na.detail.response {Hmisc} | R Documentation

## Detailed Response Variable Information

### Description

This function is called by certain `na.action` functions if `options(na.detail.response=TRUE)` is set. By default, this function returns a matrix of counts of non-NAs and the mean of the response variable computed separately by whether or not each predictor is NA. The default action uses the last column of a `Surv` object, in effect computing the proportion of events. Other summary functions may be specified by using `options(na.fun.response="name of function")`.

### Usage

    na.detail.response(mf)

### Arguments

`mf` | a model frame

### Value

a matrix, with rows representing the different statistics that are computed for the response, and columns representing the different subsets for each predictor (NA and non-NA value subsets).

### Author(s)

Frank Harrell
Department of Biostatistics
Vanderbilt University
f.harrell@vanderbilt.edu

### See Also

`na.omit`, `na.delete`, `model.frame.default`, `naresid`, `naprint`, `describe`

### Examples

    # sex
    # [1] m f f m f f m m m m m m m m f f f m f m
    # age
    # [1] NA 41 23 30 44 22 NA 32 37 34 38 36 36 50 40 43 34 22 42 30
    # y
    # [1] 0 1 0 0 1 0 1 0 0 1 1 1 0 0 1 1 0 1 0 0
    # options(na.detail.response=TRUE, na.action="na.delete", digits=3)
    # lrm(y ~ age*sex)
    #
    # Logistic Regression Model
    #
    # lrm(formula = y ~ age * sex)
    #
    #
    # Frequencies of Responses
    #   0 1
    #  10 8
    #
    # Frequencies of Missing Values Due to Each Variable
    #  y age sex
    #  0   2   0
    #
    #
    # Statistics on Response by Missing/Non-Missing Status of Predictors
    #
    #     age=NA age!=NA sex!=NA Any NA  No NA
    #   N    2.0  18.000   20.00    2.0 18.000
    # Mean    0.5   0.444    0.45    0.5  0.444
    #
    # ......
    # options(na.action="na.keep")
    # describe(y ~ age*sex)
    # Statistics on Response by Missing/Non-Missing Status of Predictors
    #
    #      age=NA age!=NA sex!=NA Any NA  No NA
    #    N    2.0  18.000   20.00    2.0 18.000
    # Mean    0.5   0.444    0.45    0.5  0.444
    #
    # ...
    # options(na.fun.response="table")  #built-in function table()
    # describe(y ~ age*sex)
    #
    # Statistics on Response by Missing/Non-Missing Status of Predictors
    #
    #   age=NA age!=NA sex!=NA Any NA No NA
    # 0      1      10      11      1    10
    # 1      1       8       9      1     8
    #
    # ...

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