R: Fitting disease models via multinomial logistic models

rhoMLogit {bcROCsurface} | R Documentation

## Fitting disease models via multinomial logistic models

### Description

`rhoMLogit` is used to fit multinomial logistic models to the disease process in the verified subjects.

### Usage

    rhoMLogit(formula, data, test = FALSE, maxit = 500, trace = FALSE)

### Arguments

`formula` | an object of class "formula": a symbolic description of the model to be fitted.
`data` | an optional data frame containing the variables in the model.
`test` | a logical value indicating whether p-values of the regression coefficients should be returned. Default `FALSE`.
`maxit` | maximum number of iterations. Default 500.
`trace` | switch for tracing estimation process. Default `FALSE`.

### Details

In the formula, the response must be a result of `preDATA`, a factor with three levels, say 1, 2, 3. These levels correspond to three classes of disease status, e.g., non-dieseased, intermediate, diseased. The last class (class 3) is considered as the reference level in multinomal logistic model. In presence of verification bias, the missing (`NA`) values correspond to non verified subjects.

### Value

`rhoMLogit` returns a list containing the following components:

`coeff` | a vector of estimated coefficients.
`values` | fitted values of the model.
`Hess` | the Hessian of the measure of fit at the estimated coefficients.
`D` | the disease status vector used.
`X` | a design model matrix.
`formula` | the fomular supplied.

### References

To Duc, K., Chiogna, M. and Adimari, G. (2016) Bias-corrected methods for estimating the receiver operating characteristic surface of continuous diagnostic tests. Electronic Journal of Statistics, 10, 3063-3113.

### See Also

`multinom`, `nnet`

### Examples

    data(EOC)
    Dna <- preDATA(EOC$D, EOC$CA125)
    Dfact.na <- Dna$D
    out <- rhoMLogit(Dfact.na ~ CA125 + CA153 + Age, data = EOC, test = TRUE,
                     trace = TRUE)

[Package bcROCsurface version 1.0-3 Index]