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intsurv vs labelled

A side-by-side editorial comparison of intsurv and labelled — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

intsurv vs labelled: at a glance

Featureintsurvlabelled
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themessurvival-analysis, cure-models, censored-data, regularizationsurvey-data, data-labels, stata-spss, metadata
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is intsurv?

A Cox cure-rate model package woke up after four years to simplify its own interface.

intsurv fits Cox cure rate models for right-censored survival data where event status may be uncertain — the case where you cannot tell whether a subject experienced the event or was never susceptible to it. The core has been stable since 2019: cox_cure() and its regularized counterpart cox_cure_net(), plus a weighted concordance index and a data simulator. After more than four years without a release, version 0.3.0 arrived in September 2025 and restructured how those two functions are configured rather than adding capability.

Read the full intsurv trajectory →

What is labelled?

The bridge between Stata/SPSS labelled data and tidy R keeps widening, one integration at a time.

labelled manages variable labels, value labels and user-defined missing values on data imported from Stata, SPSS and SAS, filling the gap between those formats' metadata and R's native types. Recent releases have pushed outward from the core label accessors: survey design objects from the survey package are now supported throughout, look_for() results can be rendered as formatted gt tables, and dictionary data frames convert in both directions. Error messaging moved wholesale to cli in 2.14.0.

Read the full labelled trajectory →

intsurv vs labelled: editorial side-by-side

I
intsurv
ANALYTICS
0.0

A Cox cure-rate model package woke up after four years to simplify its own interface.

◆ Current state

intsurv fits Cox cure rate models for right-censored survival data where event status may be uncertain — the case where you cannot tell whether a subject experienced the event or was never susceptible to it. The core has been stable since 2019: cox_cure() and its regularized counterpart cox_cure_net(), plus a weighted concordance index and a data simulator. After more than four years without a release, version 0.3.0 arrived in September 2025 and restructured how those two functions are configured rather than adding capability.

◆ Where it's heading

The package has reached the point where the methods are settled and the remaining work is ergonomics. Moving control parameters, M-step settings and penalty specification into cox_cure.control(), cox_cure.mstep() and cox_cure_net.penalty() follows the established R convention of separating tuning from the model formula, and it arrives long after the arguments accumulated. The C++ headers were placed in inst/include as early as 2019 so other packages could link against them, which suggests the implementation was always intended to be reused.

◆ Prediction

The gap between 0.2.2 and 0.3.0 makes cadence a poor basis for prediction. What the entries do support is that the interface rework is unfinished business rather than a prelude to new methods, so consolidation around the new helper functions is the likelier next step.

L
labelled
ANALYTICS
0.0

The bridge between Stata/SPSS labelled data and tidy R keeps widening, one integration at a time.

◆ Current state

labelled manages variable labels, value labels and user-defined missing values on data imported from Stata, SPSS and SAS, filling the gap between those formats' metadata and R's native types. Recent releases have pushed outward from the core label accessors: survey design objects from the survey package are now supported throughout, look_for() results can be rendered as formatted gt tables, and dictionary data frames convert in both directions. Error messaging moved wholesale to cli in 2.14.0.

◆ Where it's heading

The arc is toward being usable wherever labelled data ends up, not just where it is loaded. Each recent release either extends support to another object type — survey designs, packed columns, plain vectors, tibbles with list columns — or adds a conversion path between labels and some other representation. The look_for() search function has become a second centre of gravity alongside the label accessors, accumulating its own output formats and long-format conversions.

◆ Prediction

The pattern of adding compatibility with one more object type or output format per release is stable and likely continues. Nothing in these entries indicates a change to the underlying haven_labelled representation the package is built on.

Alternatives to intsurv and labelled

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either intsurv or labelled.

See all intsurv alternatives → · See all labelled alternatives →

Recent activity from intsurv and labelled

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 9mo agolabelledFormatted look_for() tables and two-way dictionary conversion
  2. 10mo agointsurvModel configuration moves into dedicated control functions
  3. 11mo agolabelledSurvey design objects supported across the package
  4. 1y agolabelledRegression in set_variable_labels() corrected
  5. 1y agolabelledcli adopted for all messaging; null_action gains options
  6. 2y agolabelledCustom functions can rewrite variable and value labels in bulk
  7. 3y agolabelledPacked columns supported and label attributes exposed directly
  8. 5y agointsurvCross-validated model selection and offset terms added
  9. 6y agointsurvC++ headers relocated so other packages can link them
  10. 7y agointsurvCox cure models for uncertain event status arrive
  11. 7y agointsurvParameter initialization methods added to the alpha
  12. 7y agointsurvAlpha cut for paper submission and simulation reproducibility

Frequently asked questions

What is the difference between intsurv and labelled?

Both compete on the same themes — r-package — within Analytics. intsurv and labelled are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is intsurv better than labelled?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. intsurv and labelled are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to intsurv?

Top intsurv alternatives in Analytics are ranked by recent ship velocity. Browse the "intsurv alternatives" section above for the current picks, or visit /alternatives/intsurv for the full list with editorial commentary on each.

What are the best alternatives to labelled?

Top labelled alternatives in Analytics are ranked by recent ship velocity. Browse the "labelled alternatives" section above for the current picks, or visit /alternatives/labelled for the full list with editorial commentary on each.