Data Archive For Pepper, Bateson And Nettle, 'Telomeres As Integrative Markers Of Exposure To Stress And Adversity: A Systematic Review And Meta-Analysis'

Data archive for the paper 'Telomeres as integrative markers of exposure to stress and adversity: A systematic review and meta-analysis' by Gillian Pepper, Melissa Bateson and Daniel Nettle. This version was uploaded in July 2018 after peer-review in the journal Royal Society Open Science. Compared to earlier version, it incorporates some minor error correction to the dataset, and reflects the revised analyses we performed after peer review. Our protocol and recording guide, which were preregistered on the Open Science Framework in 2016, are also included here, as is our PRISMA diagram. The data file 'unprocessed data' contains the data as extracted from the literature, with associations shown both as provided in the original papers, and converted to correlation coefficients. The algorithms for converting all the different associations to correlation coefficients are described in the flowchart and implemented in the R script 'effect conversion algorithms.r'. The data file 'processed data.csv' is the dataset analysed in the paper. Compared to 'unprocessed data.csv', it excludes: associations from studies of non-human animals; duplicate associations; a small number of associations from studies of medical treatments; and associations considered subparts or subscales of other associations. These exclusions are outlined in Methods section of the paper. In addition, in the processed data file, all correlations are aligned in direction so as to make them comparable (variable 'ValencedEffect'); and all associations are assigned to broad and fine categories.The script 'unprocessed to processed.r' makes the processed data file from the unprocessed one, or you can simply work from the processed one directly. The R script 'telomere metanalysis script RSOS REVISED.r' reproduces the analyses found in the paper.本数据集归档对应论文《端粒作为压力与逆境暴露的整合标志物：系统综述与元分析》，作者为吉莉安·佩珀（Gillian Pepper）、梅利莎·贝特森（Melissa Bateson）与丹尼尔·内特尔（Daniel Nettle）。本版本于2018年7月在《皇家学会开放科学》（Royal Society Open Science）期刊完成同行评议后上传。相较于早期版本，本归档对数据集进行了小幅错误修正，并纳入了同行评议后我们开展的修正分析内容。 我们于2016年在开放科学框架（Open Science Framework, OSF）预注册的研究方案与记录指南，连同我们的PRISMA流程图（PRISMA diagram），均已收录至本归档中。 数据文件"未处理数据"包含从文献中提取的原始数据，其关联效应既保留了原始论文中的呈现形式，也转换为了相关系数格式。将各类关联效应转换为相关系数的算法已在流程图中说明，并在R脚本"效应转换算法.r"（effect conversion algorithms.r）中实现。 数据文件"已处理数据.csv"为本论文中所分析的数据集。相较于"未处理数据.csv"，该文件剔除了以下内容：非人动物研究的关联效应、重复关联、少量医学治疗相关研究的关联效应，以及被视为其他关联效应子部分或子量表的关联效应。上述剔除标准已在论文的方法部分中详述。此外，在已处理数据文件中，所有相关系数均已统一方向以确保可比性（对应变量"ValencedEffect"）；所有关联效应均被归入大类与细分类别。脚本"未处理数据转已处理数据.r"可将未处理数据转换为已处理数据，也可直接使用已处理数据文件开展分析。 R脚本"端粒元分析脚本 RSOS 修订版.r"（telomere metanalysis script RSOS REVISED.r）可复现论文中的分析结果。