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MS-DOS Version SV4

Constituent Programs and Free Downloads

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New MDSX CONSTITUENT PROGRAMS AND DOWNLOADS

Free MS DOS versions of the MDSX Library of programs with supporting documentation are available download where indicated

Notes for each program: 
 Program: As named by originator
 Source: Source of original program (numerical sub-routines etc. updated by MDSX staff)
 Data: Usually: Way and Mode (see Carroll & Arabie)
 Model:As specified by originator's documentation
 Transform:Transformation Function, also called Level of Measurement
 Int/ExternalExternal (with user-supplied configuration), or internal (derived from input data) analysis
 Hierarchy:Single program, or hierarchy of models/phases
 Representation:How mode/s are represented in the configuration according to the model
 TUG:Section of The User's Guide to Multidimensional Scaling in which the program is discussed
  N.B. All programs are also separately documented in the User Manual
   

Program name & [source]

Description 

PRELIMINARY

Downloads

 

Information about the MDSX series; Running MDSX programs; Attribution; 

BBDIAM 

Source: Brusco

 

Branch and Bound DIAMeter clustering

DATA: 2-Way 1-Mode

MODEL: Partition Clustering

TRANSFORMATION: Ordinal

INT/EXTERNAL: I

HIERARCHY: n

REPRESENTATION: Exclusive clusters

 

CANDECOMP  

Bell Labs

 

Downloads

 

CANonical DECOMPosition

DATA: internal analysis of a set of 3- to 7-way data matrix of (dis) similarity matrices,

MODEL: Product: Vector, Scalar Products, Factor, Composition

TRANSFORMATION: metric/linear.

INT/EXTERNAL: I & E

HIERARCHY: n

REPRESENTATION: Unidimensional Scale values for each way

TUG: 7.1.1, 7.2.2

 

CONPAR 

Brusco

 

CONcordance PARtitioning

DATA: Internal analysis of a set of three-way (2-mode) data matrix consisting of a set of (dis)similarity matrices

MODEL: A two part model: 1) Subjects are partitioned into homogeneous clusters, using BBDIAM (q.v.) and an aggregate dissimilarity matrix produced for each cluster..  2)Each cluster's data rae scaled using MINISSA Distance scalings

TRANSFORMATION: Ordinal

INT/EXTERNAL: I

HIERARCHY: n

REPRESENTATION: separate scalings

 

CORRESP

Brier

 

CORRESPondence analysis

DATA: 2-Way 2-mode table (set of profiles)

MODEL: Chi-square distance

TRANSFORMATION: Ordinal

INT/EXTERNAL: I

HIERARCHY: n

REPRESENTATION: N-mode point

 

HICLUS 

Johnson

 

Downloads

 

HIerarchical CLUStering

DATA: two-way (1 mode) (dis) similarity data

MODEL: hierarchical clustering scheme (ultrametric : Diameter & Connectedness solutions)

TRANSFORMATION:  ordinal, non-metric monotonic

INT/EXTERNAL: I

HIERARCHY: n

REPRESENTATION: Inclusive partitions / Tree

TUG: 6.1.6

 

INDSCAL-S 

Bell Labs  

Basic 3-way model

Downloads

 

INdividual Differences SCALing - Symmetric

DATA: internal analysis of a three-way (2-mode) data matrix consisting of a set of (dis) similarity matrices

MODEL:  Weighted Euclidean Distance / product composition

TRANSFORMATION: metric/ linear

INT/EXTERNAL: I

HIERARCHY: n

REPRESENTATION: Stimulus Points, subject weights

TUG: 7.1.1, 7.2, A7.2

 

MDPREF

Bell Labs

 

Downloads

MultiDimensional PREFerence Scaling

DATA: internal analysis of two-way, 2-mode data of either a set of paired comparisons matrices or a rectangular, row-conditional matrix of ratings/rankings

MODEL:  Product

TRANSFORMATION: linear

INT/EXTERNAL: I

HIERARCHY: n

REPRESENTATION: Stimulus Points, subject vectors

TUG: 5.3.2, 6.2.2

 

MDSORT

Takane

 

 

MultiDimensional SORTing

DATA:  two-way, 2-mode categorical data (set of sortings)

MODEL:  product

TRANSFORMATION: linear

INT/EXTERNAL: I

HIERARCHY: n

REPRESENTATION: Point

TUG: (Coxon 1999)

 

MINI-RSA

Roskam

 

Downloads

 

(Michigan-Israel-Netherlands Integrated = MINI)

Rectangular Smallest space Analysis

DATA: internal analysis of two-way, 2-mode data in a rectangular (row-conditional) matrix of (preference) rankings or ratings

MODEL: Euclidean distance (Unfolding) model

TRANSFORMATION:  ordinal

INT/EXTERNAL: I

HIERARCHY: n

REPRESENTATION: Point-point

TUG: 5.3.3.1, 6.2.3

 

