· I. Molina, D. Morales, L. Pardo and I. Vajda (2002). On size increase for goodness of fit tests when observations are positively dependent.

Statistics & Decisions, 20, 399-414.

· T. Hobza, I. Molina and D. Morales (2002). Likelihood divergence statistics for testing hypotheses in familial data.

Communications in Statistics - Theory and Methods, 32, 415-434.

· I. Molina and D. Morales (2004). On testing hypotheses with divergence measures.

Soft Methodology and Random Information Systems, 399-346. Editors: M. López-Díaz, M.A. Gil, P. Grzegorzewski, O. Hyrniewicz and J. Lawry. Springer.

· T. Hobza, I. Molina and I. Vajda (2005). On Convergence of Fisher Informations in continuous Models with Quantized Observations.

TEST, 14, 151-179.

· I. Molina, L. Santamaría and D. Morales (2005). A comparative study of small area estimators.

SORT (Statistics and Operations Research Transactions), 28(2), 215-229.

· I. Molina and D. Morales (2007). Rényi Statistics for Testing Hypotheses in Mixed Linear Regression Models.

Journal of Statistical Planning and Inference, 137, 87-102.

· W. González-Manteiga, M. J. Lombardía, I. Molina, D. Morales and L. Santamaría (2007). Estimation of the Mean Squared Error of Predictors of Small Area Parameters under a Logistic Mixed Model.

Computacional Statistics and Data Analysis, 51(5), 2720-2733.

· I. Molina, A. Saei and M. J. Lombardía (2007). Small area estimates of labour force participation under a multinomial logit mixed model.

Journal of the Royal Statistical Society – Series A, 170, 975-1000.

· W. González-Manteiga, M. J. Lombardía, I. Molina, D. Morales and L. Santamaría (2008). Mean Squared Error of a Small-Area EBLUP.

Journal of Statistical Computation and Simulation, 78(5), 443-462.

· W. González-Manteiga, M. J. Lombardía, I. Molina, D. Morales and L. Santamaría (2008). Analytic and Bootstrap Approximation of Prediction Errors under a Multivariate Fay-Herriot Model.

Computational Statistics and Data Analysis, 52, 5242-5252.

· I. Molina (2009). Uncertainty under a multivariate nested-error regression model with logarithmic transformation.

Journal of Multivariate Analysis 100, 963-980.

· A. Baíllo and I. Molina (2009). Mean squared errors of small area estimators under a unit-level multivariate model.

Statistics: A Journal of Theoretical and Applied Statistics 43, 553-569.

· I. Molina, N. Salvati and M. Pratesi (2009). Bootstrap for estimating the MSE of the Spatial EBLUP.

Computational Statistics 24, 441-458.

· I. Molina (2009), Comments on: Goodness-of-fit tests in mixed models.

Test 18, 244-247 (Discussion).

· T. Hobza, I. Molina and D. Morales (2009). Rényi statistics for testing hypotheses with s samples.

Brazilian Journal of Probability and Statistics 23, 196-215.

· I. Molina and D. Morales (2009). Small area estimation of poverty indicators.

Boletín de Estadística e Investigación Operativa 25, 218-225.

· I. Molina and J. N. K. Rao (2010). Small Area Estimation of Poverty Indicators.

The Canadian Journal of Statistics 38, 369-385.

· W. González-Manteiga, M. J. Lombardía, I. Molina, D. Morales and L. Santamaría (2010). Small area estimation under Fay-Herriot Models with nonparametric estimation of heteroscedasticity.

Statistical Modelling 10, 215-239.

· B. Pérez, D. Peña and I. Molina (2011). Robust Henderson III Estimators of Variance Components in the Nested Error Model.

Modern Mathematical Tools and Techniques in Capturing Complexity, 329-339. Editors: L. Pardo, N. Balakrishnan and M.A. Gil. Springer.

· G. Villa, I. Molina and R. Fried (2011). Modelling attendance at Spanish professional football league.

Journal of Applied Statistics 38, 1189-1206.

· G. S. Datta, T. Kubokawa, I. Molina and J. N. K. Rao (2011). Estimation of mean squared error of model-based small area estimators.

Test 20, 367-388.

· C. Ferretti and I. Molina (2012). Fast EB Method for Estimating Complex Poverty Indicators in Large Populations.

Journal of the Indian Society of Agricultural Statistics 66, 105-120.

· Y. Marhuenda, I. Molina and D. Morales, (2013). Small area estimation with spatio-temporal Fay-Herriot models.

Computational Statistics and Data Analysis 58, 308-325.

· I. Molina, I., B. Nandram and J.N.K. Rao (2014). Small Area Estimation of General Parameters with Application to Poverty Indicators: A Hierarchical Bayes Approach.

Annals of Applied Statistics. To appear.