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simstudy - MaRDI portal

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simstudy (Q27436)

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Simulation of Study Data
Language Label Description Also known as
English
simstudy
Simulation of Study Data

    Statements

    instance of
    R package
    0 references
    software version identifier
    0.6.0
    publication date
    18 February 2023
    0 references
    0.1.1
    publication date
    21 June 2016
    0 references
    0.1.2
    publication date
    8 December 2016
    0 references
    0.1.3
    publication date
    3 July 2017
    0 references
    0.1.4
    publication date
    20 September 2017
    0 references
    0.1.5
    publication date
    3 October 2017
    0 references
    0.1.6
    publication date
    18 October 2017
    0 references
    0.1.7
    publication date
    2 November 2017
    0 references
    0.1.8
    publication date
    8 January 2018
    0 references
    0.1.9
    publication date
    11 May 2018
    0 references
    0.1.10
    publication date
    16 September 2018
    0 references
    0.1.11
    publication date
    7 February 2019
    0 references
    0.1.12
    publication date
    26 February 2019
    0 references
    0.1.13
    publication date
    17 May 2019
    0 references
    0.1.14
    publication date
    9 August 2019
    0 references
    0.1.15
    publication date
    16 October 2019
    0 references
    0.1.16
    publication date
    31 March 2020
    0 references
    0.2.0
    publication date
    6 October 2020
    0 references
    0.2.1
    publication date
    8 October 2020
    0 references
    0.3.0
    publication date
    5 November 2021
    0 references
    0.4.0
    publication date
    20 January 2022
    0 references
    0.5.0
    publication date
    8 July 2022
    0 references
    0.5.1
    publication date
    3 October 2022
    0 references
    0.7.0
    publication date
    1 June 2023
    0 references
    0.7.1
    publication date
    23 November 2023
    0 references
    programmed in
    R
    0 references
    last update
    23 November 2023
    0 references
    description
    Simulates data sets in order to explore modeling techniques or better understand data generating processes. The user specifies a set of relationships between covariates, and generates data based on these specifications. The final data sets can represent data from randomized control trials, repeated measure (longitudinal) designs, and cluster randomized trials. Missingness can be generated using various mechanisms (MCAR, MAR, NMAR).
    0 references
    author
    Keith Goldfeld
    0 references
    Jacob Wujciak-Jens
    0 references
    imports
    data.table
    0 references
    glue
    0 references
    methods
    0 references
    mvnfast
    0 references
    Rcpp
    0 references
    backports
    0 references
    fastglm
    0 references

    Identifiers

    swMATH work ID
    15548
    0 references
    CRAN project
    simstudy
    0 references
     
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