Run the eBAC selection-adjusted IPW workflow
Source:R/ipw.R
morie_run_ebac_selection_ipw_analysis.RdMirrors the core outputs of the old 07_ebac_ipw.R workflow.
Usage
morie_run_ebac_selection_ipw_analysis(
data,
output_dir = NULL,
treatment = "cannabis_any_use",
covariates = c("age_group", "gender", "province_region", "mental_health",
"physical_health")
)Examples
# Run on a synthetic CPADS-shaped frame (the CKAN-fetched PUMF works
# identically -- see morie_load_cpads_data() for the real frame):
if (requireNamespace("survey", quietly = TRUE)) {
set.seed(1)
n <- 200
cpads <- data.frame(
weight = runif(n, 0.5, 2),
alcohol_past12m = rbinom(n, 1, 0.8),
heavy_drinking_30d = rbinom(n, 1, 0.3),
ebac_tot = abs(rnorm(n, 0.05, 0.03)),
ebac_legal = rbinom(n, 1, 0.7),
cannabis_any_use = rbinom(n, 1, 0.3),
age_group = sample(1:6, n, TRUE),
gender = sample(1:2, n, TRUE),
province_region = sample(1:5, n, TRUE),
mental_health = sample(1:5, n, TRUE),
physical_health = sample(1:5, n, TRUE)
)
morie_run_ebac_selection_ipw_analysis(cpads)
}
#> Warning: glm.fit: algorithm did not converge
#> $analysis_frame
#> weight alcohol_past12m ebac_tot ebac_legal cannabis_any_use age_group
#> 1 0.8982630 1 0.076810211 1 0 4
#> 2 1.0581858 1 0.018581056 1 1 6
#> 3 1.3592800 1 0.109140122 1 1 5
#> 4 1.8623117 1 0.038491037 0 0 3
#> 5 0.8025229 1 0.099624359 1 1 3
#> 6 1.8475845 1 0.095366381 1 1 2
#> 7 1.9170129 1 0.052488972 1 1 2
#> 8 1.4911967 1 0.067016627 1 1 1
#> 9 1.4436711 1 0.019263546 0 0 5
#> 10 0.5926794 1 0.059690195 1 0 4
#> 12 0.7648351 1 0.052972355 1 1 2
#> 13 1.5305343 1 0.036375893 1 0 3
#> 16 1.2465489 1 0.082074844 0 1 5
#> 17 1.5764278 1 0.035480752 0 1 4
#> 20 1.6661678 1 0.064829385 1 0 6
#> 21 1.9020578 1 0.089237046 1 0 5
#> 22 0.8182138 1 0.094911230 0 0 5
#> 23 1.4775106 1 0.074441082 1 0 1
#> 24 0.6883326 1 0.006093664 0 1 6
#> 26 1.0791711 1 0.063684068 0 0 6
#> 27 0.5200855 1 0.039397991 1 0 2
#> 28 1.0735819 1 0.055114684 1 0 3
#> 29 1.8045363 1 0.024078921 1 1 2
#> 31 1.2231202 1 0.040186970 1 0 3
#> 32 1.3993487 1 0.002927534 1 0 6
#> 33 1.2403120 1 0.038976477 1 0 3
#> 34 0.7793264 1 0.090933048 0 0 1
#> 35 1.7410600 1 0.039971559 1 0 1
#> 36 1.5027001 1 0.071982501 1 1 4
#> 37 1.6913598 1 0.078397569 1 0 1
#> 38 0.6619154 1 0.050131961 1 0 6
#> 39 1.5855664 1 0.039430331 0 0 4
#> 40 1.1169116 1 0.034109135 1 1 4
#> 41 1.7314194 1 0.072187677 1 0 1
#> 42 1.4705903 1 0.018096278 1 0 1
#> 44 1.3295545 1 0.041315019 1 0 2
