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Structural equation models for dealing with spatial confounding. (English) Zbl 07663944


MSC:

62-XX Statistics

Software:

mgcv; gamair; GMRFLib
Full Text: DOI

References:

[1] Besag, J.; York, J.; Mollie, A., Bayesian Image Restoration, With Two Applications in Spatial Statistics, Annals of the Institute of Statistical Mathematics, 43, 1-20 (1991) · Zbl 0760.62029
[2] Bollen, K. A., Structural Equations With Latent Variables (1989), New York: Wiley, New York · Zbl 0731.62159
[3] Clayton, D. G.; Bernardinelli, L.; Montomoli, C., Spatial Correlation in Ecological Analysis, International Journal of Epidemiology, 22, 1193-1202 (1993)
[4] Fahrmeir, L.; Kneib, T.; Lang, S.; Marx, B., Regression (2013), Berlin, Heidelberg: Springer, Berlin, Heidelberg · Zbl 1276.62046
[5] Hanks, E. M.; Schliep, E. M.; Hooten, M. B.; Hoeting, J. A., Restricted Spatial Regression in Practice: Geostatistical Models, Confounding, and Robustness Under Model Misspecification, Environmetrics, 26, 243-254 (2015) · Zbl 1525.62132
[6] Hodges, J. S.; Reich, B. J., Adding Spatially-Correlated Errors Can Mess Up the Fixed Effect You Love, The American Statistician, 64, 325-334 (2010) · Zbl 1217.62095
[7] Hughes, J.; Haran, M., Dimension Reduction and Alleviation of Confounding for Spatial Generalized Linear Mixed Models, Journal of the Royal Statistical Society, 75, 139-159 (2013) · Zbl 07555442
[8] Indikatoren und Karten zur Raum- und Stadtforschung (2015)
[9] Klein, N.; Kneib, T.; Lang, S.; Sohn, A., Bayesian Structured Additive Distributional Regression With an Application to Regional Income Inequality in Germany, The Annals of Applied Statistics, 9, 1024-1052 (2015) · Zbl 1454.62485
[10] Lemieux, T., The “Mincer Equation”. Thirty Years After Schooling, Experience, and Earnings, Jacob Mincer: A Pioneer of Modern Labor Economics (2006), Boston: Kluwer Academic, Boston
[11] Mincer, J. A., Schooling, Experience, and Earnings (1974), New York: National Bureau of Economic Research, Inc, New York
[12] Paciorek, C. J., The Importance of Scale for Spatial-Confounding Bias and Precision of Spatial Regression Estimators, Statistical Science, 25, 107-125 (2010) · Zbl 1328.62596
[13] R: A Language and Environment for Statistical Computing (2016), Vienna, Austria: R Foundation for Statistical Computing, Vienna, Austria
[14] Reich, B. J.; Hodges, J. S.; Zadnik, V., Effects of Residual Smoothing on the Posterior of the Fixed Effects in Disease-Mapping Models, Biometrics, 62, 1197-1206 (2006) · Zbl 1114.62124
[15] Robinson, W. S., Ecological Correlations and the Behavior of Individuals, American Sociological Review, 15, 351-357 (1950)
[16] Rue, H.; Held, L., Gaussian Markov Random Fields: Theory and Applications (2005), London: Chapman & Hall, London · Zbl 1093.60003
[17] Slesnick, D. T., Empirical Approaches to the Measurement of Welfare, Journal of Economic Literature, 36, 2108-2165 (1998)
[18] Sohn, A., The Gender Earnings Rift: Assessing Hourly Earnings Distributions of Males and Females Using Structured Additive Distributional Regression, Zentrum für Statistik, Universität Göttingen, Working Paper Series
[19] Weiber, R.; Mühlhaus, D., Strukturgleichungsmodellierung (2014), Berlin, Heidelberg: Springer, Berlin, Heidelberg
[20] Wood, S., Generalized Additive Models: An Introduction with R (2006), Boca Raton, FL: Chapman and Hall, Boca Raton, FL · Zbl 1087.62082
[21] Wood, S., mgcv: Mixed GAM Computation Vehicle with GCV/AIC/REML Smoothness Estimation (2016)
[22] Wright, S., On the Nature of Size Factors, Genetics, 3, 367 (1918)
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