Combining Modelling Strategies to Analyse Teaching Styles Data

Spencer, Neil H.
May 2002
Quality & Quantity;May2002, Vol. 36 Issue 2, p113
Academic Journal
This paper combines two estimation procedures: Iterative Generalized Least Squares as used in the software MLwiN; Gibbs Sampling as employed in the software BUGS to produce a modelling strategy that respects the hierarchical nature of the Teaching Styles data and also allows for the endogeneity problems encountered when examining pupil progress.


Related Articles

  • Representations and expansions of weighted pseudoinverse matrices, iterative methods, and problem regularization. II. Singular weights. I. Sergienko; E. Galba; V. Deineka // Cybernetics & Systems Analysis;May2008, Vol. 44 Issue 3, p375 

    Abstract  The paper reviews studies on the representations and expansions of weighted pseudoinverse matrices with positive semidefinite weights and on the construction of iterative methods and regularized problems for the calculation of weighted pseudoinverses and weighted normal...

  • OPTIMIZATION OF DAVIDSON MODEL BASED ON RF MEASUREMENT CONDUCTED IN UHF/VHF BANDS. Faruk, Nasir; Adediran, Yinusa. A.; Ayeni, Adeseko A. // International Conference on Information Technology;2013, p1 

    In this paper, field strength measurements were conducted at 203.25 MHz and 583.25 MHz frequencies along six different routes that spanned through the urban, suburban and rural areas of Kwara State, Nigeria. The measurement results were converted to path losses and were compared with path loss...

  • Interactive parameter estimation for output error moving average systems. Xie, Li; Yang, Huizhong // Transactions of the Institute of Measurement & Control;Feb2013, Vol. 35 Issue 1, p34 

    In this paper we study parameter estimation problems for the output error moving average systems. In order to reduce calculation loads of the existing identification methods, an interactive stochastic gradient (ISG) algorithm is presented to estimate the parameters of the system model and the...

  • Optimal depth-based regional frequency analysis. Wazneh, H.; Chebana, F.; Ouarda, T. B. M. J. // Hydrology & Earth System Sciences Discussions;2013, Vol. 10 Issue 1, p519 

    Classical methods of regional frequency analysis (RFA) of hydrological variables face two drawbacks: (1) the restriction to a particular region which can correspond to a loss of some information and (2) the definition of a region that generates a border effect. To reduce the impact of these...

  • Study on Cellular Iterative Location Algorithm with Uniform Noise. An Qin-li; Chen Jian-feng; Yin Zhong-hai // International Journal of Software Engineering & Its Applications;Jul2013, Vol. 7 Issue 4, p279 

    In order to realize location in cellular networks, the location model with uniform noise based on AOA is established when seven base stations are available. Then a maximum likelihood estimation (MLE) method is proposed and realized by an iterative algorithm under this model. Finally, the...

  • Subspace Approach for Frequency Estimation of Superimposed Exponential signals in Multiplicative and Additive Noise. Zhihui Liu; Lihua Fu; Shizhong Zhang // Journal of Software (1796217X);Jul2013, Vol. 8 Issue 7, p1671 

    In this paper, we consider the problem of frequency estimation of superimposed exponential signals in the presence of multiplicative and additive noise. We propose a subspace method based iterative procedure for estimation of signal frequency parameters. The proposed method is based principal...

  • Nonlinear Least Square Based on Control Direction by Dual Method and Its Application. Fu, Zhengqing; Liu, Guolin; Guo, Lanlan; Liu, Weike; Guo, Hua // Mathematical Problems in Engineering;10/30/2016, p1 

    A direction controlled nonlinear least square (NLS) estimation algorithm using the primal-dual method is proposed. The least square model is transformed into the primal-dual model; then direction of iteration can be controlled by duality. The iterative algorithm is designed. The Hilbert morbid...

  • Missing Value Estimation for Microarray Data by Bayesian Principal Component Analysis and Iterative Local Least Squares. Fuxi Shi; Dan Zhang; Jun Chen; Karimi, Hamid Reza // Mathematical Problems in Engineering;2013, p1 

    Missing values are prevalent in microarray data, they course negative influence on downstream microarray analyses, and thus they should be estimated fromknown values. We propose a BPCA-iLLS method, which is an integration of two commonly usedmissing value estimationmethods--Bayesian principal...

  • Norm-Constrained Least-Squares Solutions to the Matrix Equation AXB = C. An-bao Xu; Zhenyun Peng // Abstract & Applied Analysis;2013, p1 

    An iterative method to compute the least-squares solutions of the matrix AXB = C over the norm inequality constraint is proposed. For thismethod, without the error of calculation, a desired solution can be obtained with finitely iterative step. Numerical experiments are performed to illustrate...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics