QDA Miner 是一套易於使用於編碼、註釋、擷取和分析大小集合的文件甚至是圖像資訊的混合模型的質性數據分析套件軟體。QDA Miner 常用於團體焦點訪談逐字稿、合法資料、雜誌文章甚至是整本書的分析。或者可以運用在繪圖、照片、繪畫及任何形式的視覺資料。它能與 SimStat 統計數據分析工具軟體，而且跟 WordStat 質性分析和文本採礦組元軟體緊密的集合，使您能夠靈活的分析文本以及包括數值和分類數據的相關結構性資訊。
誰會使用 QDA MINER？
QDA MINER 質性數據分析軟體，可適用於需要從大型或小型的文黨和圖像的集合中，進行編碼文字或圖片、註釋、搜尋、探索和提取信息的任何人，包括：
● 商業智能分析師、市場研究人員、民調人員和 CRM 專業人員
QDA Miner 新版特色
1. IMPORTATION FROM NEW SOURCES
QDA Miner 5 expands your reach to analyze unstructured data for your research or business needs. Import data from major email providers, web survey companies, social media and RSS feeds.
Web Survey Platform
• SurveyMonkeyQualitative Software for Survey Analysis
Reference Management Tools
• Outlook account and PST files
• Hotmail account
• Gmail account
• RSS Feeds
2. IMPORTATION AND MONITORING OF TWITTER, FACEBOOK, REDDIT AND RSS FEEDS
Twitter, Reddit and Facebook are a great source for getting the instantaneous pulse of people’s opinion, while RSS feeds are a good way of keeping oneself informed about what’s new on the web. In QDA Miner 5, not only can you create projects from a search on Twitter, Reddit, Facebook or through an RSS feed, it comes with a standalone tool that will continually monitor in the background those sources and aggregate tweets, Reddit posts, Facebook comments or news on specific topics, allowing you to keep your data current.
Twitter and RSS
3. DOCUMENT OVERVIEW
A graphical overview of the codings of the current document can be displayed allowing one to get a quick glimpse of the spatial distribution of the coding. Bars can be sorted in alphabetical, frequency, first appearance, in codebook order, or by color hue. They may also be stacked to easily compare coding importance. The graphic display can be zoomed in or out, saved to disk or copied to the clipboard. Clicking a bar brings you the location of the corresponding segment in the text.
QDA Miner Document Overview
4. LINK ANALYSIS FEATURE
A new Link Analysis feature allows one to display co-occurrence of coding using force-based, multi-dimensional scaling or circular layouts. Graphs are interactive and may be used to explore connections between codings.
Integrated geocoding service is available in QDA Miner to transform references to cities, states, provinces, countries, postal codes, and IP addresses into geographical coordinates. IP addresses may also be used to obtain the city, region or country of origin.
6. INTERACTIVE PLOT OF DATA POINTS
Plots of data points can be created from various retrieval dialogs (CODING RETRIEVAL, CODE SEQUENCE ANLAYSIS, CODING BY VARIABLES, and LINK RETRIEVAL. The GISViewer mapping module will then allow one to quickly filter data points on categorical, numerical, and date variables or create dynamic range displays and custom animations to easily identify temporal trends, cyclical patterns or relationships to numerical variables. Single data points can be customized and annotated.
INTERACTIVE PLOT OF DATA POINTS
7. DISTRIBUTION MAPS
Users can create layers from various vector file formats and produce choropleth maps to represent point density, demographic information stored in shapefiles, or statistical summaries of numerical values associated with text segments. One can also easily adjust the color range, the number of steps and level of transparency.
Density of data points can be visualized with heatmaps displays to easily identify customer concentrations, crime hot spots, or disease outbreaks. Users can also create heatmaps on all data point or just on selected regions and choose from a wide variety of color ramps or create their own.