#> 45 1.2945794 1 0.017946681 1 1 1
#> 46 1.6840343 1 0.007734486 1 1 1
#> 47 0.5349968 1 0.077480580 1 1 5
#> 48 1.2158451 1 0.044261631 1 1 5
#> 49 1.5984706 1 0.074098496 1 1 1
#> 51 1.2164294 1 0.094216435 1 0 1
#> 53 1.1571457 1 0.061398881 1 1 6
#> 54 0.8671959 1 0.044216047 0 1 5
#> 55 0.6060186 1 0.097336754 0 0 1
#> 56 0.6491992 1 0.067887023 1 0 4
#> 57 0.9744076 1 0.014792692 0 0 4
#> 58 1.2779514 1 0.045330724 1 0 2
#> 59 1.4930076 1 0.007567295 1 1 5
#> 61 1.8693139 1 0.027769830 1 0 2
#> 62 0.9404051 1 0.089420065 0 1 3
#> 63 1.1885986 1 0.030933710 0 0 1
#> 64 0.9985920 1 0.037100635 1 1 1
#> 65 1.4763057 1 0.044920450 1 0 5
#> 66 0.8870252 1 0.068366545 0 0 4
#> 67 1.2178179 1 0.070350205 1 0 6
#> 68 1.6494660 1 0.067038559 1 1 6
#> 69 0.6263704 1 0.032823722 0 0 1
#> 70 1.8129820 1 0.009101262 1 0 2
#> 71 1.0086094 1 0.038338333 1 0 1
#> 72 1.7591605 1 0.058337424 1 0 3
#> 73 1.0200252 1 0.025307566 1 1 2
#> 74 1.0006624 1 0.047934772 1 1 3
#> 75 1.2145269 1 0.014970130 0 0 6
#> 76 1.8382975 1 0.049750730 1 0 2
#> 77 1.7965092 1 0.053865662 0 0 1
#> 78 1.0849843 1 0.045623731 1 1 6
#> 79 1.6659810 1 0.045082671 1 1 4
#> 80 1.9409270 1 0.102906560 1 1 4
#> 81 1.1519892 1 0.072877595 1 0 1
#> 82 1.5687720 1 0.083342932 1 0 1
#> 84 0.9880282 1 0.054930255 1 1 4
#> 85 1.6356307 1 0.084644756 1 1 2
#> 86 0.8040384 1 0.048304357 0 0 6
#> 87 1.5666818 1 0.013880819 1 0 5
#> 88 0.6825379 1 0.060345373 1 0 6
#> 89 0.8682328 1 0.007148663 0 0 5
#> 90 0.7149566 1 0.025664895 1 0 4
#> 91 0.8594441 1 0.089720130 1 0 3
#> 92 0.5884016 1 0.068469105 0 1 6
#> 94 1.8144038 1 0.059198146 1 0 5
#> 95 1.6683720 1 0.046695237 0 0 2
#> 96 1.6959632 1 0.022270617 0 0 3
#> 97 1.1829117 1 0.097787413 1 0 1
#> 98 1.1151261 1 0.051350318 1 0 1
#> 99 1.7163054 1 0.028546148 1 0 6
#> 101 1.4820859 1 0.082233229 1 0 5
#> 102 1.0297959 1 0.106869643 1 0 2
#> 103 0.9053902 1 0.031910081 1 0 5
#> 104 1.9890261 1 0.038273965 1 1 1
#> 105 1.4502399 1 0.037513339 1 1 3
#> 107 0.6940585 1 0.039001072 1 0 3
#> 109 1.8861117 1 0.093254612 0 0 3
#> 110 1.3981415 1 0.029073851 1 0 3
#> 111 1.9642560 1 0.038354975 1 0 6
#> 112 1.5976888 1 0.069576094 1 0 4
#> 114 1.1472105 1 0.026836676 1 0 5
#> 115 0.7223173 1 0.034757414 0 0 3
#> 116 0.5196164 1 0.065708618 1 1 5
#> 117 1.5733491 1 0.080532627 1 0 5
#> 118 0.6547764 1 0.042465062 0 0 5
#> 120 1.4601516 1 0.101273631 0 0 1
#> 121 1.9877579 1 0.093052087 1 0 5
#> 122 1.2433904 1 0.028688866 0 0 3
