Deficit (frailty) Index (DI) summarizes a range of deficits from in surveys or clinical data sets. "Recalling that frailty is an age-associated, nonspecific vulnerability, we consider symptoms, signs, diseases, and disabilities as deficits, which are combined in a frailty index. An individual's frailty index score reflects the proportion of potential deficits present in that person, and indicates the likelihood that frailty is present. Although based on a simple count, the frailty index shows several interesting properties, including a characteristic rate of accumulation, a submaximal limit, and characteristic changes with age in its distribution. The frailty index, as a state variable, is able to quantitatively summarize vulnerability. Future studies include the application of network analyses and stochastic analytical techniques to the evaluation of the frailty index and the description of other state variables in relation to frailty." 
library(di) # Simulate database of N individuals: N <- 1000 dd <- data.frame(subj=seq(1:N), var1=rbinom(N,1,.5), var2=rbinom(N,1,.5), var3=rbinom(N,1,.5), age=rnorm(N, 80, 20)) # Calculate DI ddi <- di(dd, c("var1", "var2", "var3"))
By default, values are rescaled to the interval [0,1]. If you do not want this, you can set
rescale flag to
ddi <- di(dd, c("var1", "var2", "var3"), rescale = FALSE)
Sometimes it needs to apply a custom scaling. For example if values 0 and 1 incorrectly represent the reality,
the user can apply his own scale: 0 --> 0.2 and 1 --> 0.8. To do this, he needs to use a special grammar:
ddi <- di(dd, c("var1", "var2", "var3"), rescale.custom = c("var1:0.2:0.8", "var3:0.3:0.7"))
ddi <- di(dd, c("var1", "var2", "var3"), rescale.avoid = c("var2"))
invert allows inverting values of some columns (user-defined).
NULL by default.
ddi <- di(dd, c("var1", "var2", "var3"), rescale = FALSE, invert=c("var1", "var3"))
ddi <- di(dd, c("var1", "var2", "var3"), age="age", visible=TRUE)
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