9. TREE GRID DISPLAY
A new tree grid report format for the CODING FREQUENCY and the CODING BY VARIABLE commands allows you to view the results organized according to the codebook hierarchical structure.
Tree grid display
10. DUPLICATE CASES IDENTIFICATION
Duplicate cases may occur for many reasons, including data importation, data entry or data management errors, or may occur naturally such as twitter and other online sources (ads, news lines, press releases, etc.). Such duplication may affect the program’s ability to extract relevant features (topics, phrases, etc.) or statistics. The new CASES | DUPLICATES command allows one to identify, tag, select, filter out, or delete duplicate observations. A variable can be created to indicate whether a case is unique, has duplicates (primary) or is such a duplicate. A numerical variable with sequential values may also be created and used for ordering cases on their content.
11. MONITORING FOLDERS, FILES OR ONLINE RESOURCES
The new CASES | MONITORING command allows you to configure a QDA Miner project to monitor a specific folder, and automatically import any documents and images stored in this folder. File may then be automatically deleted or moved to another location. It can also monitor changes to the original source file or online service such as web services, E-mail accounts or reference management tools, allowing you to import any new case, survey response, email, tweet, and so on.
12. VARIABLE EXTRACTION
A new VARIABLES | EXTRACT command allows you to transform coded text into variables, with optional extraction of dates, date and time, numeric values, or text strings. Very useful to extract relevant meta data from unstructured documents or transform an unstructured project into a structured one.
13. EXTRACTION OF JPEG META DATA
JPEG photos and images may contain a lot of information, such as the geographic location where a photo has been taken, a title and description added by its author, or even comments or tags attached by him or by viewers. The new importation routine allows to import all those information and transform them into variables. One may then use those variables in combination to the new GIS feature to plot coded image properties on a map, look at their spatial distribution. Extracted information currently includes:
• Geographic coordinates (latitude and longitude)
• Camera maker and model
14. CHARTING OF DOCUMENT CODING
The new DOCUMENTS | CHART feature allows one to create bar charts, pie charts or tag clouds representing the distribution of codes in a single document.
15. NUMEROUS SPEED OPTIMIZATION
QDA Miner already has an excellent reputation for its speeds of processing (retrieval, autocoding, text analysis) especially with large datasets. Further optimization and redesign allowed us to achieve even faster processing speeds, something that will be surely appreciated by those analysing very large data sets. Here are a few examples of speed improvements we obtained:
Link Retrieval – up to 15x faster
Saving of code statistics – up to 13x faster
Merging of projects – up to 15x faster
Extraction of comments – up to 10x faster
Loading of data in spreadsheet editor – up to 6x faster
Co-occurrence analysis – 3.5x faster
Automatic Classification 3.x faster
Sequence analysis – 2x faster
Code consolidation – 2x faster
16. SAVE CHART ANIMATION, ANIMATED GIF, OR POWERPOINT
QDA Miner 4.x introduced the ability to store rotating three dimensional graphics such as multidimensional scaling or correspondence plots in AVI movie files. We added in version 5.0 the ability to store those animations in a PowerPoint as well as in an Animated GIF file for more portability, more flexibility.
17. IMAGE ROTATION AND RESIZING
Imported images may be rotated and resized. Existing coding is automatically adjusted to the new size or image orientation.
18. IMPORTATION OF POWERPOINT
Presentations stored in PowerPoint .ppt or .pptx files or books in EPUB format can now be imported directly in QDA Miner 5.0.
19. NVIVO TO QDA MINER CONVERSION TOOL
Qualitative analysis is very time consuming, and moving from one qualitative software to another one would be a huge endeavor if one had to start from scratch. QDA Miner 5.0 integrates its NVivo to QDA Miner conversion wizard to guide you through the steps needed to convert your NVivo 7 to NVivo 11 project into a QDA Miner project (documents, images, codebooks, codings, memos, etc.).
20. IMPROVED LOCATION EXTRACTION AND GAZETTER GENERATION
Extract gazetteers from SHP, KML, KMZ, GPX or from our online geographical database.
