High-Performance Open-Source Archive
id to global variables for dplyr
compatibility (#260)add_trans_prob: better documentation, proper
examples, attribute attachment, and base R speeduppamm() when data does not contain an
offset columnbroom to Suggestsadd_trans_prob help page with proper parameter
descriptions and working examplegeom_stepribbonmethods from pamm. Can be
specified via .... Fixes #200warn_about_new_time_points when original data
not stored in model object. Fixes #203split_data function that now accepts
Surv(start, stop, event) type inputs, e.g., to construct
left-truncated data.as_ped.ped now also works for transformations with
time-dependent covariatespamm,
which is a thin wrapper around mgcv::gam with some
arguments pre-set.predictSurvProb.pammpecas_ped changed. The vertical bar | is no
longer necessary to indicate concurrent or cumulative effectsFunctions get_hazard and add_hazard
also gain reference argument. Allows to calculate
(log-)hazard ratios.
Introduces breaking changes to add_term function.
Argument relative is replaced by reference,
makes calculation of relative (log-)hazards, i.e. hazard ratios, more
flexible. Argument se.fit is replaced by
ci.
dplyr reverse dependency
(see #101)make_newdataconcurrent now has a lag = 0 argument, can
be set to positive integer valuesas_ped accepts multiple concurrent
specials with different lag specificationsmake-newdata.fpedgg_laglead and
gg_partial_ll did not calculate the lag-lead-window
correctly when applied to ped datamake_newdata loses arguments expand and
n and gains ... where arbitrary covariate
specifications can be placed, i.e.
e.g. age=seq_range(age, n=20). Multiple such expression can
be provided and a data frame with one row for each combination of the
evaluated expressions will be returned. All variables not specified in
will be set to respective mean or modus values. For data of class
ped or fped make_newdata will try
to specify time-dependent variables intelligently.
te_var argument in concurrent and
cumulative was renamed to tz_var
te arguments have been replaced by tz
(time points at which z was observed) in all functions to
avoid confusion with mgcv::te (e.g.,
gg_laglead)
Overall better support for cumulative effects
Added convenience functions for work with cumulative effects, namely
gg_partial andgg_sliceAdded helper functions to calculate and visualize Lag-lead windows
get_lagleadgg_lagleadAdded convenience geoms for piece-wise constant
hazards (see examples in ?geom_hazard, cumulative hazards
and survival probabilities (usually
aes(x=time, y = surv_prob), but data set doesn’t contain
extra row for time = 0), thus
geom_stephazard adds row (x=0, y = y[1]) to the data
before plottinggeom_hazard adds row (x = 0, y = 0) before plotting
(can also be used for cumulative hazard)geom_surv add row (x = 0, y = 1) before plottingAll data transformation is now handled using as_ped
(see data
transformation vignette)
Data transformation now handles
Added functionality to flexibly simulate data from PEXP including
cumulative effects, see ?sim_pexp
Added functionality to calculate Aalen-model style cumulative
coefficients, see ?cumulative_coefficient
Breaking change in split_data (as_ped
now main data trafo function):
max.end argumentmax_time argument to introduce administrative
censoring at max_time when no custom interval split points
are providedtidyeval adaptationstidyevalpamm package to pammtools due to
naming conflicts with PAMM package on CRAN
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