helpful data software resources
- MPLUS: Mplus is an integrative latent modeling software which brings together many advanced statistical techniques within a single framework (e.g., IRT, multilevel, latent variables). The flexibility of Mplus makes it a preferred platform for handling many methodological challenges in psychological research (e.g., nested cases, scaling, missing data, violation of assumptions). Furthermore, the Muthens (owners of the software) are active in developing new techniques and are very responsive to questions on their community board. The user support alone is worth the purchase.
- SPSS: The Statistical Package for the Social Sciences (also referred to as the Predictive Analytic Software) is a staple among social scientists. It is one of the most frequently used graphic user interfaces for conducting many basic and advanced inferential tests (e.g., correlations, t-test, ANOVA, MANOVA, multiple linear regression, chi-square, factor analysis). You will likely use this software in undergraduate classes and beyond, hence it is important to become familiar with its syntax, interface, and output. Below are some sources to help you get started:
- Open Learn SPSS Course: A 3-hour interactive tutorial for those unfamiliar or uncomfortable with SPSS. Will help you quickly master the basic interface, define a variety of variables, enter basic data types, and perform analyses to test hypotheses. Great for gaining confidence with SPSS.
- Amherst SPSS Tutorial: Amherst's psychology department provides an overview of how to execute many common functions in SPSS (e.g., creating Z-scores, conditional "If" statements). This site was designed to address commands often used in a psychology lab or statistics course.
- Raynald's SPSS Tool: Collection of macros, syntax, and tricks for SPSS data management. Very useful for learning the SPSS language along with advanced data handling scripts. Originally created by an actuary, the site is now managed by Anton Balabanov, a statistical consultant in predictive modeling.
- VassarStats: Offers several online utilities for transforming data, calculating probability, running simple inferential statistics, and other quick software to check your findings from SPSS output.
- Learning R: R is an integrated, interactive environment for data manipulation and analysis that includes functions for standard descriptive statistics (means, variances, ranges) and also useful graphical tools for Exploratory and Multivariate Data Analysis. In terms of inferential statistics R has many varieties of the General Linear Model including the conventional special cases of Analysis of Variance, MANOVA, and linear regression.
What makes R particularly powerful is that statisticians and statistically minded people around the world have contributed more than 4,500 packages to the R Group and maintain a very active news group offering suggestions and help. The growing collection of packages and the ease with which they interact with each other and the core R is perhaps the greatest advantage of R. Advanced features include correlational packages for multivariate analyses including Factor and Principal Components Analysis, and cluster analysis. Advanced multivariate analyses packages that have been contributed to the R-project include at least three for Structural Equation Modeling (sem, lavaan, and Open-Mx), Multi-level modeling (also known as Hierarchical Linear Modeling and referred to as non linear mixed effects in the nlme4 package) and taxometric analysis. Listed below are multiple sites which will help you master the R language:
want to learn helpful data tricks?
How-To-Videos: Many data enthusiasts document how to do several neat tricks in Excel, SPSS, and R. These videos are especially helpful when one is first becoming familiar with the language, functionality, and applications of new or classic data techniques. Such videos are especially helpful for plotting and getting the "gist" of what a particular function or analyses aims to accomplish.