Use all data rows as a group in an aba model.

This is a helper function which allows you to specify a group in an aba model that does not have any filtering conditions. This is useful when you want to specify an aba model with one sub-group of the data but also want to fit models on the entire data. This function is really only necessary to be used instead of a call to set_groups when building an aba model.

Usage

everyone()

Value

This function actually just returns a value of TRUE.

Examples

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

# fit model with one subgroup (DX_bl) and also the entire data
model <- data %>% aba_model() %>%
  set_groups(
    everyone(),
    DX_bl %in% c('MCI', 'AD')
  ) %>%
  set_outcomes(ConvertedToAlzheimers, CSF_ABETA_STATUS_bl) %>%
  set_predictors(PLASMA_ABETA_bl, PLASMA_PTAU181_bl, PLASMA_NFL_bl) %>%
  set_stats(
    stat_glm(std.beta = TRUE)
  ) %>%
  fit()
#> [1] "ConvertedToAlzheimers ~ PLASMA_ABETA_bl"
#> [1] "ConvertedToAlzheimers ~ PLASMA_PTAU181_bl"
#> [1] "ConvertedToAlzheimers ~ PLASMA_NFL_bl"
#> [1] "CSF_ABETA_STATUS_bl ~ PLASMA_ABETA_bl"
#> [1] "CSF_ABETA_STATUS_bl ~ PLASMA_PTAU181_bl"
#> [1] "CSF_ABETA_STATUS_bl ~ PLASMA_NFL_bl"
#> [1] "ConvertedToAlzheimers ~ PLASMA_ABETA_bl"
#> [1] "ConvertedToAlzheimers ~ PLASMA_PTAU181_bl"
#> [1] "ConvertedToAlzheimers ~ PLASMA_NFL_bl"
#> [1] "CSF_ABETA_STATUS_bl ~ PLASMA_ABETA_bl"
#> [1] "CSF_ABETA_STATUS_bl ~ PLASMA_PTAU181_bl"
#> [1] "CSF_ABETA_STATUS_bl ~ PLASMA_NFL_bl"

model_summary <- model %>% aba_summary()