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  "Title": "Network Scale-Up Models for Aggregated Relational Data",
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  "Authors@R": "c(person(\"Ian\", \"Laga\", , \"ilaga25@gmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-5164-4856\")),\nperson(\"Owen G.\", \"Ward\", , \"oward@sfu.ca\", role = c(\"aut\")),\nperson(\"Anna L.\", \"Smith\", role = c(\"aut\")),\nperson(\"Benjamin\", \"Vogel\", role = c(\"aut\")),\nperson(\"Jieyun\", \"Wang\", role = c(\"aut\")),\nperson(\"Le\", \"Bao\", , \"lebao@psu.edu\", role = c(\"aut\")),\nperson(\"Xiaoyue\", \"Niu\", , \"Xiaoyue@psu.edu\", role = c(\"aut\")))",
  "Description": "Provides a variety of Network Scale-up Models for\nresearchers to analyze Aggregated Relational Data, through the\nuse of Stan and 'glmmTMB'. Also provides tools for model\nchecking In this version, the package implements models from\nLaga, I., Bao, L., and Niu, X (2023)\n<doi:10.1080/01621459.2023.2165929>, Zheng, T., Salganik, M.\nJ., and Gelman, A. (2006) <doi:10.1198/016214505000001168>,\nKillworth, P. D., Johnsen, E. C., McCarty, C., Shelley, G. A.,\nand Bernard, H. R. (1998) <doi:10.1016/S0378-8733(96)00305-X>,\nand Killworth, P. D., McCarty, C., Bernard, H. R., Shelley, G.\nA., and Johnsen, E. C. (1998) <doi:10.1177/0193841X9802200205>.",
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  "Author": "Ian Laga [aut, cre] (<https://orcid.org/0000-0002-5164-4856>),\nOwen G. Ward [aut], Anna L. Smith [aut], Benjamin Vogel [aut],\nJieyun Wang [aut], Le Bao [aut], Xiaoyue Niu [aut]",
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      "title": "Compute Pearson Residuals for ARD matrix and fitted model",
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      ]
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      "title": "Compute Randomized Quantile Residuals for ARD Models",
      "topics": [
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    },
    {
      "page": "correlatedStan",
      "title": "Fit ARD using the uncorrelated or correlated model in Stan This function fits the ARD using either the uncorrelated or correlated model in Laga et al. (2021) in Stan. The population size estimates and degrees are scaled using a post-hoc procedure.",
      "topics": [
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      ]
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      "title": "Covariance plots",
      "topics": [
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      ]
    },
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      "title": "Dispersion Metric for Fitted ARD Model",
      "topics": [
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      ]
    },
    {
      "page": "example_data",
      "title": "Simulated ARD data set with z and x.",
      "topics": [
        "example_data"
      ]
    },
    {
      "page": "fit_mle",
      "title": "Fit basic Poisson and Negative Binomial models using glmmTMB",
      "topics": [
        "fit_mle"
      ]
    },
    {
      "page": "get_surrogate",
      "title": "Compute Surrogate Residuals for ARD Models",
      "topics": [
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    },
    {
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      "title": "Hanging Rootogram for Fitted ARD Model",
      "topics": [
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      ]
    },
    {
      "page": "killworth",
      "title": "Fit Killworth models to ARD. This function estimates the degrees and population sizes using the plug-in MLE and MLE estimator.",
      "topics": [
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      "title": "log computed uniform quantile",
      "topics": [
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      "title": "Generate simulated ARD",
      "topics": [
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    },
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      "title": "Construct tibble from ARD matrix",
      "topics": [
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    {
      "page": "networkscaleup",
      "title": "The 'networkscaleup' package.",
      "topics": [
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        "networkscaleup"
      ]
    },
    {
      "page": "overdispersed",
      "title": "Fit Overdispersed model to ARD (Gibbs-Metropolis)",
      "topics": [
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    {
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      "title": "Fit ARD using the Overdispersed model in Stan",
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      "title": "Construction Residual (row/column) correlation matrix",
      "topics": [
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      "title": "Construct heatmap of residuals",
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