While latent class (LC) modeling using bias-adjusted stepwise approaches has become widely popular, little is known on how these methods are affected by missing values. Using synthetic data sets, we illustrate under which conditions values introduce biases in the estimates of relationship between membership and auxiliary variables. We apply three-step LC analysis with both modal proportional as...

FCA has been successfully applied to software engineering tasks such as source code analysis and class hierarchy re-organization. Most notably, FCA puts mathematics behind the mechanism of abstracting from a set of concrete software artifacts. A key limitation of current FCA-based methods is the lack of support for relational information (e.g., associations between classes of a hierarchy): the ...

abstract aims: the increasing usage of antibiotics can cause resistance to the treatment of infections, which can caused by bacteria, e.g. pseudomonas aeruginosa. the aim of this study was to trace the class i, ii and iii integrons in isolates of p. aeruginosa of nosocomial infection and determining the antibiotic resistance pattern of the bacteria. instrument & methods: in this cross-sectional...

investigation on structure and dynamics of natural forest ecosystems is an important issue for silvicultural decisions. the aim of this study is to analysis dynamics and structure of a beech stand during 5-year period in the shast kalateh forest in the caspian region, north of iran. data were collected from a 16.9ha permanent research plot established in a natural unlogged stand in 2006. all li...

Summary Usually in latent class (LC) analysis, external predictors are taken to be cluster conditional probability (LC models with predictors), and/or score regression models). In such cases, their distribution is not of interest. Class‐specific interest the distal outcome model, when variables assumed depend on LC membership. this paper, we consider a more general formulation, that embeds both...