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Changelog

Source: NEWS.md

pmxhelpr 0.7.0

This release fixes bugs in previously released functions. df_mrgsim_addpred() returned a stochastic PRED whenever extra arguments were passed through ..., which also affected prediction-corrected VPCs built on it. plot_dvtime() and plot_gof() imputed every BLQ row at the first row’s LLOQ when loq = NULL and LLOQ varied. Dose-proportionality tdist intervals and the bundled pkmodel are also corrected. See Bug fixes below.

Bug fixes

  • df_mrgsim_addpred() passes ... to mrgsolve::mrgsim_df() as documented. It previously passed them to mrgsolve::zero_re(), so any extra argument left the random effects in and PRED was stochastic. A carry_out in ... is merged with output_var, and arguments that change the number of rows (e.g. obsonly) now abort.
  • plot_dvtime() and plot_gof() with loq = NULL impute each row at its own LLOQ value. Previously the first row’s LLOQ was applied to every row (and a leading NA disabled imputation and broke the LLOQ line). With several LLOQs, the LLOQ line is drawn at the highest.
  • df_doseprop() / plot_doseprop() with method = "tdist" use the regression’s residual degrees of freedom (n - 2) instead of n - 1, matching confint(). Intervals widen slightly, noticeably only for small n.
  • df_doseprop() / plot_doseprop() judge dose proportionality on unrounded confidence bounds, so bounds within rounding distance of 1 are no longer misclassified as “Dose-proportional”.
  • The bundled pkmodel (model_mread_load("pkmodel")) computed intercompartmental clearance from the clearance typical value (Q = TVCL * ...); it now uses TVQ. Simulations from pkmodel change, and data_sad, data_sad_nca, and data_sad_pkfit are regenerated with the corrected model.
  • df_doseprop() PowerCI labels pad to sigdigits significant digits (e.g. Power: 1.00 (90% CI 0.900-1.20)) and no longer use scientific notation.
  • df_doseprop() / plot_doseprop() called without metrics abort with a message saying metrics is required, instead of a misleading error about missing doseprop_stats columns.
  • print() and summary() of a vpc_stats object no longer drop the config: line when strat_var or loq is NULL; it shows NULL.
  • The plot_dvconc() caption no longer drops the fit description when the se_* flag of a fit that is not drawn is TRUE (e.g. linear = TRUE, loess = FALSE, se_loess = TRUE).

New features

Forest plots

  • plot_forest() draws a forest plot of test/reference comparisons for one exposure metric, faceted by covariate, with an Estimate (CI) text column on the right.

    Key features:

    • Reference line (ref) and optional band (ref_band, ref_band_type of "multiplicative", "additive", or "absolute").
    • Accepts raw draws or a precomputed forest_stats container, so a summary can be re-plotted without re-aggregating.
    • ref_layout draws the reference row in a reference panel ("consolidated") or in each covariate panel ("distributed", which needs cov_level_ref in df_forest()), from one forest_stats container.
    • Returns a plain ggplot object.

  • df_forest() summarizes replicate draws into medians and ci percentile intervals with formatted labels, in plot order. cov_level_ref also draws the reference row inside each covariate panel under its own label (e.g. Fasted, 70 kg).

  • df_forest_preprocess() reshapes wide replicate simulation output (one row per scenario per replicate) into the long draws df_forest() consumes, inferring each scenario’s covariate from its difference to the reference (cov_val_ref) and optionally adding test/reference ratios (ratio).

  • plot_build_forest() renders any forest_stats container, including manually built ones from external pipelines.

  • style_forest() is the ggstylekit style preset for plot_forest(); colors keyed by covariate name, or a palette function(n), color each covariate panel; errorbar_width (in row heights) draws capped error bars instead of uncapped interval lines.

  • style_forest_pmforest(), style_forest_coveffectsplot(), style_forest_pmxforest(), and style_forest_pumas() approximate the default looks of pmforest, coveffectsplot::forest_plot(), PMXForest::forestPlot(), and Pumas’ table_forest_plot().

