4.7 To know more

For intentional sampling see (Nagae 2007), (Fossaluza et al. 2009) and (Diniz et al. 2016).

The material Sampling: Theory and Practice Using R, kindly made available by professors Pedro Luis do Nascimento Silva, Zélia Magalhães Bianchini and Antonio José Ribeiro Dias, is a very rich source for additional information on this topic in Portuguese. The book Analysis of Complex Sample Data, also by professor Pedro Silva in partnership with professor Djalma Pessoa, is also available in Portuguese.
Professor Pedro also shared the slides from the presentation Combining samples to improve estimates – adventures in non-probability sampling, presented on October 18, 2020 at the VII Bahian Statistics Meeting.

There is also a course on sample data analysis using R, prepared by Prof. Marcel Vieira for the International Association of Survey Statisticians (IASS). It is a self-instructional course in English, with videos, presentations on theory and material for individual practice, which includes R codes and the necessary data. The course is free and available at this link.

Finally, there is also the samplics package for Python, which performs weighting and analysis of complex samples.


Diniz, Juliana Belo, Victor Fossaluza, Carlos Alberto de B. Pereira, and Sergio Wechsler. 2016. “Rain Dance: The Role of Randomization in Clinical Trials.” Open Access Journal of Clinical Trials 8: 21. https://www.doi.org/10.2147/OAJCT.S100446.
Fossaluza, Victor, Juliana Belo Diniz, Basilio de B. Pereira, Eurı́pedes Constantino Miguel, and Carlos Alberto de B. Pereira. 2009. “Sequential Allocation to Balance Prognostic Factors in a Psychiatric Clinical Trial.” Clinics 64 (6): 511–18. https://www.doi.org/10.1590/S1807-59322009000600005.
Nagae, Cátia Yumi. 2007. Amostragem Intencional.” PhD thesis, Universidade de São Paulo. https://teses.usp.br/teses/disponiveis/45/45133/tde-06122007-205037/pt-br.php.