Greg (version 1.2)

simpleRmsAnova: A simpler latex output of the latex.anova.rms

Description

The original problem is that the anova default function output is very detailed and cause a complaint in Sweave/knitr that \hbox is overfull. It basically changes capitalized TOTAL, TOTAL INTERACTION and TOTAL NONLINEAR INTERACTION into lower case letters. It also deletes the (Factor + Higher Order Factors).

Usage

simpleRmsAnova(anova_output, subregexps, digits = 4, pval_lim.sig = 10^-4, rowlabel = "", ...)
"print"(x, html = TRUE, ...)

Arguments

anova_output

An object from the anova() function

subregexps

A 2 column matrix with sub() regular expressions to search for and their substitutions. The regular expression should be located in column 1 and the substitution in column 2.

digits

Number of digits in using the round

pval_lim.sig

The threshold before setting "

rowlabel

The label of the rows

...

Passed on to latex() or htmlTable

x

The output object from the SimpleRmsAnova function

html

If HTML output through the htmlTable should be used instead of traditional latex() function

Value

void See the latex() function

Examples

# ** Borrowed code from the lrm example **

#Fit a logistic model containing predictors age, blood.pressure, sex
#and cholesterol, with age fitted with a smooth 5-knot restricted cubic 
#spline function and a different shape of the age relationship for males 
#and females.  

library(rms)
n <- 1000    # define sample size
set.seed(17) # so can reproduce the results
age            <- rnorm(n, 50, 10)
blood.pressure <- rnorm(n, 120, 15)
cholesterol    <- rnorm(n, 200, 25)
sex            <- factor(sample(c('female','male'), n,TRUE))
label(age)            <- 'Age'      # label is in Hmisc
label(cholesterol)    <- 'Total Cholesterol'
label(blood.pressure) <- 'Systolic Blood Pressure'
label(sex)            <- 'Sex'
units(cholesterol)    <- 'mg/dl'   # uses units.default in Hmisc
units(blood.pressure) <- 'mmHg'

#To use prop. odds model, avoid using a huge number of intercepts by
#grouping cholesterol into 40-tiles

# Specify population model for log odds that Y=1
L <- .4*(sex=='male') + .045*(age-50) +
     (log(cholesterol - 10)-5.2)*(-2*(sex=='female') + 2*(sex=='male'))
# Simulate binary y to have Prob(y=1) = 1/[1+exp(-L)]
y <- ifelse(runif(n) < plogis(L), 1, 0)
cholesterol[1:3] <- NA   # 3 missings, at random

ddist <- datadist(age, blood.pressure, cholesterol, sex)
options(datadist='ddist')

fit_lrm <- lrm(y ~ blood.pressure + sex * (age + rcs(cholesterol,4)),
               x=TRUE, y=TRUE)
             
a_out <- anova(fit_lrm, 
               dec.F = 1,
               ss    = FALSE)
             
simpleRmsAnova(a_out, 
               subregexps = rbind(c("age", "Age"),
                                  c("cholesterol", "Cholesterol"),
                                  c("sex", "Sex")),
               caption="Anova output for a logistic regression model")