  • is_forest_stats() tests for a forest_stats object.

New arguments

  • plot_dvtime() and plot_dvconc() gain show_obs to omit the observed point layer. Unlike alphas = c(obs_point = 0), hidden points no longer affect the axis limits.
  • plot_vpc_shown() gains loq_line (default TRUE); FALSE hides the LLOQ reference line on standard VPCs, including one inherited from an LLOQ column, and its plot_vpc_legend() entry.
  • plot_vpc_legend(), plot_dvtime(), and plot_gof() gain show_loq_value. Set show_loq_value = FALSE to label the LLOQ linetype as a single "LLOQ" legend entry without its value.

New datasets

  • data_sad_pkforest_sim: example raw replicate simulation output (500 bootstrap replicates of steady-state CMAX, CMIN, AUC, CAVG under six covariate scenarios).
  • data_sad_pkforest: data_sad_pkforest_sim processed by df_forest_preprocess(), ready for df_forest() / plot_forest().

Breaking changes

Removed arguments

  • df_mrgsim_replicate() no longer has a parallel argument; replicates always run sequentially under seed. Passing parallel aborts with a message. future.apply is no longer a suggested dependency.

Changed behavior

  • pmxhelpr now requires ggstylekit >= 0.4.1 (was 0.4.0), which adds the caption style field used by the style_*() presets.
  • plot_vpc_legend()’s lloq argument is renamed loq, matching every other function. lloq still works for now with a deprecation warning. ci and pi are validated as in df_vpcstats(), so ci = 90 aborts instead of labeling a “9000% CI”.
  • df_mrgsim_replicate() aborts with a clear message when pred_var is not "PRED", which previously failed with an internal column-selection error.
  • plot_dvtime() and plot_gof() message when loq is given with loq_method = 0, where it has no effect.
  • Character col_var labels in plot_dvconc(), plot_dvtime(), and plot_gof() now order by a number anywhere in the label (e.g. "Dose 5 mg" before "Dose 10 mg"), not only a leading one. Label sets with any number-free value keep first-appearance order; factors are unaffected.
  • min_bin_count in plot_vpc_cont(), plot_vpc_cens(), and plot_build_vpc() now defaults to 0 (was 1), so no bins are filtered by default. Prediction-corrected simulated quantiles (pc_sim_*) are NA in bins with no quantifiable observations, so pcVPCs do not draw them.
  • plot_dvtime(), plot_dvconc(), plot_gof(), plot_vpc_cont(), plot_vpc_cens(), plot_build_vpc(), plot_doseprop(), and plot_build_doseprop() abort when a logical argument (e.g. log_y, show_caption, pcvpc, show_rep, se) is not TRUE or FALSE, instead of silently treating it as FALSE or failing later with an unclear error.

pmxhelpr 0.6.0

Plot styling is now powered by the ggstylekit package, replacing the bespoke pmx_* element/theme system introduced in 0.5.0.

New features

Breaking changes

Removed functions

  • The pmx_* element constructors are removed: pmx_point(), pmx_line(), pmx_ribbon(), pmx_errorbar(), pmx_trend(), pmx_style(), and pmx_color().
  • The theme factories are removed: plot_dvtime_theme(), plot_dvconc_theme(), plot_gof_theme(), plot_doseprop_theme(), and plot_vpc_theme(). Use the corresponding style_*() preset instead.
  • The theme class system is removed: pmx_theme(), is_pmx_element(), is_pmx_theme(), and the + / print methods for pmx_element and pmx_theme.

