This package is considered a duplicate. The official version of this package is found at:https://kkholst.r-universe.dev/mets

Package: mets 1.3.4

Klaus K. Holst

mets: Analysis of Multivariate Event Times

Implementation of various statistical models for multivariate event history data <doi:10.1007/s10985-013-9244-x>. Including multivariate cumulative incidence models <doi:10.1002/sim.6016>, and bivariate random effects probit models (Liability models) <doi:10.1016/j.csda.2015.01.014>. Modern methods for survival analysis, including regression modelling (Cox, Fine-Gray, Ghosh-Lin, Binomial regression) with fast computation of influence functions.

Authors:Klaus K. Holst [aut, cre], Thomas Scheike [aut]

mets_1.3.4.tar.gz
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mets_1.3.4.tgz(r-4.4-emscripten)mets_1.3.4.tgz(r-4.3-emscripten)
mets.pdf |mets.html✨
mets/json (API)
NEWS

# Install 'mets' in R:

install.packages('mets', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kkholst/mets/issues

Pkgdown site:https://kkholst.github.io

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

Datasets:

TRACE - The TRACE study group of myocardial infarction
base1cumhaz - Rate of CRBSI for HPN patients of Copenhagen
base44cumhaz - Rate of Occlusion/Thrombosis complication for catheter of HPN patients of Copenhagen
base4cumhaz - Rate of Mechanical (hole/defect) complication for catheter of HPN patients of Copenhagen
bmt - The Bone Marrow Transplant Data
dermalridges - Dermal ridges data
dermalridgesMZ - Dermal ridges data
diabetes - The Diabetic Retinopathy Data
drcumhaz - Rate for leaving HPN program for patients of Copenhagen
ghaplos - Ghaplos haplo-types for subjects of haploX data
hapfreqs - Hapfreqs data set
haploX - HaploX covariates and response for haplo survival discrete survival
melanoma - The Melanoma Survival Data
mena - Menarche data set
migr - Migraine data
multcif - Multivariate Cumulative Incidence Function example data set
np - Np data set
prt - Prostate data set
sTRACE - The TRACE study group of myocardial infarction
tTRACE - The TRACE study group of myocardial infarction
ttpd - Ttpd discrete survival data on interval form
twinbmi - BMI data set
twinstut - Stutter data set

fortran openblas cpp

7.74 score 1 stars 38 packages 331 scripts 8.9k downloads 6 mentions 345 exports 19 dependencies

Last updated 11 months agofrom:3c6ae6420f. Checks:OK: 2. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Dec 13 2024
R-4.5-linux-x86_64	OK	Dec 13 2024

