@article{ATM9244,
author = {Zhongheng Zhang},
title = {Reshaping and aggregating data: an introduction to reshape package},
journal = {Annals of Translational Medicine},
volume = {4},
number = {4},
year = {2016},
keywords = {},
abstract = {It is common that data format extracted from clinical database does not meet the purpose of statistical analysis. In clinical research, variables are frequently measured repeatedly over the follow-up period. Such data can be displayed either in wide or long format. Transformation between these 2 forms can be challenging by hand. Fortunately, there are sophisticated packages in R environment. Data frame should firstly be melted and then casted to format that you want. Aggregation over unique combination of id variables is also allowable. Additionally, the article also introduces 2 functions colsplit() and funstofun() that can be useful in some circumstances.},
issn = {2305-5847}, url = {https://atm.amegroups.org/article/view/9244}
}