21. ADDED VARIABLES WHEN COMPARING CODINGS IN WORDSTAT
A new variable selection feature allows one to include numerical, categorical or date variables when one use WordStat to compare text associated with QDA Miner codes.
22. NEW DATE & TIME VARIABLE
A new date and time variable has been added, allowing one to associated a precise time stamp to cases.
23. NEW TYPE TRANSFORMATIONS
New variable type transformations have been added for greater flexibility.
String -> Date & Time
Date & Time -> String
Nominal -> Date
Nominal -> Date & Time
String -> Integer
String -> Double
24. RECODING OF NUMERIC VARIABLES INTO ORDINAL VARIABLES
In order to transform numerical values into ordinal classes one had to transform the numerical variable into a string or an ordinal/nominal variable prior to the recoding operation. The improved RECODE dialog box can now automatically detect when a nominal variable is needed and perform the variable type transformation and recoding in a single operation.
25. CATEGORY MEMOS
It is now possible to attach a memo to a codebook category.
26. MOVING COLUMNS IN TABLE REPORTS
Columns in many tabular reports may now be reordered using simple drag-and-drop operations.
27. RESIZING OF STRING VARIABLE
String variables can be resized, allowing one to store longer string of text or strip down long variables.
28. IMPORT DOCUMENT CREATION DATE
A new option has been added to import the document creation date.
29. IMPROVED SUPPORT FOR MULTILINGUAL DOCUMENTS
Faster display, better support of multi-languages including right to left languages.
► Operating System: Microsoft Windows XP, 2000, Vista, Windows 7, 8 and 10
► Memory: From 256 MB (XP) to 1GB (Vista, Windows 7, 8 and 10)
► Disk Space: 40 MB of disk space.
MAC OS & Linux
► QDA Miner will run on a Mac OS using virtual machine solution or Boot Camp, and on Linux computers using CrossOver or Wine.
ProSuite 是一個 Provalis Research tools 的整合性集合，可允許探索、分析和有關結構化和非結構化的數據。它允許一個先進的電腦輔助質性編碼文件和使用 QDA Miner的圖像呈現，應用強大的內容分析和 WordStat 在文本數據的文本挖掘功能，並進行先進的統計分析數值和使用 SimStat 的分類數據。
MIXING QUALITATIVE AND QUANTITATIVE DATA
The interoperability of QDA Miner, WordStat and SimStat allows researchers to integrate numerical and textual data into a single project and to seamlessly move back and forth between quantitative and qualitative data analysis. More importantly, the integration of structured and unstructured data into a single data set allows one to explore connections between text responses and numerical or categorical data. For example, one can easily analyze relationships between closed and open-ended survey questions, identify social media topic trends over time, find out how supporters’ comments differ from those of detractors, or easily explore differences in word usage between gender, age groups, or geographic locations.
INTEGRATING VARIOUS TEXT ANALYTICS TECHNIQUES
There are many ways to extract information from textual data. Techniques such as in-depth qualitative data analysis, powerful exploratory text mining, or carefully designed content analysis are just a few examples of the range of approaches available today. Each text analysis method has its own strengths and weaknesses, and no single method is appropriate for all text analysis tasks. Yet, most text analysis tools on the market today rely on a single approach to text analysis. At Provalis Research, we are committed to offering a software platform that does not confine researchers and analysts to a single approach, but allows them to choose the one that best fits the research question or the available data.
We also strongly believe that a single text analysis task often profits from combining several methods; our software platforms facilitates this type of integration. One may thus combine in many ways the automatic content analysis and text mining features of WordStat with the manual coding an annotation available in QDA Miner.
