VIEWS: 8 PAGES: 4 POSTED ON: 9/6/2011
THE INVESTIGATOR Training Program for Educational Research Workers Advanced Multivariate and Multilevel Analysis Flinders University – EDES9005 and EDES9005A Participants Students working for PhD, EdD, MA and MEd degrees. Other students and interested persons are welcome Staff Professor John P. Keeves, Dr Kelvin Gregory, Mr Pawel Skuza and Dr I Gusti Ngurah Darmawan Duration One Semester Class Contact One 90 minute lecture and one 90 minute computer practical per week Pre-requisite An Introductory Course in Statistics Units 6 units for MEd, 9 units for EdD Location Investigator Room, Room N105, Sturt Buildings, Flinders University Time Tuesdays afternoons, 1:30 pm to 4:30 pm, during Semester 2. First lesson starting on Tuesday 25 July 2006. This topic aims to prepare students and research workers in education and Aim the social and behavioural sciences to select and employ appropriate analytical procedures for the examination of data collected in surveys, quasi- experimental research studies and longitudinal studies as well as to draw appropriate conclusions and interpret the research findings from such studies. The course concentrates on an understanding of and on the use of the analytical procedures of linear regression, path analysis, multiple regression, factor analysis, cluster analysis, canonical analysis, discriminant analysis, analysis of variance and covariance, latent variable path analysis, and structural equation modelling. In addition, the problems of multilevel analysis are examined and an understanding and experience in the use of the analytical procedure of hierarchical linear modelling is provided both for studies of growth and of school and classroom effects. The HLM, MLWin, MPlus and STREAMS programs are introduced as appropriate procedures for multilevel analysis. The implications of the choice of a particular multivariate analytical procedure for the design of quantitative research studies in the social and behavioural sciences are considered. Course Outline Class 1 Introduction to multivariate and multilevel analysis, Missing data 25 Jul 2006 Correlation coefficients and their meaning, Effects of aggregation and disaggregation of data, Handling missing data through imputation Exercise: Problem Influence on correlation matrices of (a) imputation of missing data (b) aggregation of data (c) disaggregation of data Class 2 Least squares estimation, linear and multiple regression 1 Aug 2006 Introduction to path analyses, causal modelling The development, testing and interpretation of casual models Exercise: Problem Examination of direct and indirect effects in casual path models of different levels of aggregation Class 3 Factor analysis, principal components, varimax rotation, orthogonal and 8 Aug 2006 oblique axes Exercise: Problem Examination of factor structure under different conditions using factor analysis Class 4 Cluster analysis and multidimensional scaling 15 Aug 2006 Exercise: Problem Examination of data to form clusters of variables and cases Class 5 Canonical analysis, latent variables 22 Aug 2006 Exercise: Problem Examination of canonical structure between two sets of variables Class 6 Discriminant analysis for dichotomous and polychotomous variables 29 Aug 2006 as the criterion Exercise: Problem Examination of factors influencing a criterion variable with dichotomous and polychotomous categories Class 7 Multivariate analysis of variance and covariance, repeated measures, 5 Sep 2006 relative change and absolute change over time Estimation of design effects Exercise: Problem Examination of the use of multivariate analysis of variance for (a) a covariance adjustments, (b) relative change, (c) absolute change, (d) to estimate design effects Class 8 Latent variables, Partial least squares path analysis 12 Sep 2006 Jackknife estimates of sampling error Exercise: Problem Examination and testing of a latent variable path model with a simple random sample or a complex sample Class 9 Maximum likelihood estimation 3 Oct 2006 Structural equation modelling using maximum likelihood estimation procedures using LISREL or AMOS Exercise: Problem Comparison of estimation using partial least squares analysis and maximum likelihood procedures Class 10 Confirmatory factor analysis of test-item data using LISREL or 10 Oct 2006 AMOS Hierarchical and nested models Exercise: Problem Examination of factor structure of a mathematics test Class 11 Analysis of growth and learning using hierarchical linear modelling 17 Oct 2006 Exercise: Problem Estimation of growth of rats Estimation of learning in a classroom experimental study Class 12 Hierarchical linear modelling and multilevel analysis 24 Oct 2006 Cross-level interaction effects, Value added effects, residuals Exercise: Problem The class-size problem and the effects of streaming using HLM Class 13 HLM and the v-known estimation procedure 31 Oct 2006 Exercise: Problem Meta analysis of gender effects in reading Measurement problems with gender effects in reading over time Class 14 Multilevel Path Modelling, Suppressor variables, and cross-level 7 Nov 2006 interaction effects Use of STREAMS, AMOS and MPLUS Exercise: Problem Examination of a simple two level path model using MPLUS Assignment MEd: EDES9005 The assignment to be completed at the conclusion of the topic involves the demonstration of competence in the use of two of the analytical procedures treated during the topic and in the inferences drawn and the reporting of results of analyses undertaken through the use of these procedures. EdD: EDES9005A The assignment to be completed at the conclusion of the topic involves demonstration of competence in the use of three analytical procedures treated during the topic and on the inferences drawn and the reporting of analyses undertaken through the use of these procedures. Students are encouraged to analyse their own data. In addition, all members of the class are expected to obtain working experience with all analytical techniques considered in the topic. Reference Book Keeves, J.P. (ed) (1997) Educational Research, Methodology and Measurement. An International Handbook (2nd edn), Oxford: Pergamon. .
Pages to are hidden for
"THE INVESTIGATOR"Please download to view full document