# ------------------------------------------------
# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# ------------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "silentema" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'silentema: Dynamic Missingness Graphs and Sensitivity Analysis for EMA Data'
version: 1.0.0
identifiers:
- type: url
  value: https://osf.io/x6d2t/
abstract: Tools for diagnosing and correcting informative nonresponse in ecological
  momentary assessment (EMA) and other experience-sampling designs. Declares the assumed
  nonresponse mechanism as a dynamic missingness graph built from a taxonomy of seven
  motifs, following the graphical missing-data framework of Mohan and Pearl (2021)
  <https://doi.org/10.1080/01621459.2021.1874961>; checks by d-separation which within-person
  and between-person estimands of a two-level vector autoregressive model remain recoverable
  and by which estimator; tests whether skipped prompts were informative (the silence
  test and the sensor-gap test, with cluster-robust inference after Cameron and Miller
  (2015) <https://doi.org/10.3368/jhr.50.2.317>); estimates the temporal and contemporaneous
  networks from answered adjacent prompts with the half-panel jackknife of Dhaene
  and Jochmans (2015) <https://doi.org/10.1093/restud/rdv007>, by inverse-probability
  weighting on an observed context, and by full-information maximum likelihood with
  the state-space expectation-maximization (EM) algorithm of Shumway and Stoffer (1982)
  <https://doi.org/10.1111/j.1467-9892.1982.tb00349.x>; profiles the estimates over
  a self-censoring sensitivity parameter (inverse-probability weighting with a fixed
  probit selection model whose intercept is calibrated to the response rate); calibrates
  that parameter from passive sensors, randomized probes, or the post-skip contrast;
  computes worst-case bounds for person means in the spirit of Manski (2003) <https://doi.org/10.1007/b97478>;
  writes a preregistration-ready missingness declaration; and simulates experience-sampling
  data under every motif. The methods are described in Yu (2026, manuscript under
  review); the accompanying materials are archived at <https://osf.io/x6d2t/>.
authors:
- family-names: Yu
  given-names: Hsiu-Ting
  email: hsiutingyu@gmail.com
  orcid: https://orcid.org/0000-0002-3668-8033
preferred-citation:
  type: unpublished
  title: 'What skipped prompts hide: Detecting, diagnosing, and correcting informative
    nonresponse in ecological momentary assessment'
  authors:
  - family-names: Yu
    given-names: Hsiu-Ting
    email: hsiutingyu@gmail.com
    orcid: https://orcid.org/0000-0002-3668-8033
  year: '2026'
  notes: Manuscript under review
  url: https://osf.io/x6d2t/
repository: https://hsiutingyu.r-universe.dev
repository-code: https://github.com/hsiutingyu/silentema
commit: 1966db3533db80b80309dc5d34036e62d8e49c2c
url: https://hsiutingyu.github.io/silentema/
date-released: '2026-09-28'
contact:
- family-names: Yu
  given-names: Hsiu-Ting
  email: hsiutingyu@gmail.com
  orcid: https://orcid.org/0000-0002-3668-8033
references:
- type: manual
  title: 'silentema: Dynamic Missingness Graphs and Sensitivity Analysis for EMA Data'
  authors:
  - family-names: Yu
    given-names: Hsiu-Ting
  year: '2026'
  notes: R package version 1.0.0
  url: https://CRAN.R-project.org/package=silentema