TY - JOUR
T1 - Using multidimensional scaling on data from pairs of relatives to explore the dimensionality of categorical multifactorial traits
AU - Meyer, J. M.
AU - Heath, A. C.
AU - Eaves, L. J.
AU - Chakravarti, A.
PY - 1992
Y1 - 1992
N2 - An accurate specification of the dimensionality and ordering of categorical multifactorial phenotypes (e.g., smoking status, including heavy, moderate, light, and nonsmokers) is an important prerequisite for the genetic analysis of these traits. Typically, phenotypic dimensionality and ordering are determined by comparing the relative fits of alternative parametric threshold models. Here, a method of analysis is described which addresses the same issue of trait dimensionality but does not require parametric assumptions. Specifically, we detail how nonmetric multidimensional scaling (MDS), applied to contingency tables which cross‐classify the phenotypes or responses of one relative with another, may be used to explore trait dimensionality. Scaling results from deterministic simulation studies indicate that the latent structure of categorical phenotypes can be recovered with nonmetric MDS. Results from stochastic simulations, however, indicate that the accuracy of recovery, as well as the rejection of models of incorrect dimensionality, are strongly dependent upon sample size and the latent liability correlation between relatives. As an application of the method, the dimensionality of a measure of smoking status in 1,656 pairs of monozygotic twins ascertained through the American Association of Retired Persons is considered. The MDS results indicate that the onset of the smoking habit and the quantity smoked in this aging population represent a unidimensional process. The implication this finding has for subsequent genetic analysis is discussed. © 1992 Wiley‐Liss, Inc.
AB - An accurate specification of the dimensionality and ordering of categorical multifactorial phenotypes (e.g., smoking status, including heavy, moderate, light, and nonsmokers) is an important prerequisite for the genetic analysis of these traits. Typically, phenotypic dimensionality and ordering are determined by comparing the relative fits of alternative parametric threshold models. Here, a method of analysis is described which addresses the same issue of trait dimensionality but does not require parametric assumptions. Specifically, we detail how nonmetric multidimensional scaling (MDS), applied to contingency tables which cross‐classify the phenotypes or responses of one relative with another, may be used to explore trait dimensionality. Scaling results from deterministic simulation studies indicate that the latent structure of categorical phenotypes can be recovered with nonmetric MDS. Results from stochastic simulations, however, indicate that the accuracy of recovery, as well as the rejection of models of incorrect dimensionality, are strongly dependent upon sample size and the latent liability correlation between relatives. As an application of the method, the dimensionality of a measure of smoking status in 1,656 pairs of monozygotic twins ascertained through the American Association of Retired Persons is considered. The MDS results indicate that the onset of the smoking habit and the quantity smoked in this aging population represent a unidimensional process. The implication this finding has for subsequent genetic analysis is discussed. © 1992 Wiley‐Liss, Inc.
KW - contingency tables
KW - the smoking habit
KW - threshold models
KW - twins
UR - http://www.scopus.com/inward/record.url?scp=0026697358&partnerID=8YFLogxK
U2 - 10.1002/gepi.1370090203
DO - 10.1002/gepi.1370090203
M3 - Article
C2 - 1639247
AN - SCOPUS:0026697358
SN - 0741-0395
VL - 9
SP - 87
EP - 107
JO - Genetic Epidemiology
JF - Genetic Epidemiology
IS - 2
ER -