Dergiler / TOJSAT / 2015 / Cilt: 5 Sayı: 4

Trends in Human Development Index of European Union

Dergi
TOJSAT
Sayfa
68–79
Yayın Tarihi
2016-07-23
DOI
—
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Generalized Estimating Equations method is often employed to analyze longitudinal and other correlated response data does not require any multivariate distribution assumption

📌 3 Maddede Bu Makale

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Amaç & Hipotez:The Human Development Index is a measure of development index calculated from life expectancy, literacy, education and standards of living.
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Temel Bulgular & Veri:In this paper, Human Development Index data of European Union are collected for periods 1980-2013, and analyzed using Generalized Estimating Equations to investigate whether there is a trend through the years.
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Sonuç & Katkı:Generalized Estimating Equations method is often employed to analyze longitudinal and other correlated response data does not require any multivariate distribution assumption
🔬Tür:Araştırma Makalesi
📍Kapsam:2013 Verileri
⚙️Değişkenler:Human Development Index · Generalized Estimating Equations · European Union

Abstract

The Human Development Index is a measure of development index calculated from life expectancy, literacy, education and standards of living. In this paper, Human Development Index data of European Union are collected for periods 1980-2013, and analyzed using Generalized Estimating Equations to investigate whether there is a trend through the years. Generalized Estimating Equations method is often employed to analyze longitudinal and other correlated response data does not require any multivariate distribution assumption

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Bu Makaleye Atıf Yap

AKTAŞ, S., KARAGÖZ, D. (2016). Trends in Human Development Index of European Union. TOJSAT, Cilt: 5 Sayı: 4, 68–79. https://ajindex.com/articles/1008560

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Kaynakça (6)

  1. Diggle, P. J., Liang, K. Y., and Zeger, S. L. (1994),
  2. Analysis of Longitudinal Data, Oxford: Clarendon Press.
  3. Diggle, P. J., Heagerty, P., Liang, K.-Y., & Zeger, S. L. (2002). Longitudinal data analysis (2nd ed.). Oxford, UK: Oxford University Press.
  4. Liang, K.-Y., & Zeger, S. L. (1986). Longitudinal data analysis using Generalized Linear Models. Biometrika,, 13 22. Hin, L.-Y., Wang, Y.-G. (2009). Working Correlation Structure Identification in Generalized Estimating Equations, Statistics in Medicine, 28, 642-658. IBM Corp. Released 2011.
  5. IBM SPSS Statistics for Windows, Version 20.0. Armonk, NY: IBM Corp. McCullagh, P., and Nelder, J. A. (1989),
  6. Generalized Linear Models, New York: Chapman and Hall. Zeger, S. L., & Liang, K.-Y. (1986). Longitudinal data analysis for discrete and continuous outcomes. Biometrics, 42, 121 130. Twisk, Jos W. R. (2003). Applied Longitudinal Data Analysis for Epidemiology: A Practical Guide. Cambridge University Press.