Statistical Modelling2

# Statistical Modelling2 - (SpecialTopic:SEM BidinYatim,PhD...

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Statistical Modelling (Special Topic: SEM) Bidin Yatim, PhD Associate Professor in Statistics College of Art and Science UUM. Phd Applied Statistics (Exeter, UK) MSc Industrial Maths (Aston,UK) BSc Maths & Stats (Nottingham, UK)

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Tutorial: Get Running with Amos Graphics- search from  internet Structural Equation Modelling with AMOS.  Basic  Concepts, Applications and Programming Barbara M.  Bryne Part Two Part Two     Modeling and  Modeling and  Computing Computing
Modeling and Computing   Modeling and Computing   Steps In SEM Implementing SEM Using AMOS How to draw a model using AMOS.  How to run the AMOS model and evaluate several  key components of the AMOS graphics and text  output, including overall model fit and test  statistics for individual path coefficients.  How to modify and re-specify a non-fitting model.

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The researcher first specifies a model based on theory, then determines how to measure constructs, collects data, and then inputs the data into the SEM software package, e.g., AMOS. The package fits the data to the specified model and produces the results, which include overall model fit statistics and parameter estimates.
Steps in conducting an SEM: 1. Specify the full model to be tested and check identification. Note: Models that appear identified on paper may prove to not be statistically or empirically identifiable due to properties of the data. 2. Test fit of measurement model. 3. Re-specify and refit measurement model if model fit statistics, etc. indicate this is necessary. 4. Once the measurement model is determined to have a good fit, test the fit of the theoretical model. 5. Re-specify and refit theoretical model if model fit

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Model Specification The exercise of formally stating a model. The step in which parameters are determined to be fixed or free. Fixed parameters are not estimated from the data and are typically fixed at zero (indicating no relationship between variables). The paths of fixed parameters are labeled numerically (unless assigned a value of zero, in which case no path is drawn) in a SEM diagram. Free parameters are estimated from the observed data and are believed by the investigator to be non-zero. Asterisks in the SEM diagram label the paths of free parameters. Determining which parameters are fixed and which are free in a SEM is extremely important because it determines which parameters will be used to compare the hypothesized diagram with the sample population variance and covariance matrix in testing the fit of the model (Step 4). The choice of which parameters are free and which are fixed in a model is up to the researcher. This choice represents the researcher’s a priori hypothesis about which pathways in a system are important in the generation of the observed system’s relational structure (e.g., the observed sample variance and covariance matrix).
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Statistical Modelling2 - (SpecialTopic:SEM BidinYatim,PhD...

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