5 citations · 8 across the 6 of their papers we have counts for
9 papers
nonprobsvy -- An R package for modern methods for non-probability surveys
Łukasz Chrostowski, Piotr Chlebicki, Maciej Beręsewicz
The following paper presents nonprobsvy -- an R package for inference based on non-probability samples. The package implements various approaches that can be categorized into three…
Data integration of non-probability and probability samples with deterministic predictive mean matching
Aniela Czerniawska, Piotr Chlebicki, Łukasz Chrostowski +1
We study deterministic predictive mean matching mass imputation estimators to integrate data from probability and non-probability samples. We consider two approaches: predicted-to-…
Quantile balancing inverse probability weighting for non-probability samples
Maciej Beręsewicz, Marcin Szymkowiak, Piotr Chlebicki
The use of non-probability data sources for statistical purposes and for official statistics has become increasingly popular in recent years. However, statistical inference based o…
Survey calibration for causal inference: a simple method to balance covariate distributions
Maciej Beręsewicz
This paper proposes a~simple, yet powerful, method for balancing distributions of covariates for causal inference based on observational studies. The method makes it possible to ba…
A note on joint calibration estimators for totals and quantiles
Maciej Beręsewicz, Marcin Szymkowiak
In this paper, we combine calibration for population totals proposed by Deville and Särndal (1992) with calibration for population quantiles introduced by Harms and Duchesne (2006)…
COVID-19 and the gig economy in Poland
Maciej Beręsewicz, Dagmara Nikulin
We use a dataset covering nearly the entire target population based on passively collected data from smartphones to measure the impact of the first COVID-19 wave on the gig economy…