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silentema 1.0.0

First CRAN release. The statistical code is unchanged from version 0.2.1, so every estimate produced with 0.2.0 or 0.2.1 is reproduced exactly; the release prepares the package for CRAN, completes its documentation and fixes one display issue.

Renamed argument: the number of prompts per person is set by n_prompts in simulate_ema() and simulate_from_fit() (it was called T in 0.2.x, which masks TRUE); the corresponding elements of the returned objects are settings$n_prompts (simulations) and n_prompts (FIML fits). Code written for 0.2.x must replace T = by n_prompts =; the generated data are unchanged.
New vignettes: dm-graphs (the motif taxonomy, d-separation and recoverability), testing-informativeness (the silence test, the sensor-gap test and the fatigue check), sensitivity-analysis (tilting, break-even values, the three calibration designs and the missingness declaration) and simulation-and-design (the simulator, every motif’s parameters, design planning). The workflow vignette is revised.
Every exported function documents its return value in full and has runnable examples; the documentation cites the methods (Mohan & Pearl, 2021; Dhaene & Jochmans, 2015; Shumway & Stoffer, 1982; Cameron & Miller, 2015; Manski, 2003) instead of the numbered propositions of the accompanying manuscript.
Package overview (?silentema) describing the workflow, the data format and the simulator.
DESCRIPTION: method references with DOIs, URL and BugReports fields pointing to the GitHub repository and the documentation site; the title is shortened.
citation("silentema") now points to the CRAN page of the package.
American spelling throughout the documentation.
Subsetting a recoverability, silence_test or sensor_gap_test object with [ now returns a plain data frame; previously the class was kept and the print method showed an incomplete report. No estimate is affected.
Input validation with clear messages: a response-indicator column must be 0/1 without NA; state columns must be complete at answered prompts (item-level missingness is reported instead of producing NA results); a response column named other than the default "R" must exist; the prompt index must be an integer index without NA, also in fatigue_check(); the “too few pairs/triples” messages report the counts and hint at the prompt index. bounds_support() checks its columns and returns the whole scale for a person without any answered prompt (previously NaN).
fit_pairs() (and the tilted fits) warn when no person reaches min_pairs complete pairs, instead of silently returning NaN between-person summaries; fit_fiml() starts from a diagonal between-person covariance when fewer than three persons have enough pairs (previously it failed for one to three persons), stops when the prompt index spans a single prompt, and warns when prompt indices are missing for some persons; fatigue_check() no longer fails when the prompt index has fewer than four distinct values.
tilt_profile(which = ) accepts a variable name; plot.tilt_profile() reports unknown coefficient names; plot.dm_graph() honors a user main; print.delta_calibration() reports failed bootstrap resamples; the EM loop of fit_fiml() checks for user interrupts.

silentema 0.2.1

Metadata release; no change to any R or C++ code, so every result produced with 0.2.0 is reproduced exactly (checked bit-for-bit on six simulation cells).

URL points to the OSF project; the placeholder BugReports field is removed (contact the maintainer by email).
citation("silentema") uses the revised title of the accompanying manuscript, “What skipped prompts hide: Detecting, diagnosing, and correcting informative nonresponse in ecological momentary assessment”.

silentema 0.2.0

Revision after peer review of the accompanying manuscript.

calibrate_delta(method = "postskip") gains burden = "fit": the simulated model includes a burden term (motif M3) calibrated to the observed response persistence, so that the post-skip calibration is valid under a declared M2 + M3 graph. The number of simulated data sets is now n_sim (default 20; formerly B = 10). The result reports the number of crossings, and no crossing is reported as such.
simulate_from_fit() gains days and kappa_R, and stops with a clear message when the fitted dynamics are not stable.
recoverability() distinguishes, under reactivity (M6), the recoverable assessment-conditioned kernel (Phi and Psi) from the dynamics-recovered person mean, which is biased; the observed person mean is judged by d-separation as for the other motifs.
fit_tilt() returns every quantity from one undamped weighted fit at the converged iterate, reports max_weight, passes min_pairs through, and returns class tilt_fit also at delta = 0.
silence_test() gains poly (polynomial degree in the lagged states) and seed; fatigue_check() gains day and a print method; summary.pairs_fit() uses a t(G - 1) reference; coef(), vcov(), confint(), nobs() methods for fits; plot() method for calibrations; plot.dm_graph() redrawn.
missingness_declaration() fills its sections from the test, profile and calibration objects when they are supplied.
Input validation with informative messages (motif codes, column names, integer prompt index, delta length, weights); functions that simulate or bootstrap restore the caller’s random-number state.
Examples for every exported function; American spelling throughout.

silentema 0.1.0

First release accompanying the manuscript “When silence is informative: Dynamic missingness graphs, recoverability, and sensitivity analysis for ecological momentary assessment” (Yu, 2026).

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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