ALSCAL 84.1

Software for Multidimensional Scaling ALSCAL performs metric or nonmetric Multidimensional Scaling and Unfolding with individual differences options. It can analyze one or more matrices of dissimilarity or similarity data. The analysis represents the rows and columns of the data matrix as points in a Euclidean space. If a row and column are similar, then their points are close together, while if the row and column are dissimilar, they are far apart. Get ALSCAL and give it a try to see what it’s all about! ALSCAL performs metric and nonmetric analyses: · The multidimensional scaling can be “metric” or “nonmetric”. Metric scaling assumes that the dis/similarity data are quantitative — that they are measured at the interval or ratio levels of measurement. Nonmetric scaling assumes that the data are qualitative — that they are at the ordinal level of measurement. ALSCAL analyzes one or more dissimilarity matrices: · ALSCAL can analyze one or more matrices of dis/similarity data. The matrices may be rectangular or square, symmetric or asymmetric, conditional or unconditional, and may have missing elements. The program permits the analysis of any number of matrices, each having any number of rows or columns. ALSCAL does Scaling and Unfolding: · ALSCAL can analyze data whose rows and columns refer to the same set of objects or events (square data, which may be symmetric or asymmetric), or which refer to two different sets of objects or events (rectangular data). · When the data are square the program performs multidimensional scaling, constructing a Euclidean space which has points in it for every object/event. · When the data are rectangular the program performs multidimensional unfolding, constructing a Euclidean space which has points in it for every row and column object/event. In both cases, the distance between the points corresponding to the dis/similarity between the objects/events. ALSCAL does Individual Differences Models: · ALSCAL can analyze data that are contained in several matrices. With several matrices ALSCAL can perform replicated or individual differences multidimensional scaling or unfolding. · For replicated scaling or unfolding the analysis constructs a Euclidean space just as when there is only one matrix of data. · For individual differences (weighted) scaling or unfolding, the objects/events are represented by points in a Euclidean space (as above), while the matrices are represented by vectors of weights in an additional individual differences space. · The replicated and weighted multidimensional scaling and unfolding analyses may be either metric or nonmetric.