sim.statistics.logistic {simitation}

sim.statistics.logistic

Description

sim.statistics.logistic

Usage

sim.statistics.logistic(simdat, the.formula, grouping.variables)

Arguments

simdat

Data for use in multivariable regression models across one or more experiments. Structure is in the form returned by the function simitation::simulation.steps().

the.formula

A formula object or character value specifying the formula for the regression model.

grouping.variables

A character vector of column names from simdat on which to group the data. The intended regression model will be fit in groups based on this selection.

Value

A list containing: * 'the.coefs': A data frame of logistic regression coefficients for each group and predictor variable. * 'summary.stats': A data frame of summary statistics for each group, such as the Akaike Information Criterion (AIC), deviance, residuals, and other metrics.

Examples

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")