Description Usage Arguments Value References See Also Examples

This function performs an association analysis between a CNV and a dependent variable (phenotype) using a latent class model that incorporates the uncertainty arising from calling procedure. The phenotype may be quantitative or categorical. In the second case (e.g. case-control studies) this variable must be coded as 1 (for cases) and 0 (for controls). The association can be adjusted for other covariates (e.g. clinical covariates, stratification, ...)

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`formula` |
an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted. Right side of ~ should have an object of class 'cnv'. |

`data` |
an optional data frame, list or environment (or object coercible by 'as.data.frame' to a data frame) containing the variables in the model. If not found in 'data', the variables are taken from 'environment(formula)'. |

`subset` |
an optional vector specifying a subset of observations to be used in the fitting process. |

`na.action` |
a function which indicates what should happen when the data contain 'NA's. The default is set by the 'na.action' setting of 'options', and is 'na.fail' if that is unset. The 'factory-fresh' default is 'na.omit'. Another possible value is 'NULL', no action. Value 'na.exclude' can be useful. |

`model` |
Genetic model to be tested. Possible values are "multiplicative" (model free, e.g. co-dominant) or "additive", partial matching allowed. Default value is "multiplicative". |

`family` |
a description of the error distribution and link function to be used in the model. This must be a character string naming a family function. Possible values are "binomial", "gaussian", "poisson" or "weibull". Default value is "binomial" |

`tol` |
Tolerance for convergence in fitting model. Default value is 1e-06. |

`max.iter` |
Maximum number of iterations in fitting model. Default value is 30. |

`emsteps` |
Number of iterations using Expectation Maximization (EM) alghorithm to set initial values before using Newton-Rapson (NR) in fitting model. Default value is zero, that means that EM step is not performed |

`verbose` |
logical. If TRUE parameter values for each iteration are shown in the console. Default value is FALSE |

`coef.start` |
initial values for coefficients in NR procedure |

`sigma.start` |
initial values for scale parameter (only for "gaussian") in NR procedure |

`alpha.start` |
initial values for shape parameter (only for "weibull") in NR procedure |

An object of class 'CNVassoc'.
'print' returns model parameter estimates
'summary' returns a summary table similar to summary.glm
'anova' performs a Likelihood Ratio Test comparing two nested models fitted
using `CNVassoc`

'logLik' returns the log-likelihood of a model fitted using `CNVassoc`

See examples for further illustration about all previous issues.

Gonzalez JR, Subirana I, Escaramis G, Peraza S, Caceres A, Estivill X and
Armengol L. Accounting for uncertainty when assessing association between
copy number and disease: a latent class model. *BMC Bioinformatics*,
2009;10:172.

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