Description Usage Arguments Value Examples
View source: R/estimate_surrogate_value.R
Estimate the surrogate value of a longitudinal marker
1 2 | estimate_surrogate_value(y_t, y_c, X_t, X_c, method = c("gam", "linear",
"kernel"), k = 3, bootstrap_samples = 0, alpha = 0.05, ...)
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y_t |
vector of n1 outcome measurements for treatment group |
y_c |
vector of n0 outcome measurements for control or reference group |
X_t |
n1 x T matrix of longitudinal surrogate measurements for treatment group |
X_c |
n0 x T matrix of longitudinal surrogate measurements for control or reference group |
method |
method for dimension-reduction of longitudinal surrogate, either 'gam', 'linear', or 'kernel' |
bootstrap_samples |
number of bootstrap samples to use for variance estimation. The default is 0, which estimates without providing a variance estimate. |
a tibble containing estimates, standard errors, and quantile-based confidence intervals for the residual treatment effect Deltahat_s_*
and the proportion of treatment effect explained R_*
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | library(dplyr)
library(longsurr)
full_data <-
generate_discontinuous_data(n = 50, n_i = 5, delta_s = 0.5,
k = 1, s_y = 0.1, s_x = 0.1)$full_ds
wide_ds <- full_data %>%
dplyr::select(id, a, tt, x, y) %>%
tidyr::spread(tt, x)
wide_ds_0 <- wide_ds %>% filter(a == 0)
wide_ds_1 <- wide_ds %>% filter(a == 1)
X_t <- wide_ds_1 %>% dplyr::select(`-1`:`1`) %>% as.matrix
y_t <- wide_ds_1 %>% pull(y)
X_c <- wide_ds_0 %>% dplyr::select(`-1`:`1`) %>% as.matrix
y_c <- wide_ds_0 %>% pull(y)
estimate_surrogate_value(y_t = y_t, y_c = y_c, X_t = X_t, X_c = X_c, method = 'kernel')
estimate_surrogate_value(y_t = y_t, y_c = y_c, X_t = X_t, X_c = X_c, method = 'linear', bootstrap_sample = 50)
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