WordStat 是一個靈活且易於使用的文本分析軟件 - 無論您是否需要快速提取主題和趨勢的文本挖掘工具，還是要用國家級最先進的質量內容分析工具進行仔細和精確的測量。 WordStat 利用和 SimStat 無縫整合 - 我們的數據統計分析工具 - 和 QDA Miner - 我們的質性數據分析軟體 - 為您的文本分析和其相關的結構化訊息，包括數值和分類數據，帶來前所未有的靈活性。
WHAT IT IS USED FOR?
WordStat can be used by anyone who needs to quickly extract and analyze information from large amounts of documents. Our content analysis and text mining software is used for:
● Content analysis of open-ended responses, interview or focus group transcripts
● Business intelligence and competitive web sites analysis
● Information extraction and knowledge discovery from incident reports, customer complaints
● Content analysis of news coverage or scientific literature
● Automatic tagging and classification of documents
● Fraud detection, authorship attribution, patent analysis
● Taxonomy development and validation
KEY AND UNIQUE FEATURES
● Powerful CONTENT ANALYSIS AND TEXT MINING SOFTWARE for handling large amounts of unstructured information. WordStat can process up to 20 million words per minute and identify all references to user-defined concepts using categorization dictionaries.
● Text Mining and Visualization Tools Integrated EXPLORATORY TEXT MINING AND VISUALIZATION TOOLS such as clustering, multidimensional scaling, proximity plots, and more, to quickly extract themes and automatically identify patterns.
● RELATES UNSTRUCTURED TEXT WITH STRUCTURED DATA such as dates, numbers or categorical data for identifying temporal trends or differences between subgroups or for assessing relationship with ratings or other kinds of categorical or numerical data.
● Use existing or create your own HIERARCHICAL CONTENT ANALYSIS DICTIONARIES OR TAXONOMIES composed of words, word patterns, phrases as well as proximity rules (such as NEAR, AFTER, BEFORE) for achieving precise measurement of concepts.
● COMPUTER ASSISTANCE FOR DICTIONARY BUILDING with tools for extracting common phrases and technical terms and for quickly identifying in your text collection, misspellings, synonyms, antonyms and related words
● One click access toKEYWORD-IN-CONTEXT AND KEYWORD RETRIEVAL TOOLS for easy identification and coding of relevant text segments, validation of content analysis dictionaries, word-sense disambiguation or for drilling down to the source documents.
● Seamless integration with a state of the art QUALITATIVE CODING TOOL (QDA Miner), allows more precise exploration of data or more in-depth analysis of specific documents or extracted text segments when needed.
● MACHINE LEARNING FOR AUTOMATIC DOCUMENT CLASSIFICATION using Naive Bayes and K-Nearest Neighbours algorithms with automatic features selection and validation tools. Classification models may then be saved on disk and reapplied on new data.
● Easy IMPORTATION of databases, spreadsheets and documents (including PDF and HTML) as well as EXPORTATION of text analysis results to common industry file formats (Excel, SPSS, ASCII, HTML, XML, MS Word) and graphs (PNG, BMP and JPEG).
Operating System: Microsoft Windows XP, 2000, Vista, Windows 7, 8 and 10
Memory: From 256 MB (XP) to 1GB (Vista, Windows 7, 8 and 10)
Disk Space: 40 MB of disk space.
WordStat, along QDA Miner, will run on a Mac OS using virtual machine solution or Boot Camp, and on Linux computers using CrossOver or Wine. Click here for more information on ways to run WordStat on a Mac OS computer.
共有 SIMSTAT / MVSP 請點選觀看
Simstat supports not only numerical and categorical data, dates and short alpha-numeric variables but also memos and documents variables allowing one to store in the same project file responses to open-ended questions, interview transcripts, full reports, etc. Since all Provalis Research tools share the same file format, one can easily perform statistical analysis on numerical and categorical data using Simstat, perform qualitative coding on stored documents using QDA Miner or apply the powerful content analysis and text mining features of WordStat on those same documents. Moreover, the coexistence of numerical, categorical and textual data in the same data file gives a unique ability to explore relationships between numerical and textual variables or to compare qualitative codings or content categories between subgroups of individuals.
