6533b823fe1ef96bd127f44f
RESEARCH PRODUCT
Response models for mixed binary and quantitative variables
Nanny WermuthDavid Coxsubject
Statistics and ProbabilityChain rule (probability)Applied MathematicsGeneral MathematicsMultivariate normal distributionConditional probability distributionAgricultural and Biological Sciences (miscellaneous)Discriminative modelConditional independenceJoint probability distributionStatisticsStatistics Probability and UncertaintyGeneral Agricultural and Biological SciencesConditional varianceIndependence (probability theory)Mathematicsdescription
SUMMARY A number of special representations are considered for the joint distribution of qualitative, mostly binary, and quantitative variables. In addition to the conditional Gaussian models and to conditional Gaussian regression chain models some emphasis is placed on models derived from an underlying multivariate normal distribution and on models in which discrete probabilities are specified linearly in terms of unknown parameters. The possibilities for choosing between the models empirically are examined, as well as the testing of independence and conditional independence and the estimation of parameters. Often the testing of independence is exactly or nearly the same for a number of different models.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 1992-01-01 | Biometrika |