profileR (version 0.3-5)

pams: Profile Analysis via Multidimensional Scaling

Description

The pams function implements profile analysis via multidimensional scaling as described by Davison, Davenport, and Bielinski (1995) and Davenport, Ding, and Davison (1995).

Usage

pams(data, dim)

Arguments

data

A data matrix or data frame; rows represent individuals, columns represent scores; missing scores are not allowed.

dim

Number of dimensions to be extracted from the data.

Value

• dimensional.configuration - A matrix that provides prototypical profiles of dimensions extracted from the data.

• weights.matrix - A matrix that includes the subject correspondence weights for all dimensions, level parameters, and the subject fit measure which is the proportion of variance in the subject's actual profiles accounted for by the prototypical profiles.

Details

The pams function computes similarity/dissimilarity indices based on Euclidean distances between the scores provided in the data, and then extracts dimensional coordinates for each score using multidimensional scaling. A weight matrix, level parameters, and fit measures are computed for each subject in the data.

References

Davenport, E. C., Ding, S., & Davison, M. L. (1995). PAMS: SAS Template.

Davison, M. L., Davenport, E. C., & Bielinski, J. (1995). PAMS: SPSS Template.

See Also

cpa, pr

Examples

# NOT RUN {
data(PS)
result <- pams(PS[,2:4], dim=2)
result
# }