STATISTICAL ANALYSIS FEATURES
● DESCRIPTIVE statistics (mean, variance, standard deviation, etc.).
● FREQUENCY analysis including frequencies table, descriptive statistics, percentiles table, barchart, pie chart, Pareto chart, histogram, normal probability plot, box-&-whiskers plot and cumulative distribution plot.
● CROSSTABULATION: normal crosstabulation and INTER-RATERS AGREEMENT table,nominal statistics (chi-square, Pearson’s Phi, Goodman-Kruskal’s Gamma, Contingency coefficient), ordinal statistics (Kendall’s tau-b and tau-c, Pearson’s R, symmetric and asymmetric Somers’ D, Dxy and Dyx), inter-raters agreement statistics (percentage of agreement, Cohen’s Kappa, Scott’s Pi, Krippendorf’s r and R-bar, free marginal correction for nominal and ordinal measure), 3-D bar chart.
● BREAKDOWN analysis with multiple Box-and-Whiskers plot.
● MULTIPLE RESPONSES frequency and crosstabulation analysis.
● PAIRED AND INDEPENDENT T-TESTS with effect size measures (r and d), error bar graph, barchart, dual histogram.
● ONEWAY ANALYSIS OF VARIANCE with post hoc tests (LSD, Tukey’s HSD, Scheffé’s test), effect size measures, error bar graph, barchart, deviation chart.
● GLM ANOVA/ANCOVA (up to 5 factors and covariates) including detailed ANOVA table, 3 different adjustment methods for unequal cell sizes (regression, nonexperimental, hierarchical), multiple regression statistics, test of change of R-Square, regression equation (B, standard error of B, beta, confidence, interval of B, zero-order, semi-partial and partial correlations, tolerance level, F, significance), residuals caseplot with Durbin-Watson statistic, standardized residuals scatterplot, normal probability plot of residuals, ability to save predicted and residual values.
● CORRELATION MATRIX including covariance and cross product deviation, user-specified confidence interval, scatterplot matrix.
● PARTIAL CORRELATION MATRIX with interactive correlation matrix for inclusion of exclusion of control variables, computation of confidence intervals, etc.
● REGRESSION analysis including linear and 7 nonlinear regressions (quadratic, cubic, 4th and 5th degree polynomial, logarithmic, exponential, inverse), regression equation, analysis of variance, Durbin-Watson statistics, scatterplot, residuals caseplot, standardized residuals scatterplot, normal probability plot of residuals, ability to save predicted and residual values.
● MULTIPLE REGRESSION analysis including 5 different regression methods (hierarchical entry, forward selection, backward elimination, stepwise selection, enter all variables), P to enter, P to remove, and tolerance criteria, ANOVA table, test of change ANOVA table, regression equation (B, standard error of B, beta, confidence, interval of B, zero-order, semi-partial and partial correlations, tolerance level, F, significance), residuals caseplot, Durbin-Watson statistic, standardized residuals scatterplot, normal probability plot of residuals, ability to save predicted and residual values.
● TIME SERIES analysis including data transformation (ex.: remove mean, lag, etc.), auto-correlation diagnostic (ACF and PACF plot), smoothing techniques (moving average,running median), control bars with user-specified confidence interval.
SINGLE-CASE EXPERIMENTAL DESIGN analysis with descriptive statistics, interrupted time-series graph, various graphical judgmental aids such as smoothing (moving average and running median), trend lines and control bars.
● RELIABILITY analysis with item, inter-item and item-total statistics, split-half reliability statistics, internal consistency measures (Cronbach’s alpha, etc.).
● CLASSICAL ITEM ANALYSIS for multiple-choice item questionnaires.
● FACTOR ANALYSIS including principal components analysis and image covariance factor analysis, Q-type factor analysis, varimax rotation, scree plot, etc..
