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Joint censoring of regressors and outcomes : survey nonresponse and attrition
Horowitz, Joel; Manski, Charles F. - 1994
Persistent link: https://www.econbiz.de/10000896408
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Outliers in statistical data analysis
Pemajayantha, V. - 1995
Persistent link: https://www.econbiz.de/10000603553
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Detecting interaction effects in moderated multiple regression with continuous variables : power and sample size considerations
Shieh, Gwowen - In: Organizational research methods : ORM 12 (2009) 3, pp. 510-528
Persistent link: https://www.econbiz.de/10003868006
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Data quality and non-response effects when using logistical regression in the Welsh health survey
Studley, Ruth - In: Modelling our future : population ageing, health and …, (pp. 377-385). 2007
Persistent link: https://www.econbiz.de/10003551991
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Midas regressions : further results and new directions
Ghysels, Eric; Sinko, Arthur; Valkanov, Rossen I. - In: Econometric reviews 26 (2007) 1, pp. 53-90
Persistent link: https://www.econbiz.de/10003509012
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Statistics, data analysis, and decision modeling
Evans, James R. - 2010 - 4. ed., internat. ed.
Persistent link: https://www.econbiz.de/10003857594
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Statistics, data analysis, and decision modeling
Evans, James R.; Basu, Ayanendranath - 2013 - 5th ed., internat. ed.
Persistent link: https://www.econbiz.de/10009525190
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U-MIDAS: MIDAS regressions with unrestricted lag polynomials
Foroni, Claudia; Marcellino, Massimiliano; Schumacher, … - 2011
Mixed-data sampling (MIDAS) regressions allow to estimate dynamic equations that explain a low-frequency variable by … high-frequency variables and their lags. When the difference in sampling frequencies between the regressand and the … macroeconomic applications, however, differences in sampling frequencies are often small. In such a case, it might not be necessary …
Persistent link: https://www.econbiz.de/10009490826
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Finite sample performance of sequential designs for model identification
Dette, Holger; Kwiecien, Robert - 2003
Classical regression analysis is usually performed in two steps. In a first step an appropriate model is identified to describe the data generating process and in a second step statistical inference is performed in the identified model. An intuitively appealing approach to the design of...
Persistent link: https://www.econbiz.de/10010511732
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Dynamic latent class model averaging for online prediction
Yang, Hongxia; Hosking, Jonathan R. M.; Amemiya, Yasuo - In: Journal of forecasting 34 (2015) 1, pp. 1-14
Persistent link: https://www.econbiz.de/10011305378