Renamed and changed arguments

Migration

Replace theme = plot_<fn>_theme(<role> = pmx_*(<field> = <value>)) with style = style_<fn>(<map> = c(<role> = <value>)), where <map> is the ggstylekit per-series map for that aesthetic (colors, fill, shapes, sizes, linetypes, linewidths, alphas):

# before (0.5.x)
plot_dvtime(data, theme = plot_dvtime_theme(obs_point = pmx_point(alpha = 0)))

# after (0.6.0)
plot_dvtime(data, style = style_dvtime(alphas = c(obs_point = 0)))

See the Plot Styling and Aesthetics vignette for the role vocabulary; call any style_*() preset with no arguments to view its defaults.

pmxhelpr 0.5.1

  • Bug fix in plot_dvtime() which was masking reference line, legend, and caption layers when character aliases where passed to argument loq_method in place of numeric values.

pmxhelpr 0.5.0

This release simplifies plotting function interfaces, harmonizes naming across the package, replaces the flat theme list with a system of theme and element constructor, and introduces class-tagged stats containers (vpc_stats, doseprop_stats) that can be tabulated and re-plotted with recomputation.

The VPC pipeline is rewritten without the vpc package dependency with comprehensive BLQ handling for standard and prediction- corrected VPCs of the continuous data range and and a new function for VPC plots of the proportion of data BLQ over time.

Breaking changes

Removed functions

  • plot_dvtime_dual() is removed — compose PK and PD panels with plot_dvtime() + patchwork::wrap_plots().
  • df_addn() is removed — replaced by var_addn().
  • df_pcdv() is removed — replaced by var_predcorr().
  • df_nobsbin() is removed — bin counting is now integrated into df_vpcstats().
  • mod_loglog() and df_loglog() are removed — log-log regression is performed inside df_doseprop().
  • dvconc_caption() and dvtime_caption() are no longer exported.

Renamed functions

Removed and renamed arguments

  • df_doseprop() and plot_doseprop(): metric_var is renamed to metric_name_var, and exp_var is renamed to metric_value_var, to make the role of each column explicit (i.e., exposure metric label variable vs exposure metric value variable).
  • df_mrgsim_replicate(): the named-vector arguments num_vars and char_vars are removed; pass extra simulation columns through ... to mrgsolve::mrgsim_df() via carry_out (numeric) and recover (any type but useful for character / factor).
  • plot_dvconc(), plot_dvtime(), and plot_gof(): the cfb (logical) / cfb_base (numeric) argument pair is replaced by a single numeric ref argument (NULL = no line). For example, cfb = TRUE, cfb_base = 0 becomes ref = 0.
  • plot_gof(): output_colors is removed — overlay colors for DV, PRED, and IPRED are now set via pmx_color() in plot_gof_theme().
  • plot_vpc_legend(): update is renamed to theme, aligning with the theme-argument convention used by the other plot functions.
  • All plot functions: x_breaks, x_scale, x_lab, and y_lab are removed — add the equivalent ggplot2 layers to the returned plot object.

Behavior changes

  • The VPC pipeline is rewritten without the vpc package dependency. df_vpcstats() summary column names follow a <role>_<low|med|hi> scheme — simulated quantiles are sim_low_*, sim_med_*, sim_hi_*; observed quantiles are obs_low/med/hi; per-bin counts are obs_n and obs_n_blq (previously nbin / nobsblq); BLQ proportions (std-VPC only) are sim_prop_blq_*. The min_bin_count filter now gates on quantifiable observations (obs_n - obs_n_blq) for VPCs and total observations (obs_n) for cens-VPCs. Comprehensive BLQ handling includes censoring of observed quantiles without censoring simulated data in VPCs and censoring both observed and simulated data at LLOQ before quantile aggregation in pcVPCs.
  • plot_vpc_legend(ci) default changes from c(0.05, 0.95) (vector) to 0.90 (scalar). lloq now accepts a vector and renders one legend entry per unique value.
  • vpc is removed from Imports (VPC pipeline no longer depends on it).
  • patchwork moves from Imports to Suggests — install explicitly if you compose multi-panel layouts (e.g. the legend + VPC pattern in the README).
  • var_addn() now derives factor levels from the order of first appearance in grp_var, so a pre-sorted input like c(10, 200, 1000) yields levels in numeric order rather than the alphabetic order returned by factor(). Removes the need to follow up with forcats::fct_relevel() for numeric dose / time groupings.
  • plot_build_vpc(loq = …) supplied explicitly always wins over compute_out$config$loq and draws one global reference line per unique value. Per-facet (strat_var × LLOQ) dispatch is reserved for the inherited case.