● SENSITIVITY ANALYSIS with false-positives and false negatives statistics, sensitivity and specificity statistics, ROC curve (Receiver operating characteristics), error rate graph.
● NONPARAMETRIC analysis including binomial test, one sample chi-square test, runs test, McNemar test, Mann-Whitney U test, Wilcoxon t-test, sign test, Kruskal-Wallis ANOVA, Friedman two way ANOVA, Kolmogorov-Smirnov test for 2 samples and goodness of fit test, Moses test of extreme reactions, median test (2 or more samples).
● NONPARAMETRIC ASSOCIATION MATRIX including Spearman’s R, Somer’s D, Dxy and Dyx, Goodman Kruskal’s Gamma, Kendall’s Tau-a, Tau-b, Kendall Stuart’s Tau-c, etc.
● BOOTSTRAP RESAMPLING analysis including resampling of 7 univariate and 21 bivariate estimators, descriptive statistics, percentile table, nonparametric confidence intervals, nonparametric power analysis, variable sample size, random sampling simulation, histogram.
● FULL ANALYSIS BOOTSTRAP resampling on almost every analysis (frequency, crosstab, multiple regression, reliability, nonparametric tests, etc.).
● Integer weighting of cases using another variable.
● Runs LOGISTIC, a freeware logistic regression program written by Gerard L. Dallal.
● SIMCALC probability calculator computes probabilities for 9 types of test/distribution as well as confidence intervals for proportions, mean, and correlation.
DATA MANAGEMENT FEATURES
The data window is a spreadsheet like data editor where values can be entered, browsed, or edited.
● Data file can store up to 2035 variables (or fields).
● Supports plain text as well as Rich Text Format documents.
● Imports comma or tab separated text files, DBase, FoxPro, Excel, MS Access, Paradox, Lotus, Quattro Pro, SPSS/PC+, and SPSS for Windows files.
● Exports comma or tab separated text files, DBase, FoxPro, Excel, MS Access, Paradox, Lotus, Quattro Pro, SPSS/PC+, and XML files.
● Allows merging and aggregation of data files.
● Supports variable and value labels and up to 3 missing values.
● Cases can be filtered using complex xBase expressions.
● Data grid may be sorted on one or several variables.
● Customizable grid provides alternate view of the data file
● Supports data transformation (including conditional transformation), recoding, ranking. Provides more than 50 transformation functions including trigonometric, statistical, random number functions.
OUTPUT MANAGEMENT FEATURES
The Notebook window displays the statistical output for all analysis performed during a session. The notebook metaphor provides an efficient way to browse and manage outputs.
● The text output of each analysis is displayed on a separate page.
● Each page can be annotated or edited.
● Empty pages can be inserted to put down ideas or remarks, sketch an analysis plan, or write down interpretation of results.
● Tabs can be added to create sections in the notebook allowing storage of different kinds of analysis in different sections of the notebook.
● An index of all analysis is automatically generated. This index can be used to quickly locate and go to a specific page, move pages within the notebook, or delete some pages.
● Rich Text notebook allows one to change font attributes (bold, underline, strikeout, italic) and font colors.
● Highlight tool allows to color passages of text.
● Notebooks can be exported in Rich Text Format or in plain text.
CHART CREATION AND MANAGEMENT FEATURES
All high-resolution charts created during a session are displayed in the Chart window. This window can be used to view the charts and perform various operations on individual charts or on the entire collection of charts. For example, you can modify the various chart attributes, save those charts to disk, export them to another application using the clipboard or disk files, or print them. It is also possible to delete a specific chart or to modify the order of those charts in this window.
● Control of axis, titles, legends, colors, lines, etc.
● Charts can be imported on disk or copied to the clipboard in Window bitmap or metafile format
● Charts can also be copied as tab separated values and imported by another charting application.
