Summary Applications that use linked data are now part of mainstream social science research, though they generally do not take linkage error into consideration. Solutions that correct for the bias caused by these errors have been proposed but are not yet embedded in the various analysis procedures in common use. Secondary analyses based on linked data can therefore be potentially misleading. We review some recent approaches to non‐deterministic data linkage together with a framework for secondary analysis of the linked data which makes use of paradata produced by the linkage process to correct this bias. We also describe a new method for secondary analysis of linked data that builds on this framework and show how it can be used for estimation of a set of domain means based on linked data. We then illustrate this approach via an empirical study based on record linkage of agricultural producers in four states of Brazil aimed at producing estimates of agricultural output by industry. Our study considers register‐to‐register linkage as well as sample‐to‐register linkage, and we show results for the traditional Fellegi–Sunter approach to record linkage as well as for a newer linkage procedure based on the use of classification trees and bagging.

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O conceito de direitos humanos não é consensual, contudo, persiste na cultura moral, política e jurídica do mundo moderno. O Estado sempre ocupou um lugar ambíguo e dialético, sendo hora diretamente ou indiretamente responsável pela ofensa, hora responsável pela proteção de direitos. Para além do aspecto da legitimidade, a pandemia da Covid-19 remeteu a um problema bem mais contundente relacionado com a política adotada pelo Governo brasileiro e seus efeitos. Para conhecer a percepção de moradores da cidade do Rio de Janeiro sobre diferentes aspectos relacionados com os impactos da Covid-19 sobre 5 direitos básicos: saúde, educação, liberdade de ir e vir, trabalho e renda, e voto, foi realizada uma pesquisa quantitativa do tipo web survey. Para alcançar os respondentes foi utilizado o método bola de neve, resposta e repasse do questionário, tendo como ponto de partida os contatos pessoais dos autores, docentes e discentes da ENCE, discentes da Faculdade de Direito da UERJ e servidores do IBGE. Como resultado, a grande maioria dos respondentes identificou os cinco direitos citados como Direitos Humanos e revelou acreditar que: 1) há responsabilidade do poder público, seja por ação ou omissão, nas limitações de direitos; 2) a restrição de algum dos direitos mencionados é justificável durante a pandemia; 3) os impactos das limitações de direitos sobre as classes socioeconômicas mais baixas foi maior; 4) estão insatisfeitos com a atuação do Governo Federal no que se refere a criação de medidas para amenizar os impactos da pandemia da Covid-19 e com o nível de rapidez, eficácia e rigidez das medidas adotadas; e, por fim, 5) que estão cumprindo as regras de isolamento social ao mesmo tempo em que outros moradores da cidade do Rio de Janeiro não estão.

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ObjectiveSince the 70's census, the Brazilian Institute of Geography and Statistics -IBGE has been conducting a post enumeration survey -PES to assess census coverage. In 2010 the survey was conducted in a sample of enumeration areas in each of the 27 states and matching was performed for data from Census and PES. One of the biggest improvements of the 2010 Brazilian Census was the incorporation of new methodologies and technologies. Use of handheld devices in the 2010 Census and PES facilitated automatic matching of PES to the Census. MethodA matching system was designed aiming to find as much as possible the enumerated units by both Census and PES -the true matches. An accurate matching process was essential as the number of matches/unmatches had an effect on the coverage rates so that the levels of false positive (false matches) was strongly controlled during matching operation and the number of false negative (missed true matches) was minimised by successive steps in the matching system. The matching system comprised three stages: automatic, assisted and reconciliation. The automatic matching step was based on the probabilistic linkage theory and a probabilistic model was developed to identify true matches of persons and housing units from census and post enumeration survey data files. Scores were computed according to agreement and disagreement probabilities of selected variables in the pairs of records. The assisted step was held for all housing units and persons classified as unmatch or possible match at the end of automatic step. The procedures included revision of possible matches and matching "unmatched" pairs. This step was run through an application developed in house. The last step was the field reconciliation. Field team double checked the data collected on the unmatched housing units and persons from both Census and PES and searched for new matches. ResultsNew true matches were found while carrying out field checks, especially in rural areas where the addressing system is not standardized. The matching system has been fully implemented immediately after the completion of data collection in each enumeration area. The performance of automatic step was impressive as Brazil is eight million squares kilometers country with huge regional differences and the automatic step was based in a single model for the whole country. Automatic matching resulted in 76% of the total of pairs, with regional differences under 10%, while assisted allowed for 20% and reconciliation 3% of the final pairs.