One way is to create functions that create lags explicitly like this:
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
lags <- purrr::map(1:4, ~rlang::quo(dplyr::lag(., .x))) %>%
purrr::set_names(paste0("lag", 1:4))
tibble::as_tibble(mtcars) %>%
dplyr::mutate_all(lags)
#> # A tibble: 32 x 55
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
#> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
#> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
#> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
#> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
#> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
#> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
#> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
#> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
#> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
#> # … with 22 more rows, and 44 more variables: mpg_lag1 <dbl>,
#> # cyl_lag1 <dbl>, disp_lag1 <dbl>, hp_lag1 <dbl>, drat_lag1 <dbl>,
#> # wt_lag1 <dbl>, qsec_lag1 <dbl>, vs_lag1 <dbl>, am_lag1 <dbl>,
#> # gear_lag1 <dbl>, carb_lag1 <dbl>, mpg_lag2 <dbl>, cyl_lag2 <dbl>,
#> # disp_lag2 <dbl>, hp_lag2 <dbl>, drat_lag2 <dbl>, wt_lag2 <dbl>,
#> # qsec_lag2 <dbl>, vs_lag2 <dbl>, am_lag2 <dbl>, gear_lag2 <dbl>,
#> # carb_lag2 <dbl>, mpg_lag3 <dbl>, cyl_lag3 <dbl>, disp_lag3 <dbl>,
#> # hp_lag3 <dbl>, drat_lag3 <dbl>, wt_lag3 <dbl>, qsec_lag3 <dbl>,
#> # vs_lag3 <dbl>, am_lag3 <dbl>, gear_lag3 <dbl>, carb_lag3 <dbl>,
#> # mpg_lag4 <dbl>, cyl_lag4 <dbl>, disp_lag4 <dbl>, hp_lag4 <dbl>,
#> # drat_lag4 <dbl>, wt_lag4 <dbl>, qsec_lag4 <dbl>, vs_lag4 <dbl>,
#> # am_lag4 <dbl>, gear_lag4 <dbl>, carb_lag4 <dbl>
Created on 2019-05-08 by the reprex package (v0.2.1)
There is probably a more streamlined way to do it, but it escapes me at the moment.