# 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
#
# \dots\dots
# 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
#
# \dots
# 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
#
# \dots
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