complete_data: A data.frame. Data observed and unobserved.
observed: A data.frame. Data observed.
nodes_to_observe: A list. Nodes to observe.
prob: A scalar. Observation probability.
m: A integer. Number of units to observe; if specified, m
overrides prob.
subset: A character. Logical statement that can be applied to rows of complete data. For instance observation for some nodes might depend on observed values of other nodes; or observation may only be sought if data not already observed!
Returns
A data.frame with logical values indicating which nodes to observe in each row of complete_data.
Examples
model <- make_model("X -> Y")df <- make_data(model, n =8)# Observe X values onlyCausalQueries:::observe_data(complete_data = df, nodes_to_observe ="X")# Observe half the Y values for cases with observed X = 1CausalQueries:::observe_data(complete_data = df, observed = CausalQueries:::observe_data(complete_data = df, nodes_to_observe ="X"), nodes_to_observe ="Y", prob =.5, subset ="X==1")
See Also
Other data_generation: data_helpers, get_all_data_types(), make_data_single()