stat_lm: Create an lm stat object.

In aba: Automated Biomarker Analysis

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

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()

aba documentation built on Dec. 17, 2021, 1:06 a.m.