causal-inference-in-R
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`marginaleffects` examples
@malcolmbarrett requested an issue instead of a PR, so here is a copy of examples from the G-computation chapter I posted here: https://github.com/r-causal/causal-inference-in-R/pull/239
# A linear model for wait_minutes_posted_avg
fit_wait_minutes <- lm(
wait_minutes_posted_avg ~
park_extra_magic_morning + park_ticket_season + park_close +
park_temperature_high,
data = seven_dwarfs_9
)
avg_predictions(
fit_wait_minutes,
variables = "park_extra_magic_morning")
park_extra_magic_morning Estimate Std. Error z Pr(>|z|) S 2.5 % 97.5 %
0 68.1 0.915 74.4 <0.001 Inf 66.3 69.9
1 74.2 2.052 36.2 <0.001 949.9 70.2 78.3
avg_predictions(
fit_wait_minutes,
hypothesis = "b2 - b1 = 0",
variables = "park_extra_magic_morning")
Term Estimate Std. Error z Pr(>|z|) S 2.5 % 97.5 %
b2-b1=0 6.16 2.26 2.73 0.00636 7.3 1.74 10.6
fit_wait_minutes_actual <- lm(
wait_minutes_actual_avg ~
ns(wait_minutes_posted_avg, df = 3) +
park_extra_magic_morning +
park_ticket_season + park_close +
park_temperature_high,
data = wait_times
)
avg_predictions(fit_wait_minutes_actual,
variables = list(wait_minutes_posted_avg = c(60, 30))
)
wait_minutes_posted_avg Estimate Std. Error z Pr(>|z|) S 2.5 % 97.5 %
60 29.8 7.05 4.23 <0.001 15.4 16.0 43.7
30 40.7 3.84 10.60 <0.001 84.8 33.2 48.2
avg_comparisons(fit_wait_minutes_actual,
variables = list(wait_minutes_posted_avg = c(60, 30))
)
Term Contrast Estimate Std. Error z Pr(>|z|) S 2.5 % 97.5 %
wait_minutes_posted_avg mean(60) - mean(30) -10.8 8.13 -1.33 0.182 2.5 -26.8 5.09