Additionally a "macro" language can be used to write command language subroutines. A Python programmability extension can access the information in the data dictionary and data and dynamically build command syntax programs. The Python programmability extension, introduced in SPSS 14, replaced the less functional SAX Basic "scripts" for most purposes, although SaxBasic remains available. In addition, the Python extension allows SPSS to run any of the statistics in the free software package R. From version 14 onwards, SPSS can be driven externally by a Python or a VB.NET program using supplied "plug-ins". (From Version 20 onwards, these two scripting facilities, as well as many scripts, are included on the installation media and are normally installed by default.)
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I have used SPSS to analyse social research data for about ten years now. I first learned how to use the software through coaching by experienced users. This was a challenging experience as the coaching did not always go at my pace. Similar challenges confront current SPSS beginners. In a shared office space for postgraduate Sociology students at the University Aberdeen, a remark by a frustrated student screams on the notice board, 'SPSS I hate you!' Proper use of this book can endear SPSS to such students. From its title, one might mistake this book for a user manual, but it is far more than that! The authors provide a succinct introduction to the paradigmatic contentions surrounding the application of quantitative measurement and analysis to social phenomena. This first chapter emphasises that good research design is necessary for useful quantitative social analysis, even though this is not the focus of the book. The authors have reiterated in their concluding chapter that users should acquaint themselves with social research design and provided some helpful references. The authors adopt a practical and non-technical approach, devoid of statistical notations. The utility of this second edition of the book is enhanced by use of the latest version of SPSS software (SPSS statistics 17.0) and data from the International Social Survey Programme (ISSP) - which are available for free download - to illustrate key contents. While seemingly simple to an experienced user, some of the tips in the book will be most helpful to novice researchers. Tips on how to make adjustments to SPSS by resetting variable lists and output labels (pages 18 and 19) are particularly useful. Because SPSS is Excel-based, one of the challenges new users face is locating specific variables for analysis and defining analysis outputs. Alphabetical listing of variables and including variable names and labels in outputs can alleviate these challenges. Other important procedural information in the book includes appropriate definition of variables, specification of measurement levels and how to treat missing data in analysis. Closely linked to these are the tips on data manipulation and selection that encourage analysis of a sub-set of variables most relevant to specific questions rather than using an entire database, for efficiency.Data entry in SPSS is prone to errors especially because of lack of checks for valid values and for inconsistencies. While the authors recognise this weakness, and mention that there are programmes that may enhance accuracy during data entry, they fail to mention any specific programmes (page 47). While it is understandable that the authors might have avoided identifying these programmes by name because they are not linked to SPSS, it would have been helpful to explain that some of the software are available online free of charge and to even provide links to their websites for interested users to pursue further e.g. EpiData software. Chapters 4 through 11 provide an excellent step-by-step approach to performing exploratory and inferential statistical analyses in SPSS. The strength of these chapters lay in the clear interpretation of outputs, explanation of their statistical foundations and identification of requirements for application of specific tests. SPSS provides diagnostic information on the stability of tests performed given the data available, which the authors have clearly explained. A good example is the explanation of cell frequency requirements for the chi-square test (page 150). My one caveat would be that the authors have not linked adequately exploratory and inferential statistical approaches in their presentation. The chapters on multivariate analysis make limited reference to exploratory analysis discussed in earlier chapters. The importance of exploratory analysis to the identification of covariates to include in multivariate analysis and a gradual analysis process starting from simple to advanced approaches could be emphasised. This book is an ideal resource for new users of SPSS as well as those seeking a deeper understanding of some of the software's capabilities. The book is suitable both as an introductory and an intermediate course book. Willis O. OdekUniversity of Aberdeen
PSPP is a good alternative to SPSS if you want basic statistics like frequencies and t-tests and you want them for free. If you already know SPSS there is no learning curve. This website goes into more detail about PSPP:
I have been working with SPSS and PSPP, the results are basically the same. PSPP just still misses some functions. However currently pspp added factor analysis and reliability analysis. I prefer using pspp because it is free (open source!!) software and is much faster than spss.
IBM SPSS v15 has been developed for the analysts and statistical programmers who have got some advanced knowledge on the statistical methods and research tools and their usage in making better decisions. The data editor included in this application is very much similar to any of the spreadsheet application which will enable you to manually enter the data or import database from Cognos BI, Lotus, Excel, dBase and tab-delimited files. IBM SPSS v15 supports descriptive statistics, specific tests, correlation determining, neural networking, data classification and many more. It also includes output viewer that has been designed for the data visualization and script editor for the task automation purposes. All in all IBM SPSS v15 is an impressive statistical application for business, research, government and academic organization which will provide you with some advanced statistical analysis as well as forecasting tools. You can also download IBM SPSS Statistics 25 for Mac.
Subjects were recruited at the private psychiatric clinic of Littoral, Rang-du-Fliers in the North of France according to pre-definite inclusion criteria. Data assessment has been based on 1) a retrospective case-control study using electronic medical records of depressive or bipolar patients (n = 207); 2) a prospective observational study (n = 20) using the medical records, and additional questionnaires at T0 (interview-administered) and T1 (self-administered) after an average length of hospital stay of 24.8 days ( 6.3) and 3) a cross-sectional study in depressive patients (n = 40) under psychotropic treatment at the day hospital, using the medical records and an interview-administered questionnaire. Descriptive and analytical statistics (Spearman rank correlations, binary logistic regression) were performed with SPSS statistics 17.0. 2ff7e9595c
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