User manual spss 17

Using the. SAV format, SPSS automatically sets up and imports the designated variable names, variable types, titles, and value labels, making the process much easier on researchers. Once survey data is exported to SPSS, the opportunities for statistical analysis are practically endless. In short, remember to use SPSS when you need a flexible, customizable way to get super granular on even the most complex data sets. This gives you, the researcher, more time to do what you do best — identifying trends, developing predictive models, and drawing informed conclusions.

For more information on the benefits of using SPSS to conduct survey data analysis, here are some helpful resources:. We use cookies to track how our visitors are browsing and engaging with our website in order to understand and improve the user experience. The Regression optional add-on module provides the additional analytic techniques described in this manual. Base system and is completely integrated into that system. Permission is granted to make and distribute verbatim copies of this manual provided SPSS and Stata.

When reading data from text files, it is the responsibility of the user to know and to specify the conventions used to create that file, e. Keywords identify commands, subcommands, functions, operators, and other specifications in SPSS. An exception is the keyword This manual was donated by the authors to support the James A.

Fraley Scholarship Fund. Authors: Lisa A. Steven D. All Rights Reserved. Designed by Templatic. Is your question not listed? Write the model and serial. Surface Units Cookware for Radiant Glass Cooktop. Oven Controls Special Features Sabbath Mode Oven Racks Aluminum Foil and Oven Liners Viewing Output. Bringing In the Data. Analyzing the Data. Optional Output. Modeling in C. Data Input. Specifying the Model. Viewing Text Output. Viewing Graphics Output.

Modeling in VB. Analysis of the Data. Fixing Regression Weights. Viewing the Text Output. Viewing Additional Text Output. Assumptions about Correlations among Exogenous Variables. Model A. Structural Model. Model B. Results of the Analysis.

Analysis of Several Groups. Text Output. Multiple Model Input. Results for Model Z. Graphics Output. The Bootstrap Method. A Factor Analysis Model. Estimation Methods. About the Model. Adjusting the Line Representing Constant C — df. Performing the Specification Search. Customizing the Analysis. Fitting the Models. About the Example. Multiple Imputation. Posterior Predictive Distributions.

Performing the Analysis. Model Variables. Measures of Parsimony. Minimum Sample Discrepancy Function. Measures Based On the Population Discrepancy. Information-Theoretic Measures. This approach includes, as special cases, many wellknown conventional techniques, including the general linear model and common factor analysis.

With Amos, you can quickly specify, view, and modify your model graphically using simple drawing tools. Simply specify the model graphically left. Amos quickly performs the computations and displays the results right. Structural equation modeling SEM is sometimes thought of as esoteric and difficult to learn and use. This is incorrect. Indeed, the growing importance of SEM in data analysis is largely due to its ease of use.

SEM opens the door for nonstatisticians to solve estimation and hypothesis testing problems that once would have required the services of a specialist. For this reason, every effort was made to see that it is easy to use. Amos integrates an easy-to-use graphical interface with an advanced computing engine for SEM. The publication-quality path diagrams of Amos provide a clear representation of models for students and fellow researchers.

The numeric methods implemented in Amos are among the most effective and reliable available. When confronted with missing data, Amos performs state-of-the-art estimation by full information maximum likelihood instead of relying on ad-hoc methods like listwise or pairwise deletion, or mean imputation.

The program can analyze data from several populations at once. It can also estimate means for exogenous variables and intercepts in regression equations. The program makes bootstrapped standard errors and confidence intervals available for all parameter estimates, effect estimates, sample means, variances, covariances, and correlations.

Multiple models can be fitted in a single analysis. Amos examines every pair of models in which one model can be obtained by placing restrictions on the parameters of the other. The program reports several statistics appropriate for comparing such.

It provides a test of univariate normality for each observed variable as well as a test of multivariate normality and attempts to detect outliers. Path diagrams used for model specification and those that display parameter estimates are of presentation quality. They can be printed directly or imported into other applications such as word processors, desktop publishing programs, and general-purpose graphics programs.

The tutorial is designed to get you up and running with Amos Graphics. It covers some of the basic functions and features and guides you through your first Amos analysis. Once you have worked through the tutorial, you can learn about more advanced functions using the online Help, or you can continue working through the examples to get a more extended introduction to structural modeling with IBM SPSS Amos. Many people like to learn by doing. The initial examples introduce the basic capabilities of Amos as applied to simple problems.

You learn which buttons to click, how to access the several supported data formats, and how to maneuver through the output. Later examples tackle more advanced modeling problems and are less concerned with program interface issues.

Examples 1 through 4 show how you can use Amos to do some conventional analyses—analyses that could be done using a standard statistics package. These examples show a new approach to some familiar problems while also demonstrating all of the basic features of Amos. There are sometimes good reasons for using Amos to do something simple, like estimating a mean or correlation or testing the hypothesis that two means are equal. For one thing, you might want to take advantage of the ability of Amos to handle missing data.

Or maybe you want to use the bootstrapping capability of Amos, particularly to obtain confidence intervals. Examples 5 through 8 illustrate the basic techniques that are commonly used nowadays in structural modeling. Example 9 and those that follow demonstrate advanced techniques that have so far not been used as much as they deserve. These techniques include:.

Bootstrapping to obtain estimated standard errors and confidence intervals. Amos makes these techniques especially easy to use, and we hope that they will become more commonplace. Tip: If you have questions about a particular Amos feature, you can always refer to the extensive online Help provided by the program. Many excellent SEM textbooks are available.

Structural Equation Modeling: A Multidisciplinary Journal contains methodological articles as well as applications of structural modeling. Carl Ferguson and Edward Rigdon established an electronic mailing list called Semnet to provide a forum for discussions related to structural modeling.

You can find information about subscribing to Semnet at www. Many users of previous versions of Amos provided valuable feedback, as did many users who tested the present version.

Torsten B. Eric Loken reviewed Examples 32 and He also provided valuable insights into mixture modeling as well as important suggestions for future developments in Amos. A last word of warning: While Amos Development Corporation has engaged in extensive program testing to ensure that Amos operates correctly, all complicated software, Amos included, is bound to contain some undetected bugs.

We are committed to correcting any program errors. If you believe you have encountered one, please report it to technical support. Remember your first statistics class when you sweated through memorizing formulas and laboriously calculating answers with pencil and paper? The professor had you do this so that you would understand some basic statistical concepts. Later, you discovered that a calculator or software program could do all of these calculations in a split second.