#> 123 1.2265243 1 0.048047973 1 1 1
#> 128 0.8113177 1 0.026612945 1 0 1
#> 129 0.8429872 1 0.030764692 1 0 1
#> 130 1.3935680 1 0.029566058 1 1 4
#> 132 0.6155966 1 0.065028907 1 1 6
#> 133 0.5533109 1 0.004046056 1 0 3
#> 135 1.8929228 1 0.067789542 1 1 4
#> 136 1.3971386 1 0.044054137 1 0 5
#> 137 1.3413511 1 0.076760252 1 0 5
#> 138 1.2890416 1 0.049228548 1 1 1
#> 139 1.9776428 1 0.030570186 0 1 3
#> 142 1.4023118 1 0.103178336 1 0 5
#> 143 0.8583030 1 0.049452209 0 1 3
#> 144 0.8872489 1 0.075584450 1 0 2
#> 145 1.5939644 1 0.056154887 0 0 5
#> 146 1.1788562 1 0.040241458 1 0 6
#> 147 0.7626902 1 0.009016642 1 0 5
#> 148 1.6200474 1 0.037276932 1 0 4
#> 149 0.6574815 1 0.057104110 0 1 2
#> 150 1.7968174 1 0.020281694 1 0 5
#> 151 1.4219675 1 0.078850899 0 0 6
#> 152 1.3357393 1 0.031867228 1 0 5
#> 153 0.9931660 1 0.027413682 0 0 1
#> 154 1.1796972 1 0.003331652 0 0 1
#> 156 0.7712995 1 0.051689955 1 0 3
#> 158 0.6129136 1 0.012936489 1 0 4
#> 160 0.8190493 1 0.066073152 1 1 4
#> 161 0.9271857 1 0.036408887 1 1 2
#> 162 1.8426412 1 0.114961055 1 1 1
#> 164 1.6699773 1 0.067864941 1 0 6
#> 165 1.8209286 1 0.050146533 0 0 4
#> 167 0.5957127 1 0.028822816 0 0 2
#> 168 1.0032312 1 0.068840515 1 0 1
#> 169 1.5855889 1 0.094406419 1 0 2
#> 170 1.0064230 1 0.082502897 1 0 6
#> 171 1.4456212 1 0.025602672 0 0 2
#> 172 1.7609218 1 0.001433695 0 0 4
#> 174 1.0870389 1 0.063226681 1 0 6
#> 175 1.0707408 1 0.090529819 1 1 5
#> 176 1.8431681 1 0.010441715 1 1 1
#> 177 1.4664736 1 0.060931538 1 1 6
#> 179 1.4079552 1 0.085818658 1 0 4
#> 180 1.8546224 1 0.049162701 1 0 2
#> 181 0.9405952 1 0.039281034 1 1 4
#> 182 0.7868902 1 0.015595576 1 0 6
#> 183 1.8296764 1 0.034477385 1 0 4
#> 185 1.8155863 1 0.120516630 0 0 6
#> 186 0.7837904 1 0.123395941 1 0 5
#> 187 1.6371546 1 0.044998902 1 0 3
#> 189 1.9155872 1 0.009188048 1 0 4
#> 191 1.5676158 1 0.017282792 0 0 2
#> 192 1.0833576 1 0.118539780 0 0 2
#> 194 1.8909531 1 0.053333193 1 1 5
#> 195 0.9248488 1 0.164308300 1 1 3
#> 196 1.3858597 1 0.016732700 0 0 2
#> 197 0.6655409 1 0.059226999 0 1 3
#> 198 1.7607605 1 0.016793166 0 1 3
#> 199 0.9769455 1 0.060429609 1 0 5
#> 200 1.6742770 1 0.023802064 1 1 4
#> gender province_region mental_health physical_health R p_hat sw
#> 1 2 5 1 2 1 0.99 1.010101
#> 2 2 4 1 1 1 0.99 1.010101
#> 3 1 5 2 3 1 0.99 1.010101
#> 4 1 2 5 5 1 0.99 1.010101
#> 5 1 3 5 2 1 0.99 1.010101
#> 6 1 3 1 1 1 0.99 1.010101
#> 7 1 3 5 4 1 0.99 1.010101
#> 8 2 2 4 5 1 0.99 1.010101
