Results 171 to 180 of about 3,197 (211)
Nonprobability Sampling and Twitter
Social Science Computer Review, 2017 Twitter data are widely used in the social sciences. The Twitter Application Programming Interface (API) allows researchers to build large databases of user activity efficiently. Despite the potential of Twitter as a data source, less attention has been paid to issues of sampling, and in particular, the implications of different sampling strategies on ...
Patrick Rafail
openaire +2 more sources
Weight smoothing for nonprobability surveys [PDF]
Test, 2021 This study was partially supported by Ministerio de Ciencia e Innovacion, Spain [grant number PID2019-106861RB-I00/AEI/10.13039/501100011033], the IMAG-Maria de Maeztu grant [grant number CEX2020-001105-M/AEI/10.13039/501100011033] and, in terms of the ...
Ramon Ferri-García +1 more
exaly +2 more sources
Use of nonprobability samples for official statistics, state of the art [PDF]
Tightened budgets, continuing decrease of response rates in traditional probability surveys and increasing pressure by users for more timely data, has stimulated research on the use of nonprobability sample data, such as administrative records, web scraping, mobile phone data and voluntary internet surveys, for inference on finite population parameters
Pfeffermann, Danny, Sverchkov, Michael
openaire +1 more source
A Review of Conceptual Approaches and Empirical Evidence on Probability and Nonprobability Sample Survey Research [PDF]
Journal of Survey Statistics and Methodology, 2020 There is an ongoing debate in the survey research literature about whether and when probability and nonprobability sample surveys produce accurate estimates of a larger population. Statistical theory provides a justification for confidence in probability
Carina Cornesse +2 more
exaly +2 more sources
New data strategies: nonprobability sampling, mobile, big data
Quality Assurance in Education, 2018 Purpose Researchers now have more ways than ever before to capture information about groups of interest. In many areas, these are augmenting traditional survey approaches – in others, new methods are potential replacements.
Michael Link
exaly +2 more sources
Estimating response propensities in nonprobability surveys using machine learning weighted models [PDF]
Mathematics and Computers in SimulationPropensity Score Adjustment (PSA) is a widely accepted method to reduce selection bias in nonprobability samples. In this approach, the (unknown) response probability of each individual is estimated in a nonprobability sample, using a reference ...
Ramon Ferri-García +2 more
exaly +2 more sources
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Bayesian inference for nonprobability samples with nonignorable missingness
Statistical Analysis and Data Mining: The ASA Data Science JournalAbstractNonprobability samples, especially web survey data, have been available in many different fields. However, nonprobability samples suffer from selection bias, which will yield biased estimates. Moreover, missingness, especially nonignorable missingness, may also be encountered in nonprobability samples.
Zhan Liu +3 more
openaire +1 more source
Domain estimation from weighted nonprobability samples
Statistical Journal of the IAOSWhen inferring population characteristics from a nonprobability sample, it is crucial to correct the possible selection bias therein by, for example, pseudo-weighting. Many correction methods focus on estimating the population means of the target variable. However, often the quantities of subpopulations are also of interest.
An-Chiao Liu +3 more
openaire +1 more source
Response Quality in Nonprobability and Probability-based Online Panels
Sociological Methods and Research, 2023Carina Cornesse, Annelies G Blom
exaly