Tim Macer of meaning ltd. wrote an article about Ruby Tabluation Software from the Australian firm Red Centre Software. I’ve always struggled way ways to automate the analysis and reporting on my ongoing surveys so I was intrigued. I signed up for the trial (they were very flexible — first they spent about an hour and a half with me on a webinar and then they let me try the full, unencumbered version of the software for more than a month) and fell in love with it.

As Tim Macer reports, it does have a bit of a learning curve, but once you work your way through the various manuals (one manual for data processing and setting up surveys; another manual for doing actual data analysis) you’ll find that the software is exceptionally powerful and very useful. It has a variety of data important options, a number of different ways you can process the data, and it integrates very well with Microsoft Excel and Powerpoint.

I won’t rewrite all of Tim’s article (you can read it by following the link below), but I will say that if you do a lot of tracking surveys and want to easily be able to cut your data every which way in a fairly effortless manner (once you get the survey set up right!) then this is the software package for you.

Read Tim Macer’s review of Ruby Tabulation Software

Visit the Red Centre Software website

SPSS has announced the new features that they plan to the upcoming release of PASW Statistics 18 (formerly know as SPSS Statistics 18, or SPSS Base).

• Improved research and reporting tools
• New bootstrapping module for more stable models
• New non-parametrics tests procedure
• Automated data preparation for easier model building
• New Direct Marketing add-on module
• More customizability in the base PASW Statistics
• Easier enterprise integration, deployment and management

PASW Bootstrapping Module

As I understand it, this new module lets you automatically run statistical tests on thousands of randomly drawn sub-samples of your dataset, which lets you minimize impact of outliers and anomalies on your results. If this is easy to use it could be exceptionally useful and time saving. It can be applied to the following SPSS/PASW procedures:

• Descriptive Procedures
  • Frequencies (PASW Statistics Base)
  • Descriptives (PASW Statistics Base)
  • Examine (PASW Statistics Base)
  • Means (PASW Statistics Base)
  • Crosstabs (PASW Statistics Base)
  • T-tests (PASW Statistics Base)
  • Correlations (PASW Statistics Base)
  • Partial Correlations(PASW Statistics Base)
• Modeling Procedures
  • One-Way (PASW Statistics Base)
  • UniAnova (PASW Statistics Base)
  • GLM (PASW Advanced Statistics)
  • Regression (PASW Regression)
  • Nominal Regression (PASW Regression)
  • Discriminant (PASW Statistics Base)
  • Logisitic Regression (PASW Regression)
  • Binary Multi-nominal Logistic Ordinal Regression (PASW Statistics Base)
  • GENLIN (PASW Advanced Statistics)
  • Linear Mixed Models (PASW Advanced Statistics)
  • Cox Regressions (PASW Advanced Statistics)

PASW Direct Marketing

SPSS PASW Direct Marketing is a new model specifically designed to make statistical procedures that can be used to better understand customers more accessible and easier to use.  This is accomplished by cleanly packaging six different procedures/techniques that might be accomplished through other means but that are unlikely to ever be done simply because they are so complex. It appears here that SPSS has made it fairly easy. These procedures are:

• RFM Analysis allows users to score and rank customers by analyzing a combination of how recently they made their last purchase, how frequently they purchase, and how much they spend. The results can then be analyzed and output in a variety of ways.
• Cluster Analysis allows you to group your customers/data into different market segments which can be used to improved your targeting. It includes an interactive model viewer that allows the user to visualize and play with the results in real time.
• Control Package Test allows you to utilize the results of marketing campaigns to figure out which of your customers are most likely to respond to similar campaigns.
• Propensity to Purchase Analysis lets you determine which of your customers are the “lowest hanging fruit” so you can minimize your marketing costs.
• Postal Code Analysis helps you determine best locations for brick-and-mortar stores and other geographic sensitive decisions.

PASW Statistics Developer

PASW Statistical Developer is a new module that gives PASW Statistics users access to thousands of free R algorithms and packages using an interact that is “indistinguishable” from PASW Statistic’s built-in dialogs.

Non-Parametric Testing

Offers more non-parametric testing, which is the ability to make multiple comparisons with non-normal (that is, non-bell shaped) data.

A few links with more information:

• Press Release for SPSS PASW Statistics 18.0
• PDF Detailing PASW Bootstrapping Module
• PDF Detailing PASW Direct Marketing Module
• Details of PASW Statistics Developer (R & Python)

PSAW Statistics 18 will be released on August 17, 2009. SPSS will be hosting an online event in which they intend to go through all of the new features. Sign up here.