#> 9 1 3 1 3 1 0.99 1.010101
#> 10 2 2 2 2 1 0.99 1.010101
#> 12 1 4 5 4 1 0.99 1.010101
#> 13 1 4 2 3 1 0.99 1.010101
#> 16 2 2 1 5 1 0.99 1.010101
#> 17 2 4 3 5 1 0.99 1.010101
#> 20 1 3 1 1 1 0.99 1.010101
#> 21 2 5 4 2 1 0.99 1.010101
#> 22 2 2 1 3 1 0.99 1.010101
#> 23 1 1 3 1 1 0.99 1.010101
#> 24 1 3 2 1 1 0.99 1.010101
#> 26 1 1 4 5 1 0.99 1.010101
#> 27 1 4 2 3 1 0.99 1.010101
#> 28 1 1 5 2 1 0.99 1.010101
#> 29 2 4 4 2 1 0.99 1.010101
#> 31 1 5 4 5 1 0.99 1.010101
#> 32 2 5 4 3 1 0.99 1.010101
#> 33 1 2 3 4 1 0.99 1.010101
#> 34 1 2 3 3 1 0.99 1.010101
#> 35 2 1 5 4 1 0.99 1.010101
#> 36 1 4 2 5 1 0.99 1.010101
#> 37 2 2 5 5 1 0.99 1.010101
#> 38 2 1 5 1 1 0.99 1.010101
#> 39 1 3 5 2 1 0.99 1.010101
#> 40 1 3 5 2 1 0.99 1.010101
#> 41 1 1 4 5 1 0.99 1.010101
#> 42 1 5 2 2 1 0.99 1.010101
#> 44 1 2 1 4 1 0.99 1.010101
#> 45 2 3 4 5 1 0.99 1.010101
#> 46 2 5 1 1 1 0.99 1.010101
#> 47 1 4 2 4 1 0.99 1.010101
#> 48 1 2 4 2 1 0.99 1.010101
#> 49 2 1 4 1 1 0.99 1.010101
#> 51 2 1 4 1 1 0.99 1.010101
#> 53 2 1 1 5 1 0.99 1.010101
#> 54 2 2 3 2 1 0.99 1.010101
#> 55 2 3 1 2 1 0.99 1.010101
#> 56 2 5 4 4 1 0.99 1.010101
#> 57 2 2 2 2 1 0.99 1.010101
#> 58 1 3 2 1 1 0.99 1.010101
#> 59 2 4 2 1 1 0.99 1.010101
#> 61 1 1 2 1 1 0.99 1.010101
#> 62 1 2 4 1 1 0.99 1.010101
#> 63 1 3 3 3 1 0.99 1.010101
#> 64 2 3 5 5 1 0.99 1.010101
#> 65 2 2 1 5 1 0.99 1.010101
#> 66 1 4 4 1 1 0.99 1.010101
#> 67 1 5 4 3 1 0.99 1.010101
#> 68 2 4 3 3 1 0.99 1.010101
#> 69 2 1 2 2 1 0.99 1.010101
#> 70 1 3 3 3 1 0.99 1.010101
#> 71 1 5 4 3 1 0.99 1.010101
#> 72 1 2 4 5 1 0.99 1.010101
#> 73 2 3 3 2 1 0.99 1.010101
#> 74 2 3 1 5 1 0.99 1.010101
#> 75 2 3 2 5 1 0.99 1.010101
#> 76 1 2 4 4 1 0.99 1.010101
#> 77 1 3 4 4 1 0.99 1.010101
#> 78 1 3 5 1 1 0.99 1.010101
#> 79 2 4 5 3 1 0.99 1.010101
#> 80 1 4 5 5 1 0.99 1.010101
#> 81 2 2 3 4 1 0.99 1.010101
#> 82 1 1 2 3 1 0.99 1.010101
#> 84 2 5 3 2 1 0.99 1.010101
#> 85 1 2 5 3 1 0.99 1.010101
#> 86 2 2 3 4 1 0.99 1.010101
#> 87 1 1 4 5 1 0.99 1.010101
#> 88 1 2 2 3 1 0.99 1.010101
#> 89 2 2 1 4 1 0.99 1.010101
#> 90 1 2 4 4 1 0.99 1.010101
#> 91 2 5 1 2 1 0.99 1.010101
#> 92 2 2 3 1 1 0.99 1.010101
#> 94 2 3 1 4 1 0.99 1.010101
#> 95 1 3 1 5 1 0.99 1.010101
#> 96 2 2 1 1 1 0.99 1.010101
#> 97 2 3 2 2 1 0.99 1.010101
#> 98 1 2 4 2 1 0.99 1.010101
#> 99 1 3 4 2 1 0.99 1.010101
#> 101 1 4 2 5 1 0.99 1.010101
#> 102 1 4 2 4 1 0.99 1.010101
#> 103 2 4 5 1 1 0.99 1.010101
#> 104 2 1 4 2 1 0.99 1.010101