MINISSA (N)

Roskam

Basic Nonmetric Model

Downloads

[MINI]  Smallest Space Analysis (Nijmegen version)

DATA: internal analysis of a two-way (1mode) symmetric matrix of (dis) similarities

MODEL: Euclidean distance

TRANSFORMATION: Ordinal also called non-metric monotonic

INT/EXTERNAL: I

HIERARCHY: n

REPRESENTATION: Point

TUG: Ch. 3

 

MRSCAL

Roskam

 

Downloads

 

MetRic SCALing

DATA: internal analysis of a two-way (1 mode) symmetric matrix of (dis) similarities

MODEL: Minkowski r-metric (default Euclidean distance model)

TRANSFORMATION:  Linear and Log-interval

INT/EXTERNAL: I

HIERARCHY: n

REPRESENTATION: Point

TUG: 6.1.4

PARAMAP

Bell Labs

 

 

PARAmetric MAPping

DATA: Two-way, 2-mode data (Profiles)

MODEL: Smoothness

TRANSFORMATION: Continuity

INT/EXTERNAL: I, E

HIERARCHY: n

REPRESENTATION: Points (1 mode)

TUG: 5.2.2, 6.1.5

 

PINDIS

Roskam Lingoes

 

Downloads

Procrustean INdividual DIfferences Scaling (Hierarchy)

DATA: Two-way 2-mode Configuration Co-ordinates

MODEL: Hierarchy of Procrustean Fitting models (general distance and general vector)

TRANSFORMATIONS: Similarity, then progressively more complex

INT/EXTERNAL: I, E

HIERARCHY: y (6 models)

REPRESENTATION: Point (dist.), Vector

TUG: 7.3 - 7.6, A7.1

 

PREFMAP

Bell Labs

 

Downloads

PREFerence MAPping (Hierarchy)

DATA: external (and quasi-internal) analysis of two-way, 2-mode row- conditional data (usually a preference measure)

MODEL: 3 general distance and 1 vector models

TRANSFORMATION: Linear, ordinal

INT/EXTERNAL: E, I

HIERARCHY: y 4

REPRESENTATION: Point, vector

TUG: 4.2, 4.4, 6.2.1, 7.5

 

PROCRUSTES

Roskam Lingoes

 

Downloads

 

PROCRUSTEan Similarity (=PINDIS0)

DATA: 2-way 2-mode Configuration Co-ordinates

MODEL: Euclidean Distance

TRANSFORMATION: Similarity (Reflection, Rotation, Uniform re-scaling)

INT/EXTERNAL: I,E

HIERARCHY: n

REPRESENTATION: Point (dist.)

TUG: A7.1

 

PRO-FIT

Bell Labs

 

Downloads

 

PROperty FITting

DATA: external analysis of a configuration, using 2-way 2-mode rectangular matrix of property ratings or rankings

MODEL: scalar products (vector)

TRANSFORMATION: either a linear or continuity

INT/EXTERNAL: E

HIERARCHY: n

REPRESENTATION: vector

TUG: 5.22, 6.2.1

 

TRISOSCAL

Roskam-Prentice

 

Downloads

 

TRIadic Similarities Ordinal SCALing

DATA: internal analysis of a set of triadic (dis) similarity measures

MODEL: Minkowski distance

TRANSFORMATION: Ordinal

INT/EXTERNAL: I

HIERARCHY: n

REPRESENTATION: point

TUG: 2.1.4, 6.1.3

 

CONJOINT (Formerly UNICON)

Roskam

 

 

 

CONJOINT measurement (UNICON, ADDIT, MONANOVA)

DATA: N-way table

MODEL: Simple composition models

TRANSFORMATION: Ordinal

INT/EXTERNAL: I

HIERARCHY: n

REPRESENTATION: Unidimensional scale values for each way

TUG: 5.3.1, 6.1.8

 

WOMBATS 

[Coxon-Sykes]

 

Downloads

 

Work Out Measures Before Attempting To Scale (Utility)

DATA: From rectangular raw data matrix 

Computes one or more measures of dis/similarity , and

Outputs in a user-chosen matrix format

(for input into MDSX and other programs)

MODEL: Dis/similarity Measures

TUG: 2.2

 

 

Programs in the  original MDSX (SV3.2) Library not included, but still available:

MINICPA        (GLR: [MINI]  Conditional Proximity Analysis).

MVNDS          (BL:     Shepardís Maximum Variance Non-Dimensional Scaling)

PARAMAP      (BL:     Carrollís PARAmetric MAPping)

UNICON        (GLR: UNIdimensional CONjoint measurement)

CONCOR       (Arabie: CONvergence of iterated CORrelations: blockmodel  analysis through the production of the image matrices)

 

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