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A SAS/IML Companion for Linear Models
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ISBN: 1441955569 1441955577 1441955720 1280391308 Year: 2010 Publisher: New York, NY : Springer New York : Imprint: Springer,

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Linear models courses are often presented as either theoretical or applied. Consequently, students may find themselves either proving theorems or using high-level procedures like PROC GLM to analyze data. There exists a gap between the derivation of formulas and analyses that hide these formulas behind attractive user interfaces. This book bridges that gap, demonstrating theory put into practice. Concepts presented in a theoretical linear models course are often trivialized in applied linear models courses by the facility of high-level SAS procedures like PROC MIXED and PROC REG that require the user to provide a few options and statements and in return produce vast amounts of output. This book uses PROC IML to show how analytic linear models formulas can be typed directly into PROC IML, as they were presented in the linear models course, and solved using data. This helps students see the link between theory and application. This also assists researchers in developing new methodologies in the area of linear models. The book contains complete examples of SAS code for many of the computations relevant to a linear models course. However, the SAS code in these examples automates the analytic formulas. The code for high-level procedures like PROC MIXED is also included for side-by-side comparison. The book computes basic descriptive statistics, matrix algebra, matrix decomposition, likelihood maximization, non-linear optimization, etc. in a format conducive to a linear models or a special topics course. Also included in the book is an example of a basic analysis of a linear mixed model using restricted maximum likelihood estimation (REML). The example demonstrates tests for fixed effects, estimates of linear functions, and contrasts. The example starts by showing the steps for analyzing the data using PROC IML and then provides the analysis using PROC MIXED. This allows students to follow the process that lead to the output.

Linear mixed models in practice : an SAS-oriented approach
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ISBN: 0387982221 9780387982229 0387950273 9780387950273 Year: 1997 Volume: 126 Publisher: New York: Springer,

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Keywords

Linear Models. --- Statistics as Topic. --- Models, Theoretical. --- 519.25 --- #ABIB:astp --- Linear models (Statistics) --- Longitudinal method --- Longitudinal research --- Longitudinal studies --- Methodology --- Research --- Social sciences --- Models, Linear (Statistics) --- Mathematical models --- Mathematical statistics --- Statistics --- 519.25 Statistical data handling --- Statistical data handling --- Area Analysis --- Correlation Studies --- Correlation Study --- Correlation of Data --- Data Analysis --- Estimation Technics --- Estimation Techniques --- Indirect Estimation Technics --- Indirect Estimation Techniques --- Multiple Classification Analysis --- Service Statistics --- Statistical Study --- Statistics, Service --- Tables and Charts as Topic --- Analyses, Area --- Analyses, Data --- Analyses, Multiple Classification --- Analysis, Data --- Analysis, Multiple Classification --- Area Analyses --- Classification Analyses, Multiple --- Classification Analysis, Multiple --- Data Analyses --- Data Correlation --- Data Correlations --- Estimation Technic, Indirect --- Estimation Technics, Indirect --- Estimation Technique --- Estimation Technique, Indirect --- Estimation Techniques, Indirect --- Indirect Estimation Technic --- Indirect Estimation Technique --- Multiple Classification Analyses --- Statistical Studies --- Studies, Correlation --- Studies, Statistical --- Study, Correlation --- Study, Statistical --- Technic, Indirect Estimation --- Technics, Estimation --- Technics, Indirect Estimation --- Technique, Estimation --- Technique, Indirect Estimation --- Techniques, Estimation --- Techniques, Indirect Estimation --- Linear Regression --- Log-Linear Models --- Models, Linear --- Linear Model --- Linear Regressions --- Log Linear Models --- Log-Linear Model --- Model, Linear --- Model, Log-Linear --- Models, Log-Linear --- Regression, Linear --- Regressions, Linear --- Programming --- Experimental Model --- Experimental Models --- Mathematical Model --- Model, Experimental --- Models (Theoretical) --- Models, Experimental --- Models, Theoretic --- Theoretical Study --- Mathematical Models --- Model (Theoretical) --- Model, Mathematical --- Model, Theoretical --- Models, Mathematical --- Studies, Theoretical --- Study, Theoretical --- Theoretical Model --- Theoretical Models --- Theoretical Studies --- Computer Simulation --- Systems Theory --- SAS (Computer file) --- Data processing --- Linear models (Statistics). --- Longitudinal method. --- Data processing. --- QA 279 Analysis of variance and covariance. Experimental design. / General works --- Linear Models --- Statistics as Topic --- Models, Theoretical --- Linear models (Statistics) - Data processing

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