Makes a basic cross-classified design with random intercepts for subjects and items. See vignette("sim_mixed", package = "faux") for examples and details.
Usage
sim_mixed_cc(
sub_n = 100,
item_n = 20,
grand_i = 0,
sub_sd = 1,
item_sd = 1,
error_sd = 1,
empirical = FALSE,
seed = NULL
)Arguments
- sub_n
the number of subjects
- item_n
the number of items
- grand_i
the grand intercept (overall mean)
- sub_sd
the SD of subject random intercepts (or a sub_n-length named vector of random intercepts for each subject)
- item_sd
the SD of item random intercepts (or an item_n-length named vector of random intercepts for each item)
- error_sd
the SD of the error term
- empirical
Should the returned data have these exact parameters? (versus be sampled from a population with these parameters)
- seed
DEPRECATED use set.seed() instead before running this function
Examples
sim_mixed_cc(10, 10)
#> sub_id item_id y grand_i sub_i item_i err
#> 1 S01 I01 0.11138858 0 -0.82934037 0.5061139 0.43461501
#> 15 S01 I02 -0.81307920 0 -0.82934037 -0.6422030 0.65846421
#> 29 S01 I03 -1.66215884 0 -0.82934037 -1.1919609 0.35914242
#> 31 S01 I04 -1.45637848 0 -0.82934037 0.4521354 -1.07917352
#> 44 S01 I05 1.57035956 0 -0.82934037 0.6939601 1.70573986
#> 58 S01 I06 0.24612839 0 -0.82934037 -0.4971279 1.57259663
#> 61 S01 I07 -0.83501241 0 -0.82934037 0.3780080 -0.38368010
#> 73 S01 I08 -1.28364991 0 -0.82934037 0.8327482 -1.28705774
#> 87 S01 I09 -1.00667299 0 -0.82934037 0.3245808 -0.50191343
#> 91 S01 I10 -2.41694772 0 -0.82934037 -0.6686266 -0.91898072
#> 7 S02 I01 0.38242003 0 -0.06023448 0.5061139 -0.06345943
#> 17 S02 I02 -1.00337281 0 -0.06023448 -0.6422030 -0.30093528
#> 30 S02 I03 0.64387703 0 -0.06023448 -1.1919609 1.89607241
#> 36 S02 I04 -0.04437200 0 -0.06023448 0.4521354 -0.43627293
#> 46 S02 I05 0.93350809 0 -0.06023448 0.6939601 0.29978251
#> 59 S02 I06 0.21732575 0 -0.06023448 -0.4971279 0.77468810
#> 69 S02 I07 2.02137827 0 -0.06023448 0.3780080 1.70360470
#> 75 S02 I08 -0.66778463 0 -0.06023448 0.8327482 -1.44029835
#> 88 S02 I09 -0.60798030 0 -0.06023448 0.3245808 -0.87232662
#> 98 S02 I10 -0.49725439 0 -0.06023448 -0.6686266 0.23160672
#> 4 S03 I01 2.49090018 0 1.34776012 0.5061139 0.63702612
#> 18 S03 I02 0.15831488 0 1.34776012 -0.6422030 -0.54724220
#> 23 S03 I03 0.40971307 0 1.34776012 -1.1919609 0.25391385
#> 33 S03 I04 1.05150517 0 1.34776012 0.4521354 -0.74839036
#> 47 S03 I05 3.11838800 0 1.34776012 0.6939601 1.07666781
#> 60 S03 I06 0.69103818 0 1.34776012 -0.4971279 -0.15959408
#> 62 S03 I07 2.67788323 0 1.34776012 0.3780080 0.95211506
#> 76 S03 I08 2.34414047 0 1.34776012 0.8327482 0.16363215
#> 89 S03 I09 2.30780323 0 1.34776012 0.3245808 0.63546231
#> 95 S03 I10 0.36930499 0 1.34776012 -0.6686266 -0.30982849
#> 5 S04 I01 -0.59715435 0 -0.78918445 0.5061139 -0.31408385
#> 19 S04 I02 -1.73718977 0 -0.78918445 -0.6422030 -0.30580228
#> 21 S04 I03 -2.94840448 0 -0.78918445 -1.1919609 -0.96725913
#> 34 S04 I04 -0.90078488 0 -0.78918445 0.4521354 -0.56373584
#> 48 S04 I05 0.04137551 0 -0.78918445 0.6939601 0.13659990
#> 51 S04 I06 -0.66987520 0 -0.78918445 -0.4971279 0.61643711
#> 63 S04 I07 -1.31699202 0 -0.78918445 0.3780080 -0.90581563
#> 77 S04 I08 -1.35974362 0 -0.78918445 0.8327482 -1.40330737
#> 90 S04 I09 -1.15253512 0 -0.78918445 0.3245808 -0.68793147
#> 92 S04 I10 -1.19224042 0 -0.78918445 -0.6686266 0.26557066
#> 2 S05 I01 0.41217672 0 -1.18833080 0.5061139 1.09439358
#> 16 S05 I02 -0.33439624 0 -1.18833080 -0.6422030 1.49613760
