STATA Programs for Using the Intermediate Data Structure (IDS) to Construct Files for Statistical Analysis
DOI:
https://doi.org/10.51964/hlcs9350Keywords:
STATA, Event history analysis, Survival analysis, Episodes table, History, Social history, Life courses, Demography, Historical demography, IDS, Intermediate Data StructureAbstract
The Intermediate Data Structure (IDS) provides a common structure for storing and sharing historical demographic data. The structure also facilitates the construction of different open-access software to extract information from these tables and construct new variables. The article Using the Intermediate Data Structure (IDS) to Construct Files for Analysis (Quaranta 2015) presented a series of concepts and programs that allow the user to construct a rectangular episodes file for longitudinal statistical analysis using data stored in the IDS. The current article discusses, in detail, each of these programs, describing their technicalities, structure and syntax, and also explaining how they can be used.
Downloads
References
Alter, G. & Mandemakers, K. (2014). The Intermediate Data Structure (IDS) for longitudinal historical microdata, version 4. Historical Life Course Studies, 1, 1-26.
Alter, G., Mandemakers, K. & Gutmann, M. (2009). Defining and distributing longitudinal historical data in a general way through an intermediate structure. Historical Social Research, 34(3), 78-114.
Cox, D. (1972). Regression models and life-tables. Journal of the Royal Statistical Society, Series B (Methodological), 34(2), 187-220.
Quaranta, L. (2015). Using the intermediate data structure (IDS) to construct files for statistical analysis. Historical Life Course Studies, 2, 86-107.
Stead, W., Hammond, W. & Straube, M. (1982). A chartless record - is it adequate? In: Proceedings of the annual symposium on computer application in medical care (pp. 89-94). American Medical Informatics Association. https://doi.org/10.1007/BF00995117
Therneau, T. M. & Grambsch, P. M. (2000). Modeling survival data: Extending the Cox model. New York: Springer-Verlag.
