Results 251 to 260 of about 397,901 (297)
Some of the next articles are maybe not open access.
2005
A large amount of data collected in the social sciences are counts crossclassified into categories. These counts are non-negative integers and require special methods of analysis to model appropriately; log-linear models are one sophisticated method. The counts are modeled by the Poisson distribution, and related to the classifying variables through a ...
openaire +1 more source
A large amount of data collected in the social sciences are counts crossclassified into categories. These counts are non-negative integers and require special methods of analysis to model appropriately; log-linear models are one sophisticated method. The counts are modeled by the Poisson distribution, and related to the classifying variables through a ...
openaire +1 more source
Journal of Clinical Epidemiology, 2008 Objective: In health research, ordinal scales are extensively used. Reproducibility of ratings using these scales is important to assess their quality.
Christiane Guinot, Khaled Ezzedine
exaly +2 more sources
1981
The three preceding chapters have all used models in which the response variables were probabilities (Chapters 4 and 5) or a linear combination of probabilities (Chapter 6). In this chapter we consider a model in which the response function involves the natural logarithm of the response variable.
Ron N. Forthofer, Robert G. Lehnen
openaire +1 more source
The three preceding chapters have all used models in which the response variables were probabilities (Chapters 4 and 5) or a linear combination of probabilities (Chapter 6). In this chapter we consider a model in which the response function involves the natural logarithm of the response variable.
Ron N. Forthofer, Robert G. Lehnen
openaire +1 more source
2006
Abstract Log-linear models for multidimensional tables of discrete data were first popularized by Goodman (1970) and Bishop et al. (1975). These models can be interpreted in terms of interactions between the various factors in multidimensional tables and are easily generalized to higher dimensions.
openaire +1 more source
Abstract Log-linear models for multidimensional tables of discrete data were first popularized by Goodman (1970) and Bishop et al. (1975). These models can be interpreted in terms of interactions between the various factors in multidimensional tables and are easily generalized to higher dimensions.
openaire +1 more source
Log-linear modeling using conditional log-linear structures
Annals of the Institute of Statistical Mathematics, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
VELLAISAMY, P, VIJAY, V
openaire +2 more sources
Table selection and log-linear models
Journal of Chronic Diseases, 1980Abstract The use of multi-dimensional contingency tables has become commonplace in the analysis of epidemiological data. This paper examines two problems in this methodology. First, for data having many response or dependent variables, it is often unclear as to which of many possible tables should be analyzed.
D H, Freeman, J F, Jekel
openaire +2 more sources
Equivalence of Generative and Log-Linear Models
IEEE Transactions on Audio, Speech, and Language Processing, 2011Conventional speech recognition systems are based on hidden Markov models (HMMs) with Gaussian mixture models (GHMMs). Discriminative log-linear models are an alternative modeling approach and have been investigated recently in speech recognition. GHMMs are directed models with constraints, e.g., positivity of variances and normalization of conditional
Georg Heigold +4 more
openaire +1 more source
Log-Linear Modelling and Spatial Analysis
Environment and Planning A: Economy and Space, 1985In the past decade the social sciences have seen an upsurge of interest in analysing multidimensional contingency tables using log-linear models. Two broad families of log-linear models may be distinguished: the family of conventional models and the family of unconventional models (that is, quasi-log-linear and hybrid models).
E Aufhauser, M M Fischer
openaire +3 more sources
2014
The classical log-linear models are introduced for two-way and multi-way contingency tables. Estimation theory, goodness-of-fit testing, and model selection procedures are discussed. Characteristic examples are worked out in R and interpreted. Log-linear models for three-dimensional tables are illustrated through mosaic plots.
openaire +1 more source
The classical log-linear models are introduced for two-way and multi-way contingency tables. Estimation theory, goodness-of-fit testing, and model selection procedures are discussed. Characteristic examples are worked out in R and interpreted. Log-linear models for three-dimensional tables are illustrated through mosaic plots.
openaire +1 more source