TY - JOUR
T1 - The relationship between cub and loglinear models with latent variables
AU - Oberski, D. L.
AU - Vermunt, J. K.
N1 - Publisher Copyright:
© Universitá del Salento.
PY - 2015
Y1 - 2015
N2 - The "combination of uniform and shifted binomial"(cub) model is a distribution for ordinal variables that has received considerable recent attention and specialized development. This article notes that the cub model is a special case of the well-known loglinear latent class model, an observation that is useful for two reasons. First, we show how it can be used to estimate the cub model in familiar standard software such as Mplus or Latent gold. Second, the mathematical equivalence of cub with this well-known model and its correspondingly long history allows well-known results to be applied straightforwardly, subsuming a wide range of specialized recent developments of cub and suggesting several possibly useful future ones. Thus, the observation that cub and its extensions are restricted loglinear latent class models should be useful to both applied practitioners and methodologists.
AB - The "combination of uniform and shifted binomial"(cub) model is a distribution for ordinal variables that has received considerable recent attention and specialized development. This article notes that the cub model is a special case of the well-known loglinear latent class model, an observation that is useful for two reasons. First, we show how it can be used to estimate the cub model in familiar standard software such as Mplus or Latent gold. Second, the mathematical equivalence of cub with this well-known model and its correspondingly long history allows well-known results to be applied straightforwardly, subsuming a wide range of specialized recent developments of cub and suggesting several possibly useful future ones. Thus, the observation that cub and its extensions are restricted loglinear latent class models should be useful to both applied practitioners and methodologists.
UR - http://www.scopus.com/inward/record.url?scp=84952303437&partnerID=8YFLogxK
U2 - 10.1285/i20705948v8n3p374
DO - 10.1285/i20705948v8n3p374
M3 - Article
AN - SCOPUS:84952303437
VL - 8
SP - 374
EP - 381
JO - Electronic Journal of Applied Statistical Analysis
JF - Electronic Journal of Applied Statistical Analysis
IS - 3
ER -