Description Usage Arguments Details Value Examples
This function is used to fit the model for the generalized propensity score.
Users can apply this function before multiMatch
and verify that
the output's fitted model object is the same as the user desires.
1 | estimateTrtModel(W, X, match_on, model_options, ...)
|
W |
A treatment vector (1 x n) with numerical values indicating treatment groups |
X |
A covariate matrix (p x n) with no intercept. When match_on="existing", then X must be a vector (1 x n) of user-specified propensity scores. |
match_on |
User specifies "covariates" to match on raw covariates, or "existing" to match on user-supplied propensity score values, or "polr" or "multinom" to fit a propensity score model. |
model_options |
A list of the options to pass to propensity model. Currently under development. Can only pass reference level to multinomial logistic regression. |
... |
the dots argument |
Note that the model_options
argument must be a list with
reference_level
element. Future versions of this package may allow
for the user to supply a fitted model object directly to
multiMatch
; to request this feature, users should go to the
GitHub repository and fill out an Issue requesting it.
A list element with two items:
prop_score_model
the fitted model object
prop_score_ests
the estimated generalized propensity scores
for each individual in the dataset
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | sim_data <- multilevelMatching::simulated_data
Y <- sim_data$outcome
W <- sim_data$treatment
X <- as.matrix(sim_data[ ,-(1:2)])
names(Y) <- paste0("ID", 1:length(Y))
trimming <- FALSE
method <- c("covariates", "polr", "multinom")[2]
prepared_data <- prepareData(
Y = Y,
W = W,
X = X,
match_on = "polr",
trimming = FALSE,
model_options = list(reference_level = sort(W)[1]),
M_matches = 3,
J_var_matches = 2
)
trt_model <- do.call(estimateTrtModel, prepared_data)
estimated_generalized_propensity_scores <- trt_model$prop_score_ests
|
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