I finally received my copy of SPSS Statistics 17 a couple of days ago and determined that I would try to push past my frustration with the “new and improved” Java-based interface and use it to analyze some data for a report I’m working on. But I can’t do it. There aren’t enough compelling features in the new version of SPSS to help me get past my frustration with the Java interface. So I’m sticking with SPSS 15. (more…)

SPSS has been conducting a survey for the last couple of weeks to help them develop SPSS Statistics 18 (the “new” name of what has formerly just been known as SPSS 17). One generally imagines that the questions that are asked provide insight into the types of new features they are considering, (more…)

SPSS 17.0 will feature improved research and reporting tools, greater accessibility for business users combined with new functionality for statistical programmers, and easier enterprise integration, deployment and management.

SPSS 17.0 new features will include:

• Various new algorithms, plus improved speed and performance with additional multithreaded procedures.
• New multiple imputation procedure in SPSS Missing Values that helps you more easily compelte datasets for more reliable analysis
• Updated syntax editor that makes it easier to create, test and correct syntax
• Improved integration with Microsoft Office
• New SPSS EZ RFM (Recency, Frequency, Monetary value) module to help analysts identify top customers and clients
• Ability to integrate third-party applications, procedures, and graphics packages created in R (through plug-ins)
• Enhanced administrative tools to improve IT configuration of software.

Also to be released is a new SPSS EZ RFM module, designed to help marketers use recency, frequency, and monetary value analysis to find their most valuable customers.

Why use a data analysis package like SPSS when you could use Excel? I’ve just come across an interesting marketing piece from SPSS that goes into benefits one gets from using a dedicated data analysis package instead of trying to do all of your analysis in a spreadsheet. While it would be fair to expect that this isn’t necessary an unbiased comparison, it might offer some food for thought to those of you trying to figure out why you should bother to upgrade. (more…)

Bertolt Meyer has written a not-so-happy review of SPSS for the Mac 16.0. His general thesis is that it is the “most insulting piece of software” he has ever come across. He felt that it didn’t look nor act like an Macintosh application; it isn’t properly internationalized; and more than a dozen bugs. (more…)

Let’s say you’re a market researcher, you have an extra $1000 lying around, and you’re looking for an easier way to improve the look, feel and efficiency of your cross-tabs. What do you buy? If you’re me, you buy the the Tables add-on for SPSS. While the text below certainly isn’t a detailed tutorial on how to use SPSS Tables, it should give you an idea of the features it makes available to help you decide whether it is worth the money. (more…)

SPSS announced recently to its Mac-based customers that SPSS 17.0 for Mac would not be released for the PowerPC based Mac, effectively discontinuing SPSS development for the PowerPC. PowerPC Mac users presently represent about 3% of all online computer users, down from 4.2% back in 2006 when the Intel based Mac was released. This based on the following letter which was recently e-mailed to SPSS for Mac users: (more…)

I spend a lot of time working in SPSS, and occasionally I need answers about various techniques and methods that aren’t readily available in the included documentation. Fortunately, there is a tremendous amount of free SPSS information and training materials scattered all over the web. Here are a few of my favorites. (more…)

Anderson Analytics and SPSS is offering a free webcast on March 20, 2008 at Noon EST in which Senior Consultant Jesse Chen will offer creative tips and tricks for analyzing unstructured (text) data. The webcast will last about an hour and will feature Chen using a variety of real-world case studies (probably integrating SPSS Text Analysis for Surveys).

• SPSS Event Info Page
• PR Web Press Release for the Event

Click here to see my review of SPSS Statistics 17.0, the new version of SPSS.

In the upcoming SPSS Directions User Conference in Prague (May 16) Product Management Director Kyle Weeks will discuss some of the new features in SPSS 16. These include:

• SPSS 16 has a new Java interface allowing for Windows, Mac, and Linux versions of SPSS, a searchable Output Viewer, resizable dialogs and more;
• Improved data editor (adds find and replace capabilities to both variable view and data view). Also unicode support, import/export of Excel 2007 data, and an improved data editor;
• Syntax to change string length and data types; ability to set a permanent default working directory; elimination of short/long string distinction; ability to suppress the number of active datasets.
• More powerful statistics, including a new Neural Networks add-on module, a new Partial Least Squares algorithm, a new Cox Regression for Complex Samples module, support for algorithms written in R and improvements to Generalized Linear Models and General Estimating Equations;
• Latent Class Analysis in Amos 16
• SPSS 16.0 has improved programmability (see below)
• More integration with SPSS Predictive Enterprise Services, allowing you to store/retrieve and query to/from the Predictive Enterprise Repository via both the user interface and syntax
• Multi-threaded procedures for improved performance and scalability.

Other sources also report that SPSS 16.0 for Windows will use a new syntax editor. We can also assume that it will support Vista (since they still haven’t released a patch for SPSS 15).

