• SAS
• R
• SPSS
• Mplus
• HLM
• Stata
• Amos

• Stat/Transfer
• ATLAS.ti
• MAXQDA
• NVivo and N6
• QSR Merge
• Ethnograph

• SAS

(Phil Spector, http://www.stat.berkeley.edu/classes/s100/sas.pdf)

SAS for Windows will do every task that other editions of SAS do, plus it is easy to use and its graphic user interface can do a lot more in graphical analyses than the retired mainframe. There are two main components to most SAS programs - the data step(s) and the procedure step(s). The data step reads data from external sources, manipulates and combines it with other data set and prints reports. The data step is used to prepare your data for use by one of the procedures (often called “procs”). The procedure steps perform analysis on the data, and produce (often huge amounts of) output. The most effective strategy for learning SAS is to concentrate on the details of the data step, and learn the details of each procedure as you have a need for them.

• R

(Compiled by Robert A. Muenchen - BobM@utk.edu)

R is open source software for statistics and graphics available for free at http://www.r-project.org/

With over 800 add‐on packages, many containing multiple procedures, R can do almost everything that SAS and SPSS can do and quite a bit more, plus that it is free! The table below focuses only on SAS and SPSS products and which of them have counterparts in R. As a result, some categories are extremely broad (e.g. regression) while others are quite narrow (e.g. conjoint). R packages that have no counterparts in the form of SAS Inc. or SPSS Inc. products are not listed. There are many important topics (e.g. mixed models, offered by all three) that are not listed because neither SAS nor SPSS sell a product focused just on that.

• SPSS

SPSS is composed of two inter-related facets, the statistical package itself and SPSS language, a system of syntax used to execute commands and procedures. Likewise, there are two approaches to using SPSS: (a) via the Graphical User Interface (GUI), a point-and-click approach already familiar to Windows users and (b) via the use of SPSS programming syntax.

• enter your data into the computer
• calculate new variables
• manage the SPSS files
• select or weight cases in your data
• describe the data (frequencies, graphics, statistics)
• make statistical tests (t-test, chi-square test, correlation test, ...)
• make the statistical analysis (anova, regression, factor, discriminant, ...)
• select our results in the output window and move them to the text editor

• Mplus

(Manual)

Mplus allows the analysis of both cross-sectional and longitudinal data, single-level and multilevel data and data that come from different populations with either observed or unobserved heterogeneity. Analyses can be carried out for observed variables that are continuous, censored, binary, ordered categorical (ordinal), unordered categorical (nominal), counts, or combinations of these variable types. Mplus also has special features for missing data, complex survey data, and multilevel data. In addition, Mplus has extensive capabilities for Monte Carlo simulation studies, where data can be generated and analyzed according to any of the models included in the program.

• HLM

(Manual)

The HLM program can fit models to outcome variables that generate a linear model with explanatory variables that account for variations at each level, utilizing variables specified at each level. HLM not only estimates model coefficients at each level, but it also predicts the random effects associated with each sampling unit at every level. While commonly used in education research due to the prevalence of hierarchical structures in data from this field, it is suitable for use with data from any research field that have a hierarchical structure. This includes longitudinal analysis, in which an individual's repeated measurements can be nested within the individuals being studied. In addition, although the examples above implies that members of this hierarchy at any of the levels are nested exclusively within a member at a higher level, HLM can also provide for a situation where membership is not necessarily "nested", but "crossed", as is the case when a student may have been a member of various classrooms during the duration of a study period. The HLM program allows for continuous, count, ordinal, and nominal outcome variables and assumes a functional relationship between the expectation of the outcome and a linear combination of a set of explanatory variables. This relationship is defined by a suitable link function, for example, the identity link (continuous outcomes) or logit link (binary outcomes).

