Research project

Tzavidis - Innovations in Small Area Estimation Methodologies

Lead researchers:

Professor Nikos Tzavidis
Other researchers:

Dr Yves Berger,

Professor Li-Chun Zhang
Research funder:

ESRC
Status:

Not active

Staff

Lead researchers

Professor Nikos Tzavidis PhD

Professor of Statistical Methodology

Research interests

Small Area Estimation and official statistics
Outlier robust inference; Quantile and M-quantile models
Geospatial data; Poverty mapping; Statistical inference under data aggregation and displacement

Connect with Nikos

Email: [email protected]

Other researchers

Dr Yves Berger

Associate Professor

Connect with Yves

Email: [email protected]

Professor Li-Chun Zhang

Professor in Social Statistics

Research interests

Graph sampling
Analysis of integrated data
Statistical uses of administrative sources

Connect with Li-Chun

Email: [email protected]

Research outputs

Data-driven transformations in small area estimation

N. Rojas-Perilla, S. Pannier, T. Schmid & N. Tzavidis, 2019, Journal of the Royal Statistical Society. Series A: Statistics in Society, 183(1), 121-148

DOI: 10.1111/rssa.12488

Type: article

The R package emdi for the estimation and mapping of regional disaggregated indicators

A.K. Kreutzmann, S. Pannier, N. Rojas-Perilla, T. Schmid, M. Templ & N. Tzavidis, 2019, Journal of Statistical Software, 91(7)

DOI: 10.18637/jss.v091.i07

Type: article

From start to finish

Nikolaos Tzavidis, Li-Chun Zhang, Angela Luna Hernandez, Timo Schmid & Natalia Rojas-Perilla, 2018, Journal of the Royal Statistical Society. Series A: Statistics in Society, 181(4), 927-979

DOI: 10.1111/rssa.12364

Type: article

The utility of geodemographic indicators in small area estimates of limiting long-term illness

Graham Moon, Liz Twigg, Kelvyn Jones, Grant Aitken & Joanna Taylor, 2018, Social Science and Medicine

DOI: 10.1016/j.socscimed.2018.06.029

Type: article

Estimation and testing in M-quantile regression with applications to small area estimation

Annamaria Bianchi, Enrico Fabrizi, Nicola Salvati & Nikolaos Tzavidis, 2018, International Statistical Review

DOI: 10.1111/insr.12267

Type: article