{
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  "Package": "simDAG",
  "Title": "Simulate Data from a (Time-Dependent) Causal DAG",
  "Version": "1.0.0",
  "Authors@R": "c(\nperson(\"Robin\", \"Denz\", , \"robin.denz@rub.de\", role = c(\"aut\", \"cre\")),\nperson(\"Katharina\", \"Meiszl\", , \"meiszl@amib.rub-uni-bochum.de\", role = c(\"aut\"))\n)",
  "Maintainer": "Robin Denz <robin.denz@rub.de>",
  "Description": "Simulate complex data from a given directed acyclic graph\nand information about each individual node. Root nodes are\nsimply sampled from the specified distribution. Child Nodes are\nsimulated according to one of many implemented regressions,\nsuch as logistic regression, linear regression, poisson\nregression or any other function. Also includes a comprehensive\nframework for discrete-time simulation, discrete-event\nsimulation, and networks-based simulation which can generate\neven more complex longitudinal and dependent data. For more\ndetails, see Robin Denz, Nina Timmesfeld (2026)\n<doi:10.18637/jss.v116.i02>.",
  "License": "GPL (>= 3)",
  "URL": "https://github.com/RobinDenz1/simDAG,\nhttps://robindenz1.github.io/simDAG/",
  "BugReports": "https://github.com/RobinDenz1/siMDAG/issues",
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  "Repository": "https://robindenz1.r-universe.dev",
  "Date/Publication": "2026-05-14 07:05:42 UTC",
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  "Author": "Robin Denz [aut, cre],\nKatharina Meiszl [aut]",
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    "dag_from_data",
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    "do",
    "empty_dag",
    "long2start_stop",
    "matrix2dag",
    "net",
    "network",
    "network_td",
    "node",
    "node_aalen",
    "node_aftreg",
    "node_ahreg",
    "node_binomial",
    "node_competing_events",
    "node_conditional_distr",
    "node_conditional_prob",
    "node_cox",
    "node_ehreg",
    "node_gaussian",
    "node_identity",
    "node_mixture",
    "node_multinomial",
    "node_negative_binomial",
    "node_next_time",
    "node_poisson",
    "node_polr",
    "node_poreg",
    "node_td",
    "node_time_to_event",
    "node_ypreg",
    "node_zeroinfl",
    "rbernoulli",
    "rcategorical",
    "rconstant",
    "rsample",
    "rtexp",
    "sim_discrete_event",
    "sim_discrete_time",
    "sim_from_dag",
    "sim_n_datasets",
    "sim2data"
  ],
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    {
      "page": "simDAG",
      "title": "Simulate Data from a DAG and Associated Node Information",
      "topics": [
        "simDAG-package"
      ]
    },
    {
      "page": "add_node",
      "title": "Add a 'DAG.node' or a 'DAG.network' object to a 'DAG' object",
      "topics": [
        "+.DAG",
        "add_node"
      ]
    },
    {
      "page": "as_tidy_dagitty.DAG",
      "title": "Transform a 'DAG' object into a 'tidy_dagitty' object",
      "topics": [
        "as_tidy_dagitty.DAG"
      ]
    },
    {
      "page": "as.dagitty.DAG",
      "title": "Transform a 'DAG' object into a 'dagitty' object",
      "topics": [
        "as.dagitty.DAG"
      ]
    },
    {
      "page": "as.igraph.DAG",
      "title": "Transform a 'DAG' object into an 'igraph' object",
      "topics": [
        "as.igraph.DAG"
      ]
    },
    {
      "page": "dag_from_data",
      "title": "Fills a partially specified 'DAG' object with parameters estimated from reference data",
      "topics": [
        "dag_from_data"
      ]
    },
    {
      "page": "dag2matrix",
      "title": "Obtain a Adjacency Matrix from a 'DAG' object",
      "topics": [
        "dag2matrix"
      ]
    },
    {
      "page": "do",
      "title": "Pearls do-operator for 'DAG' objects",
      "topics": [
        "do"
      ]
    },
    {
      "page": "empty_dag",
      "title": "Initialize an empty 'DAG' object",
      "topics": [
        "empty_dag"
      ]
    },
    {
      "page": "long2start_stop",
      "title": "Transform a 'data.table' in the long-format to a 'data.table' in the start-stop format",
      "topics": [
        "long2start_stop"
      ]
    },
    {
      "page": "matrix2dag",
      "title": "Obtain a 'DAG' object from a Adjacency Matrix and a List of Node Types",
      "topics": [
        "matrix2dag"
      ]
    },
    {
      "page": "net",
      "title": "Specify Network Dependencies in a 'DAG'",
      "topics": [
        "net"
      ]
    },
    {
      "page": "network",
      "title": "Create a network object for a 'DAG'",
      "topics": [
        "network",
        "network_td"
      ]
    },
    {
      "page": "node",
      "title": "Create a node object for a 'DAG'",
      "topics": [
        "node",
        "node_td"
      ]
    },
    {
      "page": "node_aalen",
      "title": "Generate Data from an Aalen Additive Hazards Model",
      "topics": [
        "node_aalen"
      ]
    },
    {
      "page": "node_binomial",
