NetInd.to.sparseAdjMat

Matrix of network IDs of dimension <code>(n=nrow(sparseAdjMat),Kmax)</code>,
where each row <code>i</code> consists of the network IDs (row number of friends) of observation <code>i</code>. Remainders are filled with <code>NA</code>s.

NetInd_k

Integer vector of length <code>n</code> specifying the number of friends for each observation.

Convert <code>simcausal</code> network ID matrix (<code>NetInd_k</code>) into a network represented by a sparse adjacency matrix.

A flexible tool for simulating complex longitudinal data using
    structural equations, with emphasis on problems in causal inference.
    Specify interventions and simulate from intervened data generating
    distributions. Define and evaluate treatment-specific means, the average
    treatment effects and coefficients from working marginal structural models.
    User interface designed to facilitate the conduct of transparent and
    reproducible simulation studies, and allows concise expression of complex
    functional dependencies for a large number of time-varying nodes. See the
    package vignette for more information, documentation and examples.

NetInd.to.sparseAdjMat: Convert Network IDs Matrix into Sparse Adjacency Matrix

Description

Usage

Arguments

Value

See Also