epi.cp {epiR} R Documentation

## Extract unique covariate patterns from a data set

### Description

Extract the set of unique patterns from a set of covariates (explanatory variables).

### Usage

```epi.cp(dat)
```

### Arguments

 `dat` an i row by j column data frame where the i rows represent individual observations and the m columns represent a set of m covariates. The function allows for one or more covariates for each observation.

### Details

This function extracts the k unique covariate patterns in a data set comprised of i observations, labelling them from 1 to k. The frequency of occurrence of each covariate pattern is listed. A vector of length i is also returned, listing the 1:k covariate pattern identifier for each observation.

### Value

A list containing the following:

 `cov.pattern` a data frame with columns: `id` the unique covariate pattern identifier (labelled 1 to k), `n` the number of occasions each of the listed covariate pattern appears in the data, and the unique covariate combinations. `id` a vector of length i listing the 1:k covariate pattern identifier for each observation.

### Author(s)

Thanks to Johann Popp and Mathew Jay for providing code and suggestions to enhance the utility of this function.

### References

Dohoo I, Martin W, Stryhn H (2003). Veterinary Epidemiologic Research. AVC Inc, Charlottetown, Prince Edward Island, Canada.

### Examples

```## EXAMPLE 1:

## Generate a set of covariates:
set.seed(seed = 1234)
obs <- round(runif(n = 100, min = 0, max = 1), digits = 0)
v1 <- round(runif(n = 100, min = 0, max = 4), digits = 0)
v2 <- round(runif(n = 100, min = 0, max = 4), digits = 0)
dat.df01 <- data.frame(obs, v1, v2)

dat.glm01 <- glm(obs ~ v1 + v2, family = binomial, data = dat.df01)
dat.mf01 <- model.frame(dat.glm01)

## Covariate pattern. Drop the first column of dat.mf01 (since column 1 is the
## outcome variable:
epi.cp(dat.mf01[,2:3])

## There are 25 covariate patterns in this data set. Subject 100 has
## covariate pattern 21.
```

[Package epiR version 2.0.31 Index]