triples | R Documentation |

Create a triples match

```
triples(cost, z, st, solver = "rrelaxiv")
```

`cost` |
List of matrices of distances between treated (rows) and control (columns) units within a stratum with one entry in the list per stratum |

`z` |
Vector of treatment assignment (0 for control, 1 for treated) |

`st` |
Vector of stratum assignments |

`solver` |
Solver to use for the network problem. Either 'rrelaxiv' or 'rlemon'. 'rrelaxiv' can be downloaded from "https://github.com/josherrickson/rrelaxiv/" |

Named list with three elements: 'm' contains the triples match. This is in the form of a data.frame with number of rows equal to the number of triples and 8 columns specifying the match number, the names of the three units within the match, the costs of the two treated-control pairs within the match, the number of treated units, and the stratum. 'obj' contains the total objective from the network optimization and 'bound' contains a loose lower bound on the objective of the optimal match.

```
# Generate some data
set.seed(1)
n <- 40
x <- rnorm(n, 0, 1)
nt <- floor(n * 0.4)
nc <- n - nt
z <- c(rep(1, nt), rep(0, nc))
# Create some strata
ps <- glm(z ~ x, family = binomial)$fitted.values
ps_st <- cut(ps, c(0, quantile(ps, 1/3 * 1:2), 1), labels = 1:3)
# Create a distance matrix
dist <- dist_mahal(data.frame(x = x), z, ps_st)
# Construct the triples match
triplesm <- triples(cost = dist, z = z, st = ps_st, solver = "rlemon")
```

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