SPSS has also indicated that some of the original functionality of SPSS Trends and SPSS Tables that has since been superceded by newer functionality will be eliminated. In SPSS Trends 16, the Exponential Smoothing, Autoregression, and ARIMA dialogs will be removed, while the more flexible Create Models; Apply Models; Seasonal Decomposition and Spectral Analysis dialogs will remain.

In SPSS Tables 16, Basic Tables, General Tables, Multiple Response Tables, and Tables of Frequencies will be removed, while the more flexible Custom Tables and Multiple Response Sets will remain.

It is worth noting that all of the functionality offered by the removed dialog boxes will continue to be available through syntax.

Details on the new Programmability of SPSS 16.0:

• EXTENSION command for user procedures with SPSS syntax
• Dataset features for complex data management
• New dataset class extends Python transformation program capabilities to multiple datasets
• Similar to INPUT PROGRAM but can read and write datasets
• Multiple input and output datasets
• User code written in Python
• Ability to use R procedures within SPSS through R Plug-In
• Provides ability to run R code within SPSS
• Use to take advantage of statistical capabilities in R
• Access active SPSS datset
• Write results to SPSS Viewer
• Improved implimentation of User Procedures
• Can be written in Python but specified using SPSS traditional syntax
• User never writes or sees Python code
• Used as if a built-in SPSS command
• Python module called with syntax already checked and processed by SPSS
• More general PLS module
• Dialog box interface tools coming in SPSS 17

I still wish it would be nice if they added the ability to organize variables in folders…maybe in SPSS 17?

• View the “See It in SPSS 16.0″ Presentation (both Powerpoint and live demonstration)
• List of free SPSS demonstrations and events online
• Read the full SPSS Dimensions agenda
• Visit the SPSS home page
• Read the letter from SPSS regarding Tables 16 and Trends 16

In the March 2007 issue of Research, Tim Macer reviewed streamBASE GmbH’s Coding-Modul, a program specifically designed to assist in the process of coding a significant number of open-ended questions. Tim gave the software a generally positive review (4 out of 5 for ease of use; 4.5 out of 5 for value). 

Tim liked the fact that Coding-Modul was a well-crafted system full of practical features for coding; that it allows you to easily distribute ‘packages’ of coding work to non-net connected individuals who are using standalone PCs; that it integrates seamlessly with Readsoft Forms; and that it has powerful administrative features to manage workflow.

Coding-Modul lost points because it is windows-based only; that automation features for typed texts are limited and that the documentation is not yet available in English (although it may be now).

• Read Tim Macer’s review of Coding-Modul
• Learn more about Coding-Modul at the stramBASE GmbH web site

Found an interesting comparison between the features of SPSS and STATA (two statistical analysis packages), as provided by several statisticians on Windows Live Spaces:

SPSS Advantages:

• Slightly more user friendly in making complex tables & graphs
• Nice routines for testing interactions in logistic regression models
• Friendly ANOVA commands
• Generally easier to use
• Sophisticated survival analysis

STATA Advantages:

• Much easier to run a probit
• Much better documentation
• Can do a lot more procedures than SPSS
• Great company support, friendly user base
• Multiple pooled cross sectional time series routines
• Count procedures (poisson, negative binomial and zero routines)
• Maximum likelihood estimators (Tobit, multinomial logit, ordinal logit, ordinal probit)
• Huber-White correction for heteroskedascity
• More comprehensive ANOVA routines
• Cox regression
• Duration analysis procedures
• Capability to estimate models for complex surveys
• Better weighting capability (pweights vs. aweights and iweights)
• Ability to take clustering into account
• Lots of user written solutions
• Much better handling of longitudinal panel data
• Event history analysis capabilities
• Panel data analysis capabilities
• Faster development than SPSS
• Better leasing arrangement

What this all means to market researchers I cannot say — I generally in my day to day life do not use many of the statistical procedures they describe and I’ve never tried STATA.

• Read the full comments

University of Missouri graduate student Mitch Hardin recently posted a note on his blog about how after spending a lot of quality time with SPSS he switched to R, a free software environment for statistical computing and graphics that runs on a variety of platforms (Windows, MacOS, Unix).

Although R is “almost entirely command-line driven,” Mitch likes the fact that it offers more information about what is going on and there are a lot of user-defined function. Personally, I can’t imagine using a command-line to do my stats processing, but then I’m not a big one for getting things done in SPSS syntax either. I couldn’t find much evidence of people using R for marketing research, but the software is free and I can’t imagine why it wouldn’t work if you needed a powerful statistical package but didn’t want to spend a lot of money.

• Mitch Harden’s post on Somatopsychic
• R Project for Statistical Computing