#> 105 2 3 3 1 1 0.99 1.010101
#> 107 2 4 3 2 1 0.99 1.010101
#> 109 1 1 2 5 1 0.99 1.010101
#> 110 1 2 4 4 1 0.99 1.010101
#> 111 1 3 4 4 1 0.99 1.010101
#> 112 1 2 1 4 1 0.99 1.010101
#> 114 2 5 4 3 1 0.99 1.010101
#> 115 2 5 4 2 1 0.99 1.010101
#> 116 1 2 5 5 1 0.99 1.010101
#> 117 1 2 2 3 1 0.99 1.010101
#> 118 2 3 4 5 1 0.99 1.010101
#> 120 1 2 3 2 1 0.99 1.010101
#> 121 1 1 2 5 1 0.99 1.010101
#> 122 1 5 5 3 1 0.99 1.010101
#> 123 2 2 2 5 1 0.99 1.010101
#> 128 2 2 5 1 1 0.99 1.010101
#> 129 2 1 3 2 1 0.99 1.010101
#> 130 2 1 3 5 1 0.99 1.010101
#> 132 1 5 3 3 1 0.99 1.010101
#> 133 2 5 3 2 1 0.99 1.010101
#> 135 2 2 3 3 1 0.99 1.010101
#> 136 2 4 5 3 1 0.99 1.010101
#> 137 1 3 2 3 1 0.99 1.010101
#> 138 2 5 5 2 1 0.99 1.010101
#> 139 1 3 4 1 1 0.99 1.010101
#> 142 2 2 2 1 1 0.99 1.010101
#> 143 1 1 5 1 1 0.99 1.010101
#> 144 2 3 2 5 1 0.99 1.010101
#> 145 2 4 3 2 1 0.99 1.010101
#> 146 2 3 5 1 1 0.99 1.010101
#> 147 1 2 3 1 1 0.99 1.010101
#> 148 2 1 4 4 1 0.99 1.010101
#> 149 2 5 5 5 1 0.99 1.010101
#> 150 1 4 2 3 1 0.99 1.010101
#> 151 1 2 5 5 1 0.99 1.010101
#> 152 2 5 4 5 1 0.99 1.010101
#> 153 2 3 3 5 1 0.99 1.010101
#> 154 2 5 2 4 1 0.99 1.010101
#> 156 2 1 2 1 1 0.99 1.010101
#> 158 2 3 5 4 1 0.99 1.010101
#> 160 2 3 2 3 1 0.99 1.010101
#> 161 2 5 5 4 1 0.99 1.010101
#> 162 2 2 5 5 1 0.99 1.010101
#> 164 2 1 1 1 1 0.99 1.010101
#> 165 2 5 2 1 1 0.99 1.010101
#> 167 1 5 4 5 1 0.99 1.010101
#> 168 2 2 5 2 1 0.99 1.010101
#> 169 2 2 1 3 1 0.99 1.010101
#> 170 1 3 1 1 1 0.99 1.010101
#> 171 2 5 1 4 1 0.99 1.010101
#> 172 2 4 4 2 1 0.99 1.010101
#> 174 2 4 2 2 1 0.99 1.010101
#> 175 1 3 4 2 1 0.99 1.010101
#> 176 2 3 3 4 1 0.99 1.010101
#> 177 2 5 4 4 1 0.99 1.010101
#> 179 1 4 2 5 1 0.99 1.010101
#> 180 1 1 1 5 1 0.99 1.010101
#> 181 2 1 4 3 1 0.99 1.010101
#> 182 2 3 4 2 1 0.99 1.010101
#> 183 1 1 5 4 1 0.99 1.010101
#> 185 1 5 2 2 1 0.99 1.010101
#> 186 2 1 5 1 1 0.99 1.010101
#> 187 2 3 5 5 1 0.99 1.010101
#> 189 1 3 2 1 1 0.99 1.010101
#> 191 1 3 5 1 1 0.99 1.010101
#> 192 1 5 4 4 1 0.99 1.010101
#> 194 2 4 2 5 1 0.99 1.010101
#> 195 2 1 1 1 1 0.99 1.010101
#> 196 1 5 3 2 1 0.99 1.010101
#> 197 2 4 2 3 1 0.99 1.010101
#> 198 1 4 5 4 1 0.99 1.010101
#> 199 2 5 3 5 1 0.99 1.010101
#> 200 2 4 4 1 1 0.99 1.010101
#> sw_trim w_combined_trim
#> 1 1.010101 0.9073364
#> 2 1.010101 1.0688746
#> 3 1.010101 1.3730101
#> 4 1.010101 1.8811229
#> 5 1.010101 0.8106292
#> 6 1.010101 1.8662470
#> 7 1.010101 1.9363767
