Create a glm stat object. — stat

This function creates a glm stat object which can be passed as input to the set_stats() function when building an aba model. This stat performs a traditional logistic regression analysis using the glm function with a binary outcome. Coefficients will be presented as odds ratios. Default metrics include AUC.

Usage

stat_cox(time, std.beta = FALSE, complete.cases = TRUE)

Arguments

time: string. The "time under risk" variable determining how long e.g. the individual has been in the study or when the individual got the disease.
std.beta: logical. Whether to standardize model predictors and covariates prior to analysis.
complete.cases: logical. Whether to only include the subset of data with no missing data for any of the outcomes, predictors, or covariates. Note that complete cases are considering within each group - outcome combination but across all predictor sets.

Value

An abaStat object with glm stat type.

Examples

data <- adnimerge %>% dplyr::filter(VISCODE == 'bl')

# fit model
model <- data %>% aba_model() %>%
  set_groups(everyone()) %>%
  set_outcomes(ConvertedToAlzheimers, ConvertedToDementia) %>%
  set_predictors(
    PLASMA_PTAU181_bl, PLASMA_NFL_bl,
    c(PLASMA_PTAU181_bl, PLASMA_NFL_bl)
  ) %>%
  set_stats(
    stat_cox(time = 'TimeUnderRiskDementia')
  ) %>%
  fit()

## summarise model
model_summary <- model %>% summary()