df_netKmax6: An example of a row-dependent dataset with known network of at most 6 friends.
Description
Simulated dataset containing 3 measured i.i.d. baseline covariates (W1
, W2
, W3
), dependent binary exposure (A
)
and dependent binary binary outcome (Y
), along with a known network of friends encoded by strings on space separated
friend IDs in Net_str
.
The baseline covariates (W1
,W2
,W3
) were sampled as i.i.d.,
while the exposure value of A
for each observation i
was sampled
conditionally on the values of i
's baseline covariates (W1[i]
W2[i]
, W3[i]
),
as well as the baseline covariate values of i
's friends in Net_str
.
Similarly, the binary outcome Y
for each observation was generated conditionally on i
's
exposure and baseline covariates values in (W1[i]
,W2[i]
,W3[i]
,A[i]
),
as well as the values of exposures and baseline covariates of i
's friends in Net_str
.
Individual variables are described below.
Format
A data frame with 1,000 dependent observations (rows) and 6 variables:
- IDs
- unique observation identifier
- W1
- categorical baseline covariate (independent), range 0-5
- W2
- binary baseline covariate (independent)
- W3
- binary baseline covariate (independent)
- A
- binary exposure that depends on unit's baseline covariate values, as well as the
baseline covariate values of observations in the friend network
Net_str
- Y
- binary outcome that depends on unit's baseline covariate value and exposure, as well as the
baseline covariate values and exposures of observations in the friend network
Net_str
- nFriends
- number of friends for each observation (row), range 0-6
- Net_str
- a vector of strings, where for each observation its a string of space separated friend IDs (this can
be either observation IDs or just space separated friend row numbers)