• Stata

(http://fmwww.bc.edu/GStat/docs/StataIntro.pdf)

Stata is a full-featured statistical programming language for Windows, Macintosh, UNIX, and Linux. It can be considered a “stat package,” like SAS, SPSS, RATS, or eViews. Stata is advertised as having three major strengths: data manipulation, statistics, and graphics. Stata is an excellent tool for data manipulation: moving data from external sources into the program, cleaning it up, generating new variables, generating summary data sets, merging data sets and checking for merge errors, collapsing cross–section time–series data on either of its dimensions, reshaping data sets from “long” to “wide”... In this context, Stata is an excellent program for answering ad hoc questions about any aspect of the data. Stata graphics have been extensively improved and enhanced in version 8. They are excellent tools for exploratory data analysis, and can produce high–quality 2-D publication-quality graphics in several dozen different forms.

• AMOS

(http://www.spss.com/Amos/)

Amos provides you with powerful and easy-to-use structural equation modeling (SEM) software With Amos, you can perform estimation with ordered-categorical and censored data, enabling you to:

• Create a model based on non-numerical data without having to assign numerical scores to the data
• Work with censored data without having to make assumptions other than normality

• Stat Transfer

(http://www.stattransfer.com/html/products.html)

Stat/Transfer is designed to simplify the transfer of statistical data between different programs. Stat/Transfer will automatically read statistical data in the internal format of one of the supported programs and will then transfer as much of the information as is present and appropriate to the internal format of another. Stat/Transfer preserves all of the precision in your data, while automatically minimizing the size of your output data set. Stat/Transfer also allows control over the storage format of your output variables. In addition to converting the formats of variables, Stat/Transfer also processes variable names, missing values and value and variable labels automatically.

• ATLAS.ti

(Manual)

ATLAS.ti serves as a powerful utility for qualitative analysis, particularly of larger bodies of textual, graphical, audio, and video data. The content or subject matter of these materials is in no way limited to any one particular field of scientific or scholarly investigation. Its emphasis is on qualitative, rather than quantitative, analysis, i.e., determining the elements that comprise the primary data material and interpreting their meaning. Emerging daily are numerous new fields that can take full advantage of the program’s facilities for working with graphical, audio, and video data.

• MAXqda

(An Introduction to Qualitative Research. by Uwe Flick 2006 )

MAXqda is a state-of-the-art instrument for professional text analysis. As one of the pioneers in the field (the first version was released in 1988) With MAXqda you can create and import texts in Rich Text Format (rtf) from anywhere on your hard disk and from the Internet by drag and drop. The values can be exported to SPSS or Excel. A special strength is the teamwork functions and the features to merge qualitative and quantitative analyses. MAXqda offers a fully integrated add-on module, which allows an analysis of the word frequencies or even to perform a quantitative content analysis.

• Nvivo and N6

(http://www.cit.gu.edu.au/conferences/qualit2006/proceedings/PDFPapers/Bandara.pdf)

NVivo is a computer program for qualitative data analysis that allows one to import and code textual data, edit the text; retrieve, review and recode coded data; search for combinations of words in the text or patterns in the coding; and import from or export data to other quantitative analysis software.

• QSR Merge

(Manual)

QSR Merge is an application for merging two QSR NUD•IST project databases into one. The data documents in each project are combined into a new set of data documents, and the two index systems are combined into one. By repeated use of QSR Merge, you can combine any number of QSR NUD•IST projects into one. QSR Merge works only for projects created using QSR NUD•IST release 3.0 or later. QSR Merge for Macintoshes will combine projects on Macintoshes, and QSR Merge for Windows will combine Windows projects. You can also merge a Macintosh project with a PC/Windows project, provided they are brought together onto the same platform first. QSR Merge contains a translation utility which will do that. QSR Merge runs automatically.

• Ethnograph

(http://www.qualisresearch.com/)

The Ethnograph v5.0 for Windows PCs is a versatile computer program designed to make the analysis of data collected during qualitative research easier, more efficient, and more effective. You can import your text-based qualitative data, typed in any word processor, straight into the program. The Ethnograph helps you search and note segments of interest within your data, mark them with code words and run analyses which can be retrieved for inclusion in reports or further analysis.