New features

New functions

  • plot_vpc_cont() generates a 1-step (plot vpc_stats) or 2-step (calculate and plot) VPC of the continuous portion of the data range, wrapping both df_vpcstats and plot_build_vpc().
  • plot_vpc_cens() generates a 1-step (plot vpc_stats) or 2-step (calculate and plot) VPC of the censored portion of the data range, wrapping both df_vpcstats and plot_build_vpc().
  • df_vpcstats() computes VPC summary statistics from raw replicate simulation output and returns a vpc_stats / pmx_stats container. Always emits both standard and prediction-corrected statistics so the same object supports toggling pcvpc when plotting.
  • plot_build_vpc() renders a VPC ggplot from any vpc_stats container. Use directly when working from a manually-constructed or cached vpc_stats object; most users still go through plot_vpc_cont() and/or plot_vpc_cens.
  • plot_build_doseprop() renders a dose-proportionality ggplot from any doseprop_stats container; most users still go through plot_doseprop().
  • plot_doseprop_theme() is a theme factory for plot_doseprop() with keys obs_point and linear.
  • plot_gof_shown() and plot_vpc_shown() are constructors for GOF and VPC layer-visibility settings.
  • var_addn() generates factor labels with unique-value counts, replacing df_addn().
  • var_dosenorm() performs dose normalization.
  • var_predcorr() performs prediction correction, replacing df_pcdv().

New arguments

  • df_mrgsim_replicate(parallel = FALSE) — when TRUE, replicate simulations run via future.apply::future_lapply() using the active future plan, with per-replicate L’Ecuyer-CMRG RNG streams so output stays reproducible under a fixed seed. Adds future.apply to Suggests.
  • df_vpcstats() and plot_vpc_cont() gain mode = c("auto", "rank", "drop") controlling how BLQ-encoded values flow into quantile aggregation. "auto" (default) resolves to "rank" for std VPC and "drop" for pcVPC.
  • df_vpcstats() and plot_vpc_cont() accept per-row LLOQ (multi-cohort / mid-study assay-update datasets): each observation is censored against its own row’s LLOQ, and stratified plots draw one reference line per (strat × LLOQ) combination. Unique non-NA values are exposed via config$loq.
  • plot_dvtime() and plot_gof(): loq_method accepts the character aliases "none", "postdose", and "all" in addition to the existing numeric values 0, 1, 2. The legacy numeric form continues to work.
  • plot_dvtime() emits a message when loq is inherited from the LLOQ column of data, mirroring plot_vpc_cont(). Pass loq explicitly to suppress.
  • plot_gof(blq_mode = c("obs", "all")) scopes BLQ imputation to the observed DV layer (default) or to observed and model-predicted layers.
  • Time, prediction, and simulated-DV columns across functions are now scalar NSE-friendly arguments (time_var, ntime_var, pred_var, ipred_var, sim_dv_var) instead of named lists (time_vars, output_vars). Pass arguments as bare names or strings.
  • plot_vpc_legend(type = c("cont", "cens")) selects the label set and layer set the legend describes — "cens" relabels the central-tendency entries to "Obs Prop BLQ", "Sim Prop BLQ", and "Sim <ci>% CI Prop BLQ" and suppresses all prediction-interval entries, matching the plot_vpc_cens() plot.

Dual-mode pipelines (replot without recompute)

  • plot_doseprop() accepts the doseprop_stats container returned by df_doseprop() directly. Pass a precomputed result to skip the regression refit and re-plot with different theme or se settings. Pipeline arguments (metrics, metric_name_var, metric_value_var, dose_var, method, ci, sigdigits) cannot be honored on the precomputed path and error with a clear message.
  • plot_vpc_cont() accepts the vpc_stats container returned by df_vpcstats() directly. Pass a precomputed result to re-plot with different min_bin_count, shown, theme, or pcvpc settings without re-summarizing. Pipeline arguments (strat_var, loq, mode, pi, ci, column-name args) cannot be honored on the precomputed path and error with a clear message.

