A shortcut to generate one-, two-, or many-sided formulas from vectors of variable names.
formulize(
y = "",
x = "",
...,
data = NULL,
collapse = "+",
collapse.y = collapse,
escape = FALSE
)Character vectors, names, or calls to be collapsed (by "+") and put left-to-right in the formula.
If data is supplied, these can also be numeric, denoting which column name to use. See examples.
An R object with non-null column names.
How should terms be collapsed? Default is addition.
How should the y-terms be collapsed? Default is addition. Also accepts the special string "list", which combines them into a multiple-left-hand-side formula, for use in other functions.
A logical indicating whether character vectors should be coerced to names (that is, whether names with spaces should be surrounded with backticks or not)
## two-sided formula
f1 <- formulize("y", c("x1", "x2", "x3"))
## one-sided formula
f2 <- formulize(x = c("x1", "x2", "x3"))
## multi-sided formula
f3 <- formulize("y", c("x1", "x2", "x3"), c("z1", "z2"), "w1")
## can use numerics for column names
data(mockstudy)
f4 <- formulize(y = 1, x = 2:4, data = mockstudy)
## mix and match
f5 <- formulize(1, c("x1", "x2", "x3"), data = mockstudy)
## get an interaction
f6 <- formulize("y", c("x1*x2", "x3"))
## get only interactions
f7 <- formulize("y", c("x1", "x2", "x3"), collapse = "*")
## no intercept
f8 <- formulize("y", "x1 - 1")
f9 <- formulize("y", c("x1", "x2", "-1"))
## LHS as a list to use in arsenal functions
f10 <- formulize(c("y1", "y2", "y3"), c("x", "z"), collapse.y = "list")
## use in an lm
f11 <- formulize(2, 3:4, data = mockstudy)
summary(lm(f11, data = mockstudy))
#>
#> Call:
#> lm(formula = f11, data = mockstudy)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -41.800 -7.568 0.892 8.432 29.124
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 60.1075 0.5966 100.744 <2e-16 ***
#> armF: FOLFOX 0.6927 0.7088 0.977 0.3286
#> armG: IROX 0.1484 0.8118 0.183 0.8550
#> sexFemale -1.2319 0.6105 -2.018 0.0438 *
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 11.51 on 1495 degrees of freedom
#> Multiple R-squared: 0.003365, Adjusted R-squared: 0.001365
#> F-statistic: 1.683 on 3 and 1495 DF, p-value: 0.1688
#>
## using non-syntactic names or calls (like reformulate example)
f12 <- formulize(as.name("+-"), c("`P/E`", "`% Growth`"))
f12 <- formulize("+-", c("P/E", "% Growth"), escape = TRUE)
f <- Surv(ft, case) ~ a + b
f13 <- formulize(f[[2]], f[[3]])