Exports:aalenfrailty aalenMets ace.family.design addCums alpha2kendall alpha2spear ascertained.pairs back2timereg basecumhaz basehazplot.phreg bicomprisk bicompriskData BinAugmentCifstrata binomial.twostage binomial.twostage.time binreg binregATE binregATEbin binregCasewise binregG binregt binregTSR biprobit biprobit.time biprobit.vector blocksample Bootcovariancerecurrence BootcovariancerecurrenceS BootmediatorSurv Bootphreg bplot bplotdFG bptwin bptwin.time casewise casewise.bin casewise.test cause.pchazard.sim CCbinomial.twostage cif cif.yearslost cifreg ClaytonOakes cluster.index coarse.clust coefmat concordanceCor concordanceTwinACE concordanceTwostage cor.cif corsim.prostate corsim.prostate.random count.history count.historyVar countID covarianceRecurrent covarianceRecurrentS covfr covfridstrata covfridstrataCov covIntH1dM1IntH2dM2 cpred cumContr cumODDS cumsum2strata cumsumidstratasum cumsumidstratasumCov cumsumstrata cumsumstratasum daggr daggregate Dbvn dby dby<-dby2 dby2<-dbyr dcor dcount dcut dcut<-ddrop ddrop<-deval deval2 dfactor dfactor<-dhead diffstrata dInterval divide.conquer divide.conquer.timereg dkeep dkeep<-dlag dlag<-dlev dlevel dlevels dlist dmean dmeansd dmvn dnames dnames<-dnumeric dnumeric<-doubleFGR dprint dquantile dreg drelev drelev<-drelevel drelevel<-drename drename<-dreshape drm drm<-drop.specials drop.strata dsample dscalar dsd dsort dsort<-dsort2 dspline dspline<-dstr dsubset dsum dsummary dtab dtable dtail dtrans dtrans<-dtransform dtransform<-dunique easy.binomial.twostage Effbinreg estimate EVaddGam eventpois EventSplit extendCums familycluster.index familyclusterWithProbands.index fast.approx fast.cluster fast.pattern fast.reshape FastCoxPLstrataR faster.reshape FG_AugmentCifstrata FGprediid folds force.same.cens glm_IPTW GLprediid gof gofG.phreg gofM.phreg gofZ.phreg Grandom.cif grouptable haplo.surv.discrete headstrata IC IIDbaseline.cifreg IIDbaseline.phreg ilap indexstrata indexstratarightR Interval interval.logitsurv.discrete invsubdist ipw ipw2 jumptimes kendall.ClaytonOakes.twin.ace kendall.normal.twin.ace km kumarsim kumarsimRCT lifecourse lifetable lin.approx LinSpline logitATE logitIPCW logitIPCWATE logitSurv loglikMVN make.pairwise.design matdoubleindex matplot.mets.twostage mdi mediatorSurv medweight mets.options mlogit mystrata mystrata2index nonparcuminc normalATE npc object.defined or.cif or2prob p11.binomial.twostage.RV pairRisk pbvn pcif phreg phreg_IPTW phreg_rct phreg.par phregR piecewise.data piecewise.twostage plack.cif plack.cif2 plotConfRegion plotConfRegionSE plotcr plotstrata plotSurvd pmvn pre.cifs pred.cif.boot predictCumhaz predictdFG predictGLM predictlogitSurvd predictmlogit predictPairPlack predictSurvd prob.exceed.recurrent prob.exceedBiRecurrent prob.exceedBiRecurrentStrata prob.exceedRecurrent prob.exceedRecurrentStrata procform procform3 procformdata random.cif randomDes rchaz rchazC rcrisk rcrisks readmargsurv readPhreg recmarg recreg recregIPCW recurrentMarginal recurrentMarginalAIPCW recurrentMarginalAIPCWdata recurrentMarginalIPCW resmean.phreg resmeanATE resmeanIPCW revcumsum revcumsum2strata revcumsum2stratafdN revcumsumidstratasum revcumsumidstratasumCov revcumsumstrata revcumsumstratasum rmst.phreg rmstATE rmstIPCW rmvn robust.basehaz.phreg robust.phreg rpch rr.cif scalecumhaz scoreMVN setup.cif showfitsim sim.base sim.cause.cox sim.cif sim.cifs sim.cifsRestrict sim.cox simAalenFrailty simbinClaytonOakes.family.ace simbinClaytonOakes.pairs simbinClaytonOakes.twin.ace simBinFam simBinFam2 simBinPlack simClaytonOakes simClaytonOakes.family.ace simClaytonOakes.twin.ace simClaytonOakesLam simClaytonOakesWei simCompete.simple simCompete.twin.ace simCox simFrailty.simple simlogitSurvd simMultistate simnordic simnordic.random simrchaz simRecurrent simRecurrentII simRecurrentTS simsubdist simSurvFam simTTP simul.cifs slope.process squareintHdM strataAugment strataC subdist summaryGLM summaryTimeobject sumstrata surv.boxarea survival.twostage survivalG tailstrata test.conc tetrachoric tie.breaker twin.clustertrunc twin.polygen.design twinlm twinlm.strata twinlm.time twinsim twostage twostageMLE twostageREC vecAllStrata

Dependencies:cli codetools digest future future.apply globals lattice lava listenv Matrix mvtnorm numDeriv parallelly progressr Rcpp RcppArmadillo SQUAREM survival timereg

A practical guide to Human Genetics with Lifetime Data

Klaus Holst & Thomas Scheike

Rendered fromtime-to-event-family-studies-arev.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2023-01-17
Started: 2021-09-06

Analysis of bivariate binomial data: Twin analysis

Klaus Holst & Thomas Scheike

Rendered frombinomial-twin.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2023-12-05
Started: 2020-08-27

Analysis of multivariate binomial data: family analysis

Klaus Holst & Thomas Scheike

Rendered frombinomial-family.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2023-12-05
Started: 2020-08-27

Analysis of multivariate survival data

Klaus Holst & Thomas Scheike

Rendered fromtwostage-survival.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2023-12-05
Started: 2020-08-27

G-Computation or standardization for the Cox, Fine-Gray and binomial regression models for survival data

Klaus Holst & Thomas Scheike

Rendered fromsurvival-ate.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2023-12-05
Started: 2023-01-17

Average treatment effect (ATE) for Competing risks and binary outcomes

Klaus Holst & Thomas Scheike

Rendered frombinreg-ate.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2023-12-05
Started: 2021-09-06