Theme system

  • New pmx_theme() factory and pmx_*() element constructors — pmx_point(), pmx_line(), pmx_ribbon(), pmx_errorbar(), and pmx_trend() — replace the previous flat list of role- and geometry-based theme elements.
  • Theme factory keys follow a layer_element convention (e.g. obs_point, cent_errorbar, ref_line, loq_line). VPC keys follow an element_statistic convention aligned with the shown argument (e.g. obs_median_line, sim_pi_ci).
  • New pmx_color() constructor sets overlay colors for DV, PRED, and IPRED in plot_gof_theme() — e.g. plot_gof_theme(cent_color = pmx_color(pred = "purple")).
  • New pmx_style() convenience constructor applies shared aesthetics (color, alpha) to both point and line elements of a role — e.g. plot_dvtime_theme(obs = pmx_style(alpha = 0.3)).
  • +.pmx_theme() and +.pmx_element() methods compose partial themes; pmx_style() shortcuts are applied first and explicit element-level overrides win.

S3 classes and predicates

  • pmx_stats is a shared container with vpc_stats and doseprop_stats subclasses — slots $stats, $obs, $config — returned by df_vpcstats() and df_doseprop().
  • print(), summary(), and as.data.frame() methods on pmx_stats give a focused REPL view (dimensions, slot row counts, run-config keys) and a plain data.frame view of $stats. Subclasses override print() / summary() for richer output (column groups for VPC; one-line-per-metric PowerCI + interpretation for doseprop).
  • print() methods on pmx_theme and pmx_element objects render a banner + per-field listing instead of the default class-attribute dump.
  • pmx_vpc_plot is a ggplot subclass that warns when facet_*() layers are added externally, pointing users to the strat_var argument instead.
  • Predicates is_doseprop_stats(), is_pmx_element(), is_pmx_stats(), is_pmx_theme(), is_pmx_vpc_plot(), and is_vpc_stats() are exported. With strict = TRUE, the stats and theme predicates run the corresponding structural validator.

Vignettes and documentation

  • New Getting Started vignette ships with the package for new-user onboarding.
  • New Dose-Proportionality Workflow vignette covers df_doseprop() → plot_build_doseprop() → plot_doseprop(), the doseprop_stats / pmx_stats class system, and the precomputed-stats path.
  • The VPC, GOF, exploratory PK / PK-PD, and plot-themes vignettes are restructured into focused articles with cross-links.
  • The Plot Themes and Aesthetics article covers inspecting pmx_element / pmx_theme objects and composing partial themes with +.
  • The Visual Predictive Check Workflow article covers df_vpcstats(), plot_vpc_cens(), the pipeline column contracts (df_mrgsim_replicate() → df_vpcstats() → plot_build_vpc()), and inspection of vpc_stats objects.
  • Narrative vignettes are hosted on the pkgdown site (https://ryancrass.github.io/pmxhelpr/articles/); the installed package no longer ships built vignettes in inst/doc/, keeping the install footprint small.

Minor improvements and bug fixes

  • All exported functions that take column-name arguments accept bare names or strings via a shared NSE-resolution helper.
  • Plot functions warn when the input dataset has more than one unique compartment after the EVID == 0 filter, avoiding silently plotting observations from an unintended compartment.
  • df_mrgsim_replicate() errors when the user-supplied carry_out / recover values overlap the wrapped baseline columns, instead of silently shadowing them.
  • Line-geom aesthetics use linewidth instead of the deprecated size throughout.
  • df_vpcstats(pcvpc = TRUE) now drops MDV == 1 records from simulated data when loq = NULL and the input dataset has no LLOQ column, mirroring the observed-data path. Previous behavior caused minor quantile drift on bins with NA observations.
  • Test coverage expanded from ~100 to 800+ tests.