#> 8 1.010101 1.5062593
#> 9 1.010101 1.4582536
#> 10 1.010101 0.5986661
#> 12 1.010101 0.7725607
#> 13 1.010101 1.5459942
#> 16 1.010101 1.2591403
#> 17 1.010101 1.5923513
#> 20 1.010101 1.6829978
#> 21 1.010101 1.9212706
#> 22 1.010101 0.8264786
#> 23 1.010101 1.4924350
#> 24 1.010101 0.6952855
#> 26 1.010101 1.0900719
#> 27 1.010101 0.5253389
#> 28 1.010101 1.0844262
#> 29 1.010101 1.8227639
#> 31 1.010101 1.2354749
#> 32 1.010101 1.4134836
#> 33 1.010101 1.2528404
#> 34 1.010101 0.7871984
#> 35 1.010101 1.7586464
#> 36 1.010101 1.5178789
#> 37 1.010101 1.7084442
#> 38 1.010101 0.6686015
#> 39 1.010101 1.6015822
#> 40 1.010101 1.1281936
#> 41 1.010101 1.7489085
#> 42 1.010101 1.4854447
#> 44 1.010101 1.3429843
#> 45 1.010101 1.3076559
#> 46 1.010101 1.7010448
#> 47 1.010101 0.5404008
#> 48 1.010101 1.2281264
#> 49 1.010101 1.6146168
#> 51 1.010101 1.2287166
#> 53 1.010101 1.1688340
#> 54 1.010101 0.8759555
#> 55 1.010101 0.6121400
#> 56 1.010101 0.6557568
#> 57 1.010101 0.9842501
#> 58 1.010101 1.2908600
#> 59 1.010101 1.5080885
#> 61 1.010101 1.8881958
#> 62 1.010101 0.9499041
#> 63 1.010101 1.2006046
#> 64 1.010101 1.0086788
#> 65 1.010101 1.4912179
#> 66 1.010101 0.8959850
#> 67 1.010101 1.2301191
#> 68 1.010101 1.6661273
#> 69 1.010101 0.6326973
#> 70 1.010101 1.8312949
#> 71 1.010101 1.0187974
#> 72 1.010101 1.7769298
#> 73 1.010101 1.0303285
#> 74 1.010101 1.0107701
#> 75 1.010101 1.2267948
#> 76 1.010101 1.8568662
#> 77 1.010101 1.8146558
#> 78 1.010101 1.0959438
#> 79 1.010101 1.6828091
#> 80 1.010101 1.9605323
#> 81 1.010101 1.1636255
#> 82 1.010101 1.5846182
#> 84 1.010101 0.9980083
#> 85 1.010101 1.6521522
#> 86 1.010101 0.8121600
#> 87 1.010101 1.5825069
#> 88 1.010101 0.6894322
#> 89 1.010101 0.8770028
#> 90 1.010101 0.7221784
#> 91 1.010101 0.8681254
#> 92 1.010101 0.5943450
#> 94 1.010101 1.8327311
#> 95 1.010101 1.6852243
#> 96 1.010101 1.7130942
#> 97 1.010101 1.1948603
#> 98 1.010101 1.1263900
#> 99 1.010101 1.7336418
#> 101 1.010101 1.4970565
#> 102 1.010101 1.0401979
#> 103 1.010101 0.9145356
#> 104 1.010101 2.0091173
#> 105 1.010101 1.4648888
#> 107 1.010101 0.7010692
#> 109 1.010101 1.9051633
#> 110 1.010101 1.4122641
#> 111 1.010101 1.9840970
#> 112 1.010101 1.6138270
#> 114 1.010101 1.1587985
#> 115 1.010101 0.7296135
#> 116 1.010101 0.5248650
#> 117 1.010101 1.5892415
#> 118 1.010101 0.6613903
#> 120 1.010101 1.4749006
#> 121 1.010101 2.0078363
#> 122 1.010101 1.2559499
#> 123 1.010101 1.2389134
