Naive standard error estimates
Function to obtain naive standard error estimates for the parameter
estimates of the get_estimates function, under the GLM or AFT
setting for the analysis of a normally-distributed or censored time-to-event
primary outcome.
naive_se(setting = "GLM", Y = NULL, X = NULL, K = NULL, L = NULL, C = NULL)
setting |
String with value |
Y |
Numeric input vector for the primary outcome. |
X |
Numeric input vector for the exposure variable. |
K |
Numeric input vector for the intermediate outcome. |
L |
Numeric input vector for the observed confounding factor. |
C |
Numeric input vector for the censoring indicator under the AFT setting (must be coded 0 = censored, 1 = uncensored). |
Under the GLM setting for the analysis of a normally-distributed primary outcome Y, naive standard error estimates are obtained for the estimates of the parameters α0, α1, α2, α3, α4, αXY in the models
Y = α0 + α1*K + α2*X + α3*L + ε1, ε1 ~ N(0,σ1^2)
Y* = Y - mean(Y) - α1*(K-mean(K))
Y* = α0 + αXY*X + ε2, ε2 ~ N(0,σ2^2),
using the lm function, without accounting for the
additional variability due to the 2-stage approach.
Returns a vector with the naive standard error estimates of the parameter estimates.
dat <- generate_data(setting = "GLM") naive_se(setting = "GLM", Y = dat$Y, X = dat$X, K = dat$K, L = dat$L)
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