33 citations · 47 across the 10 of their papers we have counts for
9 papers · 1 filter
Estimating causal quantile exposure response functions via matching
Luca Merlo, Francesca Dominici, Lea Petrella +2
We develop new matching estimators for estimating causal quantile exposure-response functions and quantile exposure effects with continuous treatments. We provide identification re…
Unified unconditional regression for multivariate quantiles, M-quantiles and expectiles
Luca Merlo, Lea Petrella, Nicola Salvati +1
In this paper, we develop a unified regression approach to model unconditional quantiles, M-quantiles and expectiles of multivariate dependent variables exploiting the multidimensi…
A Nested Error Regression Model with High Dimensional Parameter for Small Area Estimation
Partha Lahiri, Nicola Salvati
In this paper we propose a flexible nested error regression small area model with high dimensional parameter that incorporates heterogeneity in regression coefficients and variance…
Scale estimation and data-driven tuning constant selection for M-quantile regression
James Dawber, Nicola Salvati, Timo Schmid +1
M-quantile regression is a general form of quantile-like regression which usually utilises the Huber influence function and corresponding tuning constant. Estimation requires a nui…
Causal Inferences in Small Area Estimation
Setareh Ranjbar, Nicola Salvati, Barbara Pacini
When doing impact evaluation and making causal inferences, it is important to acknowledge the heterogeneity of the treatment effects for different domains (geographic, socio-demogr…
Small Area Estimation with Linked Data
Ray Chambers, Enrico Fabrizi, Nicola Salvati
In Small Area Estimation data linkage can be used to combine values of the variableof interest from a national survey with values of auxiliary variables obtained from another sourc…
Semi-Parametric Empirical Best Prediction for small area estimation of unemployment indicators
Maria Francesca Marino, Maria Giovanna Ranalli, Nicola Salvati +1
The Italian National Institute for Statistics regularly provides estimates of unemployment indicators using data from the Labor Force Survey. However, direct estimates of unemploym…
M-quantile regression for multivariate longitudinal data: analysis of the Millennium Cohort Study data
Marco Alfo', Maria Francesca Marino, Maria Giovanna Ranalli +2
We propose a M-quantile regression model for the analysis of multivariate, continuous, longitudinal data. M-quantile regression represents an appealing alternative to standard regr…
Disease Mapping via Negative Binomial Regression M-quantiles
Ray Chambers, Emanuela Dreassi, Nicola Salvati
We introduce a semi-parametric approach to ecological regression for disease mapping, based on modelling the regression M-quantiles of a Negative Binomial variable. The proposed me…