MicrOsiris Statistical and Data Management Software System

MicrOsiris is a comprehensive statistical and data management package for Windows  based microcomputer systems. It is derived from OSIRIS IV, a statistical and data management package developed and used at the University of Michigan.

Developed for serious survey analysis using moderate to large data sets, MicrOsiris's speed and minimal disk storage requirement, coupled with the interactive dialogs and on-line help systems, make it also suitable for college or graduate level courses in statistics and applied survey research methods. Further, the interactive statistical decision tree for choosing appropriate statistical techniques is a comprehensive decision tool---not just for using MicrOsiris.

MicrOsiris accepts as many cases as you can get on your system. There are interactive dialogs for managing MicrOsiris sessions and an on-line help facility for aid in running a particular command. SAS and SPSS files can be easily imported

Key Benefits

  1. Handles any size data set.
  2. Interactive dialogs and batched runfiles.
  3. Data entry with Excel
  4. Imports and exports to SAS, SPSS, STATA
  5. Special Data Mining techniques for market analysis (SEARCH --very fast for large datasets).
  6. Interactive statistical decision tree for selecting appropriate statistics.
  7. Special nominal and ordinal statistical analysis techniques (MCA, MNA).
  8. Can read OSIRIS data sets from the Institute for Political and Social Research (ICPSR).
  9. Reads UNESCO IDAMS datasets.
  10. Online manual
  11. Decision Tree for choosing statistics and commands to compute them
  12. Online context sensitive help system with additional links to manual.
  13. Requires only 6MB when fully loaded; additional memory allocated as needed depending on number of variables used.
  14. Less than 12MB on disk--including manual and Statistical Decision Tree.

Features

 


 

Data Management

MicrOsiris has the ability to handle weighted data, a powerful general purpose RECODE, commands to check and validate "wild codes" and perform consistency checking among numerous variables, and the ability to aggregate data to a new level of analysis. Commands and directions are provided for importing data into the system and for reformatting MicrOsiris datafiles for use with other systems, including spreadsheet, SAS, and database programs.


 

Statistics

In addition to the usual basic statistics and functions (hypothesis testing, correlation analysis and classical regression--including stepwise and dummy variable), MicrOsiris provides multivariate analysis of nominal- and ordinal-scaled data. It can produce scatterplots, generate univariate and bivariate frequency distributions and related statistics (including lambdas, gammas, kappa, taus, chi-square, and Gini coefficients), non-parametric statistics and rank-order statistics, analysis of variance, and multiple classification analysis (multiple regression using categorical predictors). MicrOsiris also provides for factor analysis with varimax and oblimin rotations, and a variety of cluster analysis techniques.

Of special interest is SEARCH, a binary segmentation command used to develop predictive models for dependent variables. It is an elaboration of the OSIRIS AID and THAID programs developed at the Institute for Social Research. SEARCH divides a sample, through a series of binary splits, into mutually exclusive series of subgroups. The groups are chosen so that at each step the two new groups account for more of the variance or distribution than any other pair of subgroups. Predictor variables may be ordinal or nominally scaled. The dependent variable may be continuous or categorical.


 

Commands in MicrOsiris

Preparing Data for Input 

 

Analysis of Variance and Hypothesis Testing

ADDDATA

Add records to a dataset

ANOVA

One-way analysis of variance.

DICTIONARY

Create and modify dictionaries describing datafiles.

TTEST

Means testing.

IMPORT

Import files from SPSS, SAS, STATA, and other systems.

MANOVA

Multivariate analysis of variance.

MATRANS

Transform or invert matrices.

Correlation and Regression Analysis

MATRIX

Matrix input routine.

LOGLINEAR

Dichotomous dependent variable regression analysis using linear or logit model.

MERGE

Combine two datasets.

CORRELATIONS

Pearsonian correlation analysis, allowing unequal n’s for each pair of variables.

General-Purpose Utilities 

PARTIALS

Partial correlation analysis.

LISTDATA

List MicrOsiris datasets.

REGRESSSION

Multiple regression analysis and dummy variable regression.

LISTDICT

List MicrOsiris dictionaries.

Multivariate Analysis using Ordinal and Nominal Predictors

SORTDATA

Sort datasets.

MCA

Multiple classification analysis.

Checking and Correcting Datasets

MNA

Multivariate analysis of nominal data.

CONCHECK

Perform consistency checks between variables.

SEARCH

Binary segmentation.

FIXDATA

Correct individual variables case by case.

Factor and Cluster Analysis 

 

 

CAP

Spatial configuration analysis.

WILDCODE

Check and document invalid codes.

COMPARE

Compare configuration matrices.

Transforming Dataset

CLUSTER

Cluster analysis.

AGGREG

Aggregate individual records across subsets defined by the user. Compute summary descriptive statistics.

HICLUSTER

Hierarchical cluster analysis.

EXPORT

Export datasets as ASCII files for other systems such as SAS, SPSS, database and spreadsheet programs.

FACTAN

Factor analysis.

RECODE

Recode variables.

MINISSA

Guttman-Lingoes Smallest Space Analysis (Nonmetric multidimensional scaling).

TRANS

Reformat and translate datasets; produces permanently recoded datasets when used with RECODE.

Index Reliability and Survival Analysis

Frequency Distributions and Associated Statistics

ITAN

Item analysis.

SCATTERPLOT

Bivariate scatter plot diagrams

LIFETABLE

Life table analysis.

USTATS

Produces univariate statistics.

REL

Internal consistency of composite measures.

TABLES

Univariate and bivariate tables, rank-order statistics Chi-Square, Cochran's Q, Fisher, Friedman, Kendall's concordance, Kolmogorov-Smirnov two-sample, Kruskal-Wallis H, Spearman Rho, Kappa, Cramer’s V, Lambdas, Leik-Gove, Kendall’s Tau, Gamma, Mann-Whitney, Sign test, Wilcoxon). 

Hardware Requirements

Windows XP or above. MicrOsiris is optimized for a Pentium processor or better, but does not require one. It can use as much memory as you have; permitting large numbers of 2- and 3-way cross tabulations, univariate statistics, and means testing to be run in one pass of the data.

Small footprint: Approximately 12MB on disk--including manual and Statistical Decision Tree.

MicrOsiris requires a variable amount of free workspace, depending upon the command used and size of job.

Address inquiries to: 

Telephone
610-287-9503
Postal address
Van Eck Computer Consulting
814 Welsh Rd, Schwenksville, PA 19473
Electronic mail
General Information: svaneck@vaneck.ws