SCRIPT, EDUCATIONAL, & MULTIMEDIA FEATURES
The script window is used to enter and edit commands. Those commands can be either read from a script file on disk, typed in by the user or automatically generated by the program. When used with the RECORD feature, the script can also be used as a log window to keep track of the analysis performed during a session. Those commands may then be executed again, providing an efficient way to automate statistical analysis. Additional commands also allows one to create demonstration programs, computer assisted teaching lessons, and even computer assisted data entry.
● Statistical analysis, data filtering and transformation commands
● Record script feature to automatically generate commands corresponding to operations performed with menus and dialog boxes.
● Flow control features such as IF-THEN-ELSE statements, GOTO or GOSUB commands, RUN command to run external programs, etc.
● Can read, write, and perform mathematical operations on user defined variables or any database field
● Create menus, text boxes, input boxes, dialog boxes, multiple items questions, etc. (responses from a user can be stored in memory variables or in a data file)
● Multimedia features: play sound (.WAV), music (.MDI), and movie (.AVI) files, display graphics (.BMP) and text.
Operating System: Microsoft Windows 98, XP, 2000, Vista, 7, 8 and 10
Memory: From 64 MB (Win98) to 1 Gb MB (Vista, 7, 8 and 10)
Disk Space: 5 MB of disk space
MVSP 是一個價格低廉但功能強大的可與電腦相容的多變量分析程式，可進行各種協調和叢集分析 (cluster analyses)。它為生態學和地質學到社會學和市場研究等領域的分析數據提供一個簡單的方法。 MVSP 是在超過 50 個國家中被數百個網站所使用。 MVSP 的分析結果已發表在眾多的期刊，包括科學、自然、生態、Journal of Petroleum Geology 和 Journal of Biogeography。
一旦您的數據進行了分析，您就可以直接繪製結果。選擇您想看到的協調軸 (the ordination axes) 和散點圖 (scattergrams) 的繪製。自動生成叢集分析 (cluster analyses)結果的樹狀圖 (Dendrograms)。而這些圖表可以在各種輸出設備所列印。
● Data matrix manipulation: data may be transposed, transformed (transformations available include logarithms to base 10, e, and 2, square root, and Aitchison’s logratio for percentage data), converted to percentages, proportions, standard scores, octave class scale, or range through format for stratigraphic studies, and rows and columns may be selected for deletion
● Data import and export; Lotus 1-2-3 and Symphony and Cornell Ecology Programs
● Principal Coordinates Analysis, performed with the following options: use any type of input similarity matrix, user defined minimum eigenvalues and accuracy level
● Principal Components Analysis, with the following options: correlation or covariance matrix, centered or uncentered analysis, user defined minimum eigenvalues, including Kaiser’s and Jolliffe’s rules for average eigenvalues, user defined accuracy level.
● Correspondence Analysis, with these options: Hill’s detrending by segments, choice of eigenanalysis or reciprocal averaging algorithm, weighting of rare or common taxa and scaling to percentages, user defined minimum eigenvalues and accuracy level.
● Nineteen different similarity and distance measures, including Euclidean, squared Euclidean, standardized Euclidean, cosine theta (or normalized Euclidean), Manhattan metric, Canberra metric, chord, chi-square, average, and mean character difference distances; Pearson product moment correlation and Spearman rank order correlation coefficients; percent similarity and Gower’s general similarity coefficient; Sorensen’s, Jaccard’s, simple matching, Yule’s and Nei’s binary coefficients.
● Cluster analysis, with the following options: seven strategies (UPGMA, WPGMA, median, centroid, nearest and farthest neighbor, and minimum variance), constrained clustering in which the input order is maintained (e.g. stratigraphic studies), randomized input order, integral dendrogram production. Separate utility program allows data matrices to be sorted in the order of the dendrograms; allows patterns to be seen in the data.
● Diversity indices, with the following options: Simpson’s, Shannon’s, or Brillouin’s indices, choice of log base, evenness and number of species can also be calculated.