Applied Epidemiology Using R by Tomas J. Aragon

By Tomas J. Aragon

This publication fills the space as an advent to R particularly for epidemiologists. It offers all of the helpful heritage to start with R, paintings with R facts gadgets, and deal with epidemiological info in R. It then covers info research and pics for addressing difficulties in epidemiology, together with the main subject matters of confounding and outbreak research. The textual content is full of workouts to augment figuring out and specified labored examples utilizing actual facts from epidemiological studies.

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On occasion we need to generate random numbers or draw a sample from a collection of elements. 5. 01802 There are additional ways to create vectors. 4 on page 32 and spend a few minutes creating simple vectors. function name or help(function name ). 3 Naming vectors The first way of naming vector elements is when the vector is created: > x <- c(chol = 234, sbp = 148, dbp = 78, age = 54) 36 2 Working with R data objects > x chol 234 sbp 148 dbp 78 age 54 The second way is to create a character vector of names and then assign that vector to the numeric vector using the names function: > z <- c(234, 148, 78, 54) > z [1] 234 148 78 54 > names(z) <- c("chol", "sbp", "dbp", "age") > z chol sbp dbp age 234 148 78 54 The names function, without an assignment, returns the character vector of names, if it exist.

We will do this using R as a calculator. 0000000 Now let’s review each line briefly to understand the analysis in more detail. dat <- matrix(c(30, 174, 21, 184), 2, 2) We used the matrix function to take a vector and convert it into a matrix with 2 rows and 2 columns. Notice the matrix function reads in the vector column-wise. To read the vector in row-wise we would add the byrow=TRUE option. Try creating a matrix reading in a vector column-wise (default) and row-wise. rownames(dat) <- c("Deaths", "Survivors") colnames(dat) <- c("Tolbutamide", "Placebo") We used the rownames and the colnames functions to assign row and column names to the matrix dat.

We can think of a matrix as a vector with a 2dimensional structure. When R returns a matrix the [n,] indicates the nth row and [,m] indicates the mth column. > x <- c("a", "b", "c", "d") > y <- matrix(x, 2, 2) > y [,1] [,2] [1,] "a" "c" [2,] "b" "d" An array is a collection of like elements organized into a n-dimensional data object. We can think of an array as a vector with an n-dimensional structure. When R returns an array the [n,,] indicates the nth row and [,m,] indicates the mth column, and so on.

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