step.age <- "Age ~ N(45, 10)"
step.female <- "Female ~ binary(0.53)"
step.health.percentile <- "Health.Percentile ~ U(0,100)"
step.exercise.sessions <- "Exercise.Sessions ~ Poisson(2)"
step.diet <- "Diet ~ sample(('Light', 'Moderate', 'Heavy'),
(0.2, 0.45, 0.35))"
step.healthy.lifestyle <- "Healthy.Lifestyle ~ logistic(log(0.45) - 0.1 * (Age -45)
+ 0.05 * Female + 0.01 * Health.Percentile + 0.5 * Exercise.Sessions - 0.1 * (Diet
== 'Moderate') - 0.4 * (Diet == 'Heavy'))"
step.weight <- "Weight ~ lm(150 - 15 * Female + 0.5 * Age - 0.1 *
Health.Percentile - 0.2 * Exercise.Sessions + 5 * (Diet == 'Moderate') +
15 * (Diet == 'Heavy') - 2 * Healthy.Lifestyle + N(0, 10))"
the.steps <- c(step.age, step.female, step.health.percentile,
step.exercise.sessions, step.diet, step.healthy.lifestyle, step.weight)
simdat.multivariate <- simulation.steps(the.steps = the.steps, n = 50,
num.experiments = 2, experiment.name = "sim", seed = 41)
stats.logistic <- sim.statistics.logistic(simdat = simdat.multivariate,
the.formula = Healthy.Lifestyle ~ Age + Female + Health.Percentile +
Exercise.Sessions, grouping.variables = "sim")
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