pmxhelpr 0.4.0

  • Rename data_sad_pd as data_sad. No longer export data_sad_pd.
  • Rename model as pkmodel for consistency with pdmodel.
  • Rename pmxhelpr_vpc_theme to plot_vpc_theme for consistency with other plot theme functions
  • Change dvconc_caption and dvtime_caption to internal functions after simplifying
  • Added cfb_base argument to plot_gof (was hardcoded as yintercept = 0)
  • Add helpers for central tendency handing, time variable handling, BLQ imputation, and error bar width setting to remove repetition in function calls
  • Expand test coverage and refactor existing tests to reduce redundancy
  • Fix bugs and typos globally in package

pmxhelpr 0.3.9

  • Add NSE support to accept bare column names in all exported functions (e.g., dv_var = DV) in addition to strings (e.g., dv_var = “DV”) across all exported functions that take column name arguments. Revise vignettes to highlight this functionality.
  • Fix bug in plot_vpclegend that was resulting in alpha not being correctly applied

pmxhelpr 0.3.8

  • Fix bug in plot_dvtime to ensure closed circles are plotted in place of open circles for central tendency points
  • Add minimum R version of 4.4.1 given use of native pipe operator (|>)

pmxhelpr 0.3.7

  • Add plot_dvconc to generate plots of response variables versus drug concentration with LOESS and/or linear trendlines
  • Add plot_dvtime_dual wrapper function for plot_dvtime to plot two dependent variables versus time intended to support simultaneous visualization of PK and PD.
  • Update var_addn (formerly df_addn) to offload factor ordering from the function to simply output. Handling can be done outside the function with alternative packages optimized for dealing with factor variables (e.g., forcats)
  • Update plot_gof_theme to include separate line theme elements for individual observed lines (e.g., spaghetti plots) and central tendency of the observed.
  • Revise the Exploratory Data Analysis vignette to include new functionality and revised workflows with new functions.
  • Fix bug that was not scaling error bar caps for the x-axis range when cent = "median_iqr" across functions

pmxhelpr 0.3.6

  • Add var_addn (formerly df_addn) helper function to create and order factor labels including count of unique values to include counts in plot legends
  • Add plot_gof_theme function to set and adjust default aesthetics for plot_gof
  • Add LLOQ value and linetype to legend in plot_dvtime
  • Add caption indicating method of BLQ imputation to plot_dvtime
  • Fix bug in df_pcdv that was including missing values (MDV=1) in the median PRED calculation for nominal times with missing values, resulting in incorrect PRED-correction of observations in these bins ONLY. Simulated intervals and observed quantile lines were unaffected.
  • Correct error in documentation of default number of breaks in breaks_time

pmxhelpr 0.3.5

  • Add option to pass the same dataset variable to time_var and ntime_var for all functions
  • Add option to control default aesthetics (linewidth, linetype, size, shape, alpha) in plot_dvtime and plot_gof
  • Fix bug in plot_gof that was preventing upper error bars from inheriting the color mapped to “DV”

pmxhelpr 0.3.4

  • Fix bug in df_mrgsim_replicate that was precluding use of non-default time variable names

pmxhelpr 0.3.3

  • Fix bug in plot_dvtime and plot_gof where variable for “DOSE” was being assessed when dosenorm = FALSE
  • Update breaks_time to accept abbreviations for time units

pmxhelpr 0.3.2

  • Add cent = "mean_sdl_upper" option to plot_dvtime and plot_gof for plotting only the upper error bar
  • Add barwidth argument to plot_dvtime and plot_gof to allow user to change error bar cap width.

pmxhelpr 0.3.1

  • Add plot_gof to generate population overlay goodness-of-fit plots
  • Add data_sad_pkfit NONMEM PK model fit output dataset for data_sad based on model.
  • Fixed bug in plot_dvtime that was leading to plotting mean +/- 2*SD instead of mean +/- SD

pmxhelpr 0.3.0

  • Added new functionality for dose-proportionality assessment with df_doseprop and plot_doseprop, including helpers mod_loglog and df_loglog to perform and tabulate power law (log-log) regression of exposure versus dose

  • Added new internal package dataset data_sad_nca for use with dose-proportionality assessment functions

  • Added helper function dvtime_caption to generate the caption for plot_dvtime

  • Added helper function pmxhelpr_vpc_theme to capture default VPC plot aesthetics `

