aba (version 0.0.9)

stat_lm: Create an lm stat object.

Description

This function creates a lm stat object which can be passed as input to the set_stats() function when building an aba model. This stat performs a traditional linear regression analysis using the lm function. Coefficients will be presented as beta coefficients. Default metrics include adjusted R2.

Usage

stat_lm(std.beta = FALSE, complete.cases = TRUE)

Arguments

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 lm stat type.

Examples

# NOT RUN {
data <- adnimerge %>% dplyr::filter(VISCODE == 'bl')

# fit lm model with continuous outcome variables
model <- data %>% aba_model() %>%
  set_groups(
    everyone(),
    DX_bl %in% c('MCI', 'AD')
  ) %>%
  set_outcomes(CDRSB_bl, MMSE_bl) %>%
  set_predictors(
    PLASMA_ABETA_bl, PLASMA_PTAU181_bl, PLASMA_NFL_bl,
    c(PLASMA_ABETA_bl, PLASMA_PTAU181_bl, PLASMA_NFL_bl)
  ) %>%
  set_covariates(AGE, GENDER, EDUCATION) %>%
  set_stats(
    stat_lm(std.beta = TRUE)
  ) %>%
  fit()

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

# plot results
fig1 <- model_summary %>% aba_plot_coef()
fig2 <- model_summary %>% aba_plot_metric()

# }