键数据差距的热情，以促进人口健康和福祉的最终目标。值得注意的是该部门大部分研究的双重出版物记录。例如，生物行为和流行病学研究人员将在各自的期刊中发布结果，而生物统计研究人员将使用这项工作来激发原始方法研究并在统计期刊上发表方法论文。此外，部门调查人员在主题专业和人口健康期刊上发表了他们的研究。 该部门的研究包括观察性和实验研究设计，大多数 研究本质上是潜在的，并且纵向数据捕获，包括收集 在某些研究中，成像数据（例如，数字视频记录，怀孕） 超声波）。值得注意的是我们大部分工作的层次数据结构。 从研究中使用三合会/DIAD或基因组广泛的分析研究（GWAS）或多尺度数据 参与者（例如，日期，周期，女性和夫妇级别的数据收集，用于繁殖力和生育研究）。人类繁殖和发展的高度定时和有条件的性质是 非常适合统计方法，例如关节建模。前瞻性研究的例子 纵向测量和生物测量以及分层数据结构包括： NICHD胎儿生长研究（FGS），生育与环境的纵向研究（生命） 研究），下一代健康研究（下一个）以及糖尿病和妇女健康研究。 具有GWA和EWAS技术的高维数据的研究示例包括： 子宫内膜异位症：自然史，诊断和结果（内托）和遗传决定剂 缺陷。我们随机试验的例子包括：在青年家庭中培养健康饮食 1型糖尿病（厨师试验），糖尿病家庭管理（FMOD）；青少年乘客 模拟研究；阿司匹林对妊娠和繁殖试验（急切）的影响，最近 完成的叶酸和补充锌补充试验（FAZST）。所有研究的描述 迄今为止的出版物可以在该部门的网站上找到 https://www.nichd.nih.gov/about/org/diphr/pages/default。 我们目前的研究组合有大约20个大型基于人群的研究，从 大型队列研究（n = 3600）的随机干预试验（n = 260）。 生物统计学和生物信息学分支机构的研究者领导了分析的发展 与其他分支机构的调查人员合作进行部门研究计划。有指导 合同人员将从部门的调查人员中实施分析计划。 客观/特定目标 本合同的目的是为流行病学家，生物统计学家和 该部门的行为科学家使他们的有效性。拟议的工作包括 计划支持统计编程，数据收集，管理，分析和报告。 •对SAS和R的高级知识执行编程； •使用（如果可用），将公共免费软件用于数据管理和分析； •将数据凝结，合并和重新格式化到适合数据分析的文件中 （例如，R，SAS，Stata，SPSS，Mplus，Plink，Bioconductor）; •将数据凝结，合并和重新格式化为适合数据共享的文件； •组合具有ASCII，Excel，Labs数据等格式的原始数据， 包括基因组学和蛋白质组学测试，图像数据以及其他格式； •使用云计算和数据存储的设施； •使用纵向数据创建复杂的变量； •处理基因组学数据，例如代谢组学和蛋白质组学，在此情况下 数据是纵向测量的； •与大量参与者一起存储和检索“ OMICS”数据研究 存储纵向代谢组谱； •从复杂的多中心纵向存储和检索超声图像 研究； •在非常大的研究中存储和检索纵向超声图像 参与者人数； •从遗传研究中收集的用于分析的凝结，合并和格式数据 R，SAS，Stata，Bioconductor和Plink等程序。原始数据具有格式 例如ASCII，Excel，来自实验室的数据，包括基因组学和蛋白质组学测试，图像数据和其他格式。重点是使用公共可用的 用于数据存储的软件； •使用纵向数据创建复杂的变量； •创建唯一的数据库并执行错误检查，清洁和运行 概括。例子包括大型纵向队列研究的质量控制 较小的干预研究。所有研究都有复杂的数据结构，包括，但 不限于成像，高维生物标志物，加速度计和睡眠 测量，通过模拟和自然主义测量的驱动性能 驾驶研究； •准备去识别的数据集和文档专门用于数据设备； •与用于共享数据和信息的网站进行交互。网站的类型 包括：网站，用于向公众传播信息的网站，如我们的检查点 网站，https://checkpoints.nichd.nih.gov;合作工作的网站；网站 与研究公众共享数据；示例https://brads.nichd.nih.gov; •创建或更新网站，用于研究或与密码保护区域进行数据录用 为了促进手稿的安全共享，访问数据和调查结果共享， 需要； •根据需要为研究创建电话应用程序。