Simulated dataset for knockofftools — simdata • knockofftools

A synthetic dataset generated by the function generate_simdata(). It contains simulated Gaussian, binary, and survival outcomes along with covariates.

Usage

simdata

Format

A data frame with 2000 rows and 33 variables:

Yg: Continuous outcome
Yb: Binary outcome
Tc: Treatment indicator
X1: Covariate 1
X2: Covariate 2
X3: Covariate 3
X4: Covariate 4
X5: Covariate 5
X6: Covariate 6
X7: Covariate 7
X8: Covariate 8
X9: Covariate 9
X10: Covariate 10
X11: Covariate 11
X12: Covariate 12
X13: Covariate 13
X14: Covariate 14
X15: Covariate 15
X16: Covariate 16
X17: Covariate 17
X18: Covariate 18
X19: Covariate 19
X20: Covariate 20
X21: Covariate 21
X22: Covariate 22
X23: Covariate 23
X24: Covariate 24
X25: Covariate 25
X26: Covariate 26
X27: Covariate 27
X28: Covariate 28
X29: Covariate 29
X30: Covariate 30

Source

Simulated using generate_simdata()

Examples

data(simdata)
head(simdata)
#>          Yg Yb           Tc X1          X2 X3          X4 X5 X6         X7 X8
#> 1 -8.616078  0 2961.163522+  0 -1.34958449  1 -2.06459293  0  0 -0.2647307  0
#> 2  2.145781  1    14.818694  0  1.17359743  1  0.84017766  1  0  1.3229887  0
#> 3  2.855925  1     5.662159  0  0.06617883  1  0.56828582  1  0 -0.4684210  1
#> 4 -7.393736  0  780.165789+  0  0.60006023  0 -0.88344294  0  0 -1.3543175  0
#> 5 -5.357337  0 1290.810345+  0  0.68195033  0 -0.07230342  0  1 -1.3389652  0
#> 6  3.720681  1     3.590458  1 -0.65766424  1  0.46974365  0  1  0.7223677  1
#>             X9 X10         X11 X12         X13         X14        X15
#> 1 -1.195130146   0 -1.55039791   0 -0.08735044 -1.33663474 -1.4623983
#> 2  0.234492578   0 -0.21080365   1 -0.67754266 -0.95667045 -1.4382052
#> 3  0.741142955   1 -0.42313349   0  0.45978660  0.00745024 -1.0355898
#> 4 -0.569807363   1 -0.44577462   0 -1.49143858 -0.97262600 -0.5287812
#> 5  0.017296645   0 -0.92524890   1  0.60758442 -1.73842365 -1.3498640
#> 6 -0.003889527   0  0.07506359   0  0.32826109 -0.32936413 -0.2840591
#>          X16          X17 X18        X19        X20 X21         X22        X23
#> 1 -1.3602576 -1.382745067   0 -1.5624986 -1.9608922   0 -1.31489967 -2.2169518
#> 2 -0.1488313  1.205061322   1  1.0781760  1.0875351   1 -0.07223664  0.8789803
#> 3  0.5910792 -1.473117296   1 -0.3347650 -1.4291051   1 -0.04198548 -0.0466789
#> 4 -0.4705523 -1.274306922   0 -0.4005423 -1.0422824   0 -0.32670165 -0.6612200
#> 5 -0.1350612 -0.187836365   0 -0.7175496  2.0574928   0 -0.27979989 -0.3521170
#> 6  1.3349541  0.006302787   0 -0.4315391  0.7012275   1  2.34446830 -0.9578781
#>          X24         X25        X26         X27 X28         X29         X30
#> 1 -0.3959303  0.24770510 -1.0483842 -0.33177937   0 -1.32633356  0.06617234
#> 2  0.4031930  0.94219270  1.9536774  1.18859915   1 -0.51142442 -0.29964638
#> 3  0.3532464 -0.44099596 -0.3063321  0.38301926   0 -1.10414929  0.77452133
#> 4 -2.1765509 -0.33151934 -0.2245172  0.69659501   1 -0.08606082 -0.52358577
#> 5 -0.3131376  0.09381092 -0.7891119 -0.08894098   1 -0.23390222  0.25534359
#> 6  0.3491796  1.77765847 -0.1320934  0.35847389   1 -0.92297766  0.39652538