  • Revised vignettes to describe workflow with new default aesthetics

  • Remove use of log_y argument in VPC plot examples and added rationale to primary vignette for plot_vpc_exactbins

  • Add unit tests for all primary functions

pmxhelpr 0.2.4

  • Fix bug in plot_dvtime to ensure median + IQR error bars prints on both linear and log-scale axes when cent = "median_iqr"

pmxhelpr 0.2.3

  • Added cent = "median_iqr" option to plot_dvtime to plot median with inter-quartile range error bars
  • Updated the ind_dv logical argument in plot_dvtime to grp_dv to generalize use of grouping beyond connecting points within an individual subject
  • Added the grp_var argument to plot_dvtime to allow specification of the variable assigned to the group aesthetic by the user. Default is grp_var = "ID"

pmxhelpr 0.2.2

  • Corrected bug in plot_vpc_exactbins when ordered factor variables are pasted to the strat_var argument. Ordered factors cannot be passed to the underlying stratification function from the vpc package (add_stratification()); therefore, ordered factors will be coerced to unordered factors within plot_vpc_exactbins

pmxhelpr 0.2.1

  • Corrected bug in NA handling within breaks_time

pmxhelpr 0.2.0

  • Added plot_dvtime function for exploratory concentration-time plotting

  • Added breaks_time function to automatically determine x-axis breaks for time

  • Functionality from breaks_time added to plot_vpcexactbins

  • Exploratory Data Analysis vignette created to demonstrate functionality of new functions

  • Added dependency: labelling

pmxhelpr 0.1.4

  • Fixed bug leading to error when generating stratified vpcs using the strat_var argument

pmxhelpr 0.1.3

  • Vignette vpc plot axes updated to time unit breaks
  • Vignette bullet point lists updated to correct spacing
  • Coerce argument lloq argument of plot_legend() to character type

pmxhelpr 0.1.2

  • Vignettes copy edited

pmxhelpr 0.1.1

  • Added dependency: patchwork

pmxhelpr 0.1.0

  • Full VPC workflow now available in Version 0.1.0 with three vignettes to demonstrate this functionality!

  • VPC Plot Aesthetics vignette demonstrating options for modifying plot aesthetics, creating a plot legend using plot_legend(), and adding the VPC plot and legend objects together into a single object using the patchwork package

pmxhelpr 0.0.3

  • Additional functionality for plot_vpc_exactbins

    • shown argument added to facilitate customization of which layers are shown in the plot and standardize with new function plot_legend. Passed to show argument of vpc::vpc()

  • plot_legend helper function to generate a legend for a VPC plot generated using plot_vpc_exactbins(), which can be combined with the VPC plot using the patchwork package

  • VPC Plots with BLQ Censoring vignette demonstrating appropriate handling of data missing due to assay sensitivity (below the lower limit of quantification) using plot_vpc_exactbins() and workflow leveraging df_mrgsim_replicate.

pmxhelpr 0.0.2

  • Additional functionality for plot_vpc_exactbins
    • loq argument added to facilitate incorporating BLQ censoring of observed data in summary quantiles
  • Bug fix to allow passing argument vpcdb = TRUE to vpc::vpc()

pmxhelpr 0.0.1

  • data_sad NONMEM and mrgsolve analysis-ready dataset for a hypothetical SAD study with assessment of food effect.

  • model mrgsolve model file (class mrgmod) in the internal pmxhelpr model library .

  • model_load function to load internal models from the pmxhelpr model library.

  • df_mrgsim_replicate mrgsim wrapper function to run a simulation that replicates the input dataset multiple times, intended for application to generating Visual Predictive Check (VPC) simulation-based model diagnostics.

  • plot_vpc_exactbins vpc wrapper function to using an exact time binning variable in the input dataset (e.g. nominal time) with plotting of observed data points using actual time.

  • VPC Plots with Exact Bins vignette demonstrating use case for plot_vpc_exactbins() and workflow leveraging df_mrgsim_replicate.