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Comparison · Analytics
OneSampleMR vs spmodel
A side-by-side editorial comparison of OneSampleMR and spmodel — release velocity, themes, recent moves, and the top alternatives to consider.
OneSampleMR vs spmodel: at a glance
What is OneSampleMR?
OneSampleMR found that argument order in a formula was silently changing its estimates
OneSampleMR implements one-sample Mendelian randomization estimators — two-stage predictor substitution, two-stage residual inclusion, and Sanderson-Windmeijer conditional F statistics for instrument strength. The package spent its first years on packaging and dependency upkeep. The 2026 releases turn to substance: broader support for models fitted elsewhere, then a correctness fix for a defect that depended on nothing more than where covariates appeared in a formula.
What is spmodel?
Spatial regression in R, adding block kriging and then tuning the numerics underneath it
spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.
OneSampleMR vs spmodel: editorial side-by-side
OneSampleMR
0.0ANALYTICS
OneSampleMR found that argument order in a formula was silently changing its estimates
◆ Current state
OneSampleMR implements one-sample Mendelian randomization estimators — two-stage predictor substitution, two-stage residual inclusion, and Sanderson-Windmeijer conditional F statistics for instrument strength. The package spent its first years on packaging and dependency upkeep. The 2026 releases turn to substance: broader support for models fitted elsewhere, then a correctness fix for a defect that depended on nothing more than where covariates appeared in a formula.
◆ Where it's heading
Two threads. The first is reach — fsw() now reads models fitted by AER::ivreg(), estimatr::iv_robust() and fixest::feols() in addition to ivreg::ivreg(), which makes conditional F statistics available without refitting in the package's own idiom. The second is hardening: clear errors when more than one exposure is given or when a variable collides with the reserved name y, and print methods that no longer fail on user-specified t0 with log or logit links. Both come largely from user reports rather than a plan.
◆ Prediction
The estimator-support work has been adding one IV-fitting package at a time on outside contributions, so further backends are the likeliest next content — the package's own estimators have been stable since first release.
spmodel
0.0ANALYTICS
Spatial regression in R, adding block kriging and then tuning the numerics underneath it
◆ Current state
spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.
◆ Where it's heading
Two threads run in parallel. The first is expanding what can be predicted — point predictions, then areal averages over a region via block kriging, then better accuracy and efficiency for that path as the block size default moved from 1000 to 4000 in 0.12.0. The second is numerical trustworthiness, and it is unusually prominent here: a range-constraint option for stability in 0.9.0, a corrected log determinant of the fixed effects in the restricted log likelihood in 0.11.0, a cloud semivariogram that had been doubling the semivariance fixed in 0.11.1, and now a tighter optimiser tolerance. Several of these silently changed results before they were caught.
◆ Prediction
Expect the maintainers to keep publishing explicit reproduction instructions alongside numerical default changes, as 0.13.0 does by documenting the `control = list(reltol = 1e-4)` escape hatch. The entries give no signal of expansion beyond the current model families.
Alternatives to OneSampleMR and spmodel
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 OneSampleMR or spmodel.
fastplyr
A fast dplyr stand-in that keeps finding new places to skip work entirely.
trias
Belgium's invasive-species indicator toolkit is in steady refinement, one plotting edge case at a time.
icesSAG
The ICES stock assessment client took upload away in 2024 and spent two years giving it back.
dggridR
A discrete global grid generator grew cell traversal and became a usable spatial index.
vegan
Community ecology's standard toolkit is retiring the functions a generation of scripts was built on.
See all OneSampleMR alternatives → · See all spmodel alternatives →
Recent activity from OneSampleMR and spmodel
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoOneSampleMROneSampleMR fixes estimates broken by covariate order in the formula
- 2mo agospmodelTighter optimiser tolerance to avoid local maxima
- 5mo agoOneSampleMROneSampleMR computes conditional F for three more IV packages
- 6mo agospmodelEmpirical autocovariance function and better block kriging accuracy
- 9mo agospmodelCloud semivariogram doubling fixed; geometry warnings added
- 1y agospmodelBlock kriging for areal averages and their uncertainty ⚡
- 1y agoOneSampleMROneSampleMR 0.1.6
- 1y agospmodelRobust semivariogram and new covariance types for areal models
- 1y agospmodelRange constraint option and redefined covariance type names
- 2y agoOneSampleMROneSampleMR 0.1.5
- 2y agoOneSampleMROneSampleMR 0.1.4
- 3y agoOneSampleMROneSampleMR 0.1.3
Frequently asked questions
What is the difference between OneSampleMR and spmodel?
They serve adjacent needs but don't currently overlap on shipped themes. OneSampleMR and spmodel 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 OneSampleMR better than spmodel?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. OneSampleMR and spmodel 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 OneSampleMR?
Top OneSampleMR alternatives in Analytics are ranked by recent ship velocity. Browse the "OneSampleMR alternatives" section above for the current picks, or visit /alternatives/onesamplemr for the full list with editorial commentary on each.
What are the best alternatives to spmodel?
Top spmodel alternatives in Analytics are ranked by recent ship velocity. Browse the "spmodel alternatives" section above for the current picks, or visit /alternatives/spmodel for the full list with editorial commentary on each.