      "title": "Generate Data from a (Mixed) Binomial Regression Model",
      "topics": [
        "node_binomial"
      ]
    },
    {
      "page": "node_competing_events",
      "title": "Generate Data with Multiple Mutually Exclusive Events in Discrete-Time Simulation",
      "topics": [
        "node_competing_events"
      ]
    },
    {
      "page": "node_conditional_distr",
      "title": "Generate Data by Sampling from Different Distributions based on Strata",
      "topics": [
        "node_conditional_distr"
      ]
    },
    {
      "page": "node_conditional_prob",
      "title": "Generate Data Using Conditional Probabilities",
      "topics": [
        "node_conditional_prob"
      ]
    },
    {
      "page": "node_cox",
      "title": "Generate Data from a Cox-Regression Model",
      "topics": [
        "node_cox"
      ]
    },
    {
      "page": "node_gaussian",
      "title": "Generate Data from a (Mixed) Linear Regression Model",
      "topics": [
        "node_gaussian"
      ]
    },
    {
      "page": "node_identity",
      "title": "Generate Data based on an expression",
      "topics": [
        "node_identity"
      ]
    },
    {
      "page": "node_mixture",
      "title": "Generate Data from a Mixture of Node Definitions",
      "topics": [
        "node_mixture"
      ]
    },
    {
      "page": "node_multinomial",
      "title": "Generate Data from a Multinomial Regression Model",
      "topics": [
        "node_multinomial"
      ]
    },
    {
      "page": "node_negative_binomial",
      "title": "Generate Data from a Negative Binomial Regression Model",
      "topics": [
        "node_negative_binomial"
      ]
    },
    {
      "page": "node_next_time",
      "title": "Generate the Next Time of an Event in Discrete-Event Simulation",
      "topics": [
        "node_next_time"
      ]
    },
    {
      "page": "node_poisson",
      "title": "Generate Data from a (Mixed) Poisson Regression Model",
      "topics": [
        "node_poisson"
      ]
    },
    {
      "page": "node_polr",
      "title": "Generate Data from an Ordered Logistic or Probit Regression",
      "topics": [
        "node_polr"
      ]
    },
    {
      "page": "node_rsurv",
      "title": "Generate Data from Parametric Survival Models",
      "topics": [
        "node_aftreg",
        "node_ahreg",
        "node_ehreg",
        "node_poreg",
        "node_rsurv",
        "node_ypreg"
      ]
    },
    {
      "page": "node_time_to_event",
      "title": "Generate Data from repeated Bernoulli Trials in Discrete-Time Simulation",
      "topics": [
        "node_time_to_event"
      ]
    },
    {
      "page": "node_zeroinfl",
      "title": "Generate Data from a Zero-Inflated Count Model",
      "topics": [
        "node_zeroinfl"
      ]
    },
    {
      "page": "plot.DAG",
      "title": "Plot a 'DAG' object",
      "topics": [
        "plot.DAG"
      ]
    },
    {
      "page": "plot.simDT",
      "title": "Plot a Flowchart for a Discrete-Time Simulation",
      "topics": [
        "plot.simDT"
      ]
    },
    {
      "page": "rbernoulli",
      "title": "Generate Random Draws from a Bernoulli Distribution",
      "topics": [
        "rbernoulli"
      ]
    },
    {
      "page": "rcategorical",
      "title": "Generate Random Draws from a Discrete Set of Labels with Associated Probabilities",
      "topics": [
        "rcategorical"
      ]
    },
    {
      "page": "rconstant",
      "title": "Use a single constant value for a root node",
      "topics": [
        "rconstant"
      ]
    },
    {
      "page": "rsample",
      "title": "Sample values from a given vector",
      "topics": [
        "rsample"
      ]
    },
    {
      "page": "rtexp",
      "title": "Generate Data from a left-truncated exponential distribution",
      "topics": [
        "rtexp"
      ]
    },
    {
      "page": "sim_discrete_event",
      "title": "Simulate Data from a 'DAG' with Time-Dependent Variables in Continuous Time",
      "topics": [
        "sim_discrete_event"
      ]
    },
    {
      "page": "sim_discrete_time",
      "title": "Simulate Data from a 'DAG' with Time-Dependent Variables in Discrete Time",
      "topics": [
        "sim_discrete_time"
      ]
    },
    {
      "page": "sim_from_DAG",
      "title": "Simulate Data from a 'DAG'",
      "topics": [
        "sim_from_dag"
      ]
    },
    {
      "page": "sim_n_datasets",
      "title": "Simulate multiple datasets from a single 'DAG' object",
      "topics": [
        "sim_n_datasets"
      ]
    },
    {
      "page": "sim2data",
      "title": "Transform 'sim_discrete_time' output into the start-stop, long- or wide-format",
      "topics": [
        "as.data.frame.simDT",
        "as.data.table.simDT",
        "sim2data"
      ]
    }
  ],
  "_pkglogo": "https://github.com/robindenz1/simdag/raw/HEAD/man/figures/logo.png",
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