A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation ModelingSAS Institute, 1 mar 2013 - 444 páginas Annotation Structural equation modeling (SEM) has become one of the most important statistical procedures in the social and behavioral sciences. This easy-to-understand guide makes SEM accessible to all userseven those whose training in statistics is limited or who have never used SAS. It gently guides users through the basics of using SAS and shows how to perform some of the most sophisticated data-analysis procedures used by researchers: exploratory factor analysis, path analysis, confirmatory factor analysis, and structural equation modeling. It shows how to perform analyses with user-friendly PROC CALIS, and offers solutions for problems often encountered in real-world research. This second edition contains new material on sample-size estimation for path analysis and structural equation modeling. In a single user-friendly volume, students and researchers will find all the information they need in order to master SAS basics before moving on to factor analysis, path analysis, and other advanced statistical procedures. |
Índice
| 1 | |
Exploratory Factor Analysis | 43 |
Assessing Scale Reliability with Coefficient Alpha | 97 |
Path Analysis | 107 |
Developing Measurement Models with Confirmatory Factor Analysis | 185 |
Structural Equation Modeling | 253 |
Introductdion to SAS Programs SS Logs and SAS Output | 305 |
Data Input | 311 |
Working with Variables and Observations in SAS Datasets | 331 |
Exploring Data with PROC MEANS PROC FREQ PROC PRINT and PROC UNIVARIATE | 357 |
Preparing Scattergrams and Computing Correlations | 385 |
Simplifying PROC CALIS Programs | 401 |
Datasets | 405 |
Critical Values for the ChiSquare Distribution | 411 |
| 413 | |
Otras ediciones - Ver todo
A Step-by-Step Approach to Using SAS for Factor Analysis and Structural ... Ph. D. Norm O'Rourke,Ph. D. Larry Hatcher No hay ninguna vista previa disponible - 2013 |
A Step-By-Step Approach to Using SAS for Factor Analysis and Structural ... Norm O'Rourke,Larry Hatcher No hay ninguna vista previa disponible - 2013 |
Términos y frases comunes
alternative value appear assess chapter coefficient alpha column commitment compute Confidence Limit confirmatory factor analysis corr correlation coefficients correlation matrix covariance estimates Covariance Structure create criterion data=D1 datalines dataset degrees of freedom descriptive statistics discriminant validity eigenvalue endogenous Err t Value error example exogenous variables F variables factor loadings factor scores goodness-of-fit identify includes indicator variables interpret Investment Model Study kurtosis Lagrange Multiplier latent factors latent variables LINEQS statement manifest variables measurement model Model Chi-Square multiple null hypothesis observed variables option parameter estimates participants path analysis path coefficient perform preceding program predicted presented principal component analysis PROC CALIS PROC FACTOR PROC MEANS procedure program figure provides questionnaire relationship reliability residual terms responses revised model RMSEA Root Mean Square rotated factor pattern sample SAS program satisfaction SATMATH SATREAD SATWRITE scale scree SRMR statistical power Std Err Stem-Leaf structural equation modeling theoretical model variance Wald test