The course focuses on practical programming needs arising when dealing with large datasets, multiple data sources and the programming tools which may help in routinising complex tasks and automating pieces of your work.
This course provides tips and tricks on how to efficiently use Stata and easily transfer tables and model results to article manuscripts. The Course provides several practical examples and uses a learning by doing technique to deliver results to attendees. The course focuses on the Stata commands currently available as well as additional resources provided by the Stata-users community.
Our Stata Autumn School comprises a series of six individual Stata courses that provides attendees with the flexibility to register only the courses that they find most relevant to their research interests. The individual courses will cover:
Bayesian Analysis / Multivariate Analysis / Longitudinal data / Missing data / Network meta-Analysis / Structural Equation Modelling.
This course is for professionals and researchers from all academic disciplines who are new to Stata. The course assumes only limited statistical knowledge and experience of using statistical software.
The objective of this summer school is to train participants in data science, and causal modelling and inference for health and medical big data. The main subjects that the course will cover include: (i) identification of the main sources of administrative and clinical data; (ii) management and manipulation of these data using Stata; (iii) correct application of machine learning and data mining techniques; (iv) accurate application of causal inference methods, via both counterfactual and structural modelling; (v) ex-post cost-benefit analysis for health policy programs.
This course provides basic concepts of data management and how to do it efficiently using Stata. We provide several examples and use learning by doing techniques. The course focuses on available Stata commands and additional resources provided by the Stata-users community.
Econometric modelling for causal inference and program evaluation have witnessed a tremendous development in the last decade, with new approaches and methods addressing an expanding set of challenging problems, both in medical and the social sciences. This course covers some recent developments in causal inference and program evaluation using Stata.
Our Stata course Automatic selection of explanatory variables with Stata aims at introducing methods suitable to automatically select the relevant explanatory variables of linear regression models.
Choosing an appropriate sample size is a common problem and should be given due consideration in any research proposal, as an inadequate sample size invariably leads to wasted resources. This course gives a practical introduction to sample size determination in the context of some commonly used statistical hypothesis tests.
O curso de Análise de Dados Epidemiológicos com STATA tem como objetivo principal apresentar os conceitos avançados na elaboração e análise de dados, propiciando a elaboração de bases de dados eletrônicas e análise estatísticas descritiva e avançada.