Synthesis methods Stata code: Cumpston_et_al_2023_other_synthesis_methods.do

This Stata .do file provides the code used to analyse the data extracted and coded from systematic reviews included in the paper:
Cumpston MS, Brennan SE, Ryan R, McKenzie JE. 2023.
Statistical synthesis methods other than meta-analysis are commonly used, but are seldom specified: a survey of systematic reviews of interventions
Input file: Synthesis methods data file: Cumpston_et_al_2023_other_synthesis_methods.xlsx (https://doi.org/10.26180/20785396)
Associated file: Synthesis methods data dictionary (https://doi.org/10.26180/20785948)
Study protocol: Cumpston MS, McKenzie JE, Thomas J and Brennan SE. The use of ‘PICO for synthesis’ and methods for synthesis without meta-analysis: protocol for a survey of current practice in systematic reviews of health interventions. F1000Research 2021, 9:678. (https://doi.org/10.12688/f1000research.24469.2) 

Note: Naming convention of the variables. The naming convention for the variables links to the data dictionary. The character prefix identifies the  section of the data_directory (e.g. variables names with the prefix 'Chars' are from the 'CHARACTERISTICS' section). The number of the variable reflects the item number in the data dictionary, except that the first digit is removed because this is captured by the character prefix. For example, Chars_2 is item number 1.2 under the 'CHARACTERISTICS' section of the data dictionary.

本 Stata .do 文件提供了用于分析从系统评价中提取并编码的数据的代码。该论文由 Cumpston MS, Brennan SE, Ryan R, McKenzie JE 在 2023 年发表，题为《除元分析之外的其他统计合成方法：系统评价干预措施调查》。输入文件为合成方法数据文件：Cumpston_et_al_2023_other_synthesis_methods.xlsx（https://doi.org/10.26180/20785396），相关文件为合成方法数据字典（https://doi.org/10.26180/20785948）。研究方案由 Cumpston MS, McKenzie JE, Thomas J 和 Brennan SE 编写，题为《“PICO 合成”的使用以及非元分析合成方法：系统评价中当前实践调查方案》：F1000Research 2021，9:678（https://doi.org/10.12688/f1000research.24469.2）。注：变量命名规范。变量的命名规范与数据字典相联系。字符前缀标识数据目录的某个部分（例如，带有前缀 'Chars' 的变量来自 'CHARACTERISTICS' 部分）。变量的数量反映了数据字典中的项目编号，但首位数被移除，因为这部分信息已由字符前缀捕获。例如，Chars_2 代表数据字典 'CHARACTERISTICS' 部分下的 1.2 项目编号。