#> 128 1.010101 0.8195128
#> 129 1.010101 0.8515022
#> 130 1.010101 1.4076444
#> 132 1.010101 0.6218147
#> 133 1.010101 0.5588999
#> 135 1.010101 1.9120432
#> 136 1.010101 1.4112511
#> 137 1.010101 1.3549001
#> 138 1.010101 1.3020622
#> 139 1.010101 1.9976190
#> 142 1.010101 1.4164766
#> 143 1.010101 0.8669727
#> 144 1.010101 0.8962110
#> 145 1.010101 1.6100651
#> 146 1.010101 1.1907639
#> 147 1.010101 0.7703941
#> 148 1.010101 1.6364115
#> 149 1.010101 0.6641227
#> 150 1.010101 1.8149671
#> 151 1.010101 1.4363308
#> 152 1.010101 1.3492316
#> 153 1.010101 1.0031980
#> 154 1.010101 1.1916133
#> 156 1.010101 0.7790904
#> 158 1.010101 0.6191047
#> 160 1.010101 0.8273225
#> 161 1.010101 0.9365512
#> 162 1.010101 1.8612537
#> 164 1.010101 1.6868458
#> 165 1.010101 1.8393218
#> 167 1.010101 0.6017300
#> 168 1.010101 1.0133649
#> 169 1.010101 1.6016050
#> 170 1.010101 1.0165889
#> 171 1.010101 1.4602234
#> 172 1.010101 1.7787089
#> 174 1.010101 1.0980191
#> 175 1.010101 1.0815564
#> 176 1.010101 1.8617860
#> 177 1.010101 1.4812865
#> 179 1.010101 1.4221769
#> 180 1.010101 1.8733560
#> 181 1.010101 0.9500962
#> 182 1.010101 0.7948386
#> 183 1.010101 1.8481580
#> 185 1.010101 1.8339256
#> 186 1.010101 0.7917075
#> 187 1.010101 1.6536915
#> 189 1.010101 1.9349366
#> 191 1.010101 1.5834503
#> 192 1.010101 1.0943007
#> 194 1.010101 1.9100537
#> 195 1.010101 0.9341907
#> 196 1.010101 1.3998583
#> 197 1.010101 0.6722635
#> 198 1.010101 1.7785460
#> 199 1.010101 0.9868137
#> 200 1.010101 1.6911889
#>
#> $ebac_final_ipw_diagnostics
#> metric value
#> 1 eligible_n 163.000000
#> 2 observed_n 163.000000
#> 3 observed_rate 1.000000
#> 4 sw_min 1.010101
#> 5 sw_q01 1.010101
#> 6 sw_q99 1.010101
#> 7 sw_max 1.010101
#> 8 ess_survey_x_ipw_trim 147.038198
#>
#> $ebac_final_ipw_or
#> model term log_odds se or
#> 1 selection_adjusted_ipw cannabis_any_use 0.7876379 0.451863 2.198198
#> or_lower95 or_upper95 p_value significant
#> 1 0.9003952 5.366615 0.08328822
#>
#> $ebac_final_ipw_linear
#> model term estimate se ci_lower95
#> 1 selection_adjusted_ipw cannabis_any_use 0.006261202 0.005298678 -0.00420521
#> ci_upper95 p_value significant
#> 1 0.01672761 0.2391414
#>
#> $ebac_final_ipw_comparison
#> metric model estimate ci_lower95
#> 1 ebac_legal_or_cannabis selection_adjusted_ipw 2.198197912 0.90039520
#> 2 ebac_tot_beta_cannabis selection_adjusted_ipw 0.006261202 -0.00420521
#> ci_upper95 p_value
#> 1 5.36661464 0.08328822
#> 2 0.01672761 0.23914135
#>