#> 22 S05 I03 -1.74597311 0 -1.18833080 -1.1919609 0.63431859
#> 35 S05 I04 -0.45096370 0 -1.18833080 0.4521354 0.28523169
#> 45 S05 I05 1.37559688 0 -1.18833080 0.6939601 1.86996761
#> 52 S05 I06 -1.73749243 0 -1.18833080 -0.4971279 -0.05203376
#> 64 S05 I07 -0.51364858 0 -1.18833080 0.3780080 0.29667416
#> 74 S05 I08 -1.75790240 0 -1.18833080 0.8327482 -1.40231980
#> 81 S05 I09 -2.19217044 0 -1.18833080 0.3245808 -1.32842044
#> 93 S05 I10 -0.15771656 0 -1.18833080 -0.6686266 1.69924088
#> 8 S06 I01 1.49336642 0 0.32257455 0.5061139 0.66467793
#> 20 S06 I02 0.52537690 0 0.32257455 -0.6422030 0.84500540
#> 27 S06 I03 -0.40365785 0 0.32257455 -1.1919609 0.46572851
#> 37 S06 I04 -0.32497178 0 0.32257455 0.4521354 -1.09968173
#> 49 S06 I05 0.74367159 0 0.32257455 0.6939601 -0.27286302
#> 56 S06 I06 0.36325946 0 0.32257455 -0.4971279 0.53781278
#> 66 S06 I07 0.62531139 0 0.32257455 0.3780080 -0.07527121
#> 79 S06 I08 0.01706845 0 0.32257455 0.8327482 -1.13825430
#> 85 S06 I09 -0.51735938 0 0.32257455 0.3245808 -1.16451473
#> 99 S06 I10 -0.74506277 0 0.32257455 -0.6686266 -0.39901069
#> 9 S07 I01 3.03083449 0 1.76121962 0.5061139 0.76350093
#> 11 S07 I02 0.25139416 0 1.76121962 -0.6422030 -0.86762241
#> 24 S07 I03 -0.47973858 0 1.76121962 -1.1919609 -1.04899730
#> 38 S07 I04 1.96185120 0 1.76121962 0.4521354 -0.25150382
#> 50 S07 I05 3.97965980 0 1.76121962 0.6939601 1.52448012
#> 53 S07 I06 1.53723118 0 1.76121962 -0.4971279 0.27313943
#> 67 S07 I07 0.88787363 0 1.76121962 0.3780080 -1.25135403
#> 80 S07 I08 2.91541459 0 1.76121962 0.8327482 0.32144678
#> 82 S07 I09 2.27017645 0 1.76121962 0.3245808 0.18437603
#> 96 S07 I10 1.15472060 0 1.76121962 -0.6686266 0.06212762
#> 6 S08 I01 -0.04392048 0 -1.01533990 0.5061139 0.46530549
#> 12 S08 I02 -1.58833128 0 -1.01533990 -0.6422030 0.06921167
#> 25 S08 I03 -2.01904268 0 -1.01533990 -1.1919609 0.18825812
#> 39 S08 I04 -0.19768427 0 -1.01533990 0.4521354 0.36552023
#> 41 S08 I05 0.81118587 0 -1.01533990 0.6939601 1.13256571
#> 54 S08 I06 0.28676473 0 -1.01533990 -0.4971279 1.79923250
#> 68 S08 I07 0.61764890 0 -1.01533990 0.3780080 1.25498075
#> 78 S08 I08 0.23708792 0 -1.01533990 0.8327482 0.41967963
#> 83 S08 I09 -1.95214982 0 -1.01533990 0.3245808 -1.26139072
#> 97 S08 I10 -1.43443099 0 -1.01533990 -0.6686266 0.24953555
#> 3 S09 I01 -0.38713573 0 -2.05044979 0.5061139 1.15720013
#> 13 S09 I02 -4.00771209 0 -2.05044979 -0.6422030 -1.31505926
#> 26 S09 I03 -4.21696298 0 -2.05044979 -1.1919609 -0.97455229
#> 32 S09 I04 -2.04476999 0 -2.05044979 0.4521354 -0.44645561
#> 42 S09 I05 -0.91695699 0 -2.05044979 0.6939601 0.43953273
#> 55 S09 I06 -3.03708015 0 -2.05044979 -0.4971279 -0.48950249
#> 65 S09 I07 -3.17478653 0 -2.05044979 0.3780080 -1.50234479
#> 71 S09 I08 -2.75573318 0 -2.05044979 0.8327482 -1.53803158
#> 84 S09 I09 -0.76157538 0 -2.05044979 0.3245808 0.96429361
#> 94 S09 I10 -3.19036334 0 -2.05044979 -0.6686266 -0.47128692
#> 10 S10 I01 1.74805343 0 -0.46470130 0.5061139 1.70664079
#> 14 S10 I02 -1.77162146 0 -0.46470130 -0.6422030 -0.66471711
#> 28 S10 I03 -2.83179482 0 -0.46470130 -1.1919609 -1.17513261
#> 40 S10 I04 0.94557174 0 -0.46470130 0.4521354 0.95813763
#> 43 S10 I05 0.44438112 0 -0.46470130 0.6939601 0.21512236
#> 57 S10 I06 -0.83565213 0 -0.46470130 -0.4971279 0.12617704
#> 70 S10 I07 0.61424683 0 -0.46470130 0.3780080 0.70094009
#> 72 S10 I08 0.13552063 0 -0.46470130 0.8327482 -0.23252626
#> 86 S10 I09 -1.62008039 0 -0.46470130 0.3245808 -1.47995988
#> 100 S10 I10 -0.54536553 0 -0.46470130 -0.6686266 0.58796241