Average treatment effect (ATE) for Restricted mean survival and years lost of Competing risks

Klaus Holst & Thomas Scheike

Rendered fromrmst-ate.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2023-12-05
Started: 2023-01-17

Binomial Regression for Survival and Competing Risks Data

Klaus Holst & Thomas Scheike

Rendered frombinreg.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2023-12-05
Started: 2021-09-06

Cumulative Incidence Regression

Klaus Holst & Thomas Scheike

Rendered fromcifreg.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2023-01-17
Started: 2020-08-27

Discrete Interval Censored Survival Models

Klaus Holst & Thomas Scheike

Rendered frominterval-discrete-survival.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2023-12-05
Started: 2021-09-06

dUtility data-frame manipulations

Klaus Holst & Thomas Scheike

Rendered frombasic-dutils.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2021-09-06
Started: 2020-08-27

GEE cluster standard errors and predictions for glm objects

Klaus Holst & Thomas Scheike

Rendered fromglm-utility.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2023-12-05
Started: 2023-12-05

Haplotype Discrete Survival Models

Klaus Holst & Thomas Scheike

Rendered fromhaplo-discrete-ttp.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2022-09-05
Started: 2020-08-27

Marginal modelling of clustered survival data

Klaus Holst & Thomas Scheike

Rendered frommarginal-cox.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2023-01-17
Started: 2020-08-27

Mediation Analysis for survival data

Klaus Holst & Thomas Scheike

Rendered frommediation-survival.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2023-12-05
Started: 2022-09-05

Recurrent events

Klaus Holst & Thomas Scheike

Rendered fromrecurrent-events.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2024-02-17
Started: 2020-08-27

Twin models

Klaus Holst & Thomas Scheike

Rendered fromquantitative-twin.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2023-01-17
Started: 2020-08-27

Two-Stage Randomization for for Competing risks and Survival outcomes

Klaus Holst & Thomas Scheike

Rendered frombinreg-TRS.rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2023-12-05
Started: 2023-12-05

Citation

Readme and manuals

Help Manual

Help page	Topics
Analysis of Multivariate Events	mets-package
Aalen frailty model	aalenfrailty
Fast additive hazards model with robust standard errors	aalenMets
Convert to timereg object	back2timereg
rate of CRBSI for HPN patients of Copenhagen	base1cumhaz
rate of Occlusion/Thrombosis complication for catheter of HPN patients of Copenhagen	base44cumhaz
rate of Mechanical (hole/defect) complication for catheter of HPN patients of Copenhagen	base4cumhaz
Plotting the baslines of stratified Cox	basecumhaz basehazplot.phreg bplot plotConfRegion plotConfRegionSE plotstrata
Estimation of concordance in bivariate competing risks data	bicomprisk bicompriskData
Augmentation for Binomial regression based on stratified NPMLE Cif (Aalen-Johansen)	BinAugmentCifstrata
Fits Clayton-Oakes or bivariate Plackett (OR) models for binary data using marginals that are on logistic form. If clusters contain more than two times, the algoritm uses a compososite likelihood based on all pairwise bivariate models.	binomial.twostage binomial.twostage.time
Binomial Regression for censored competing risks data	binreg binregt logitIPCW
Average Treatment effect for censored competing risks data using Binomial Regression	binregATE binregATEbin kumarsim kumarsimRCT logitATE logitIPCWATE normalATE
Estimates the casewise concordance based on Concordance and marginal estimate using binreg	binregCasewise
G-estimator for binomial regression model (Standardized estimates)	binregG
2 Stage Randomization for Survival Data or competing Risks Data	binregTSR
Bivariate Probit model	biprobit biprobit.time biprobit.vector
Block sampling	blocksample dsample
The Bone Marrow Transplant Data	bmt
Wild bootstrap for Cox PH regression	Bootphreg pred.cif.boot
Liability model for twin data	bptwin bptwin.time twinlm.time
Estimates the casewise concordance based on Concordance and marginal estimate using prodlim but no testing	casewise
Estimates the casewise concordance based on Concordance and marginal estimate using timereg and performs test for independence	casewise.bin casewise.test slope.process
Cumulative incidence with robust standard errors	cif
CIF regression	cifreg diffstrata FGprediid IIDbaseline.cifreg indexstratarightR vecAllStrata
Clayton-Oakes model with piece-wise constant hazards	ClaytonOakes
Finds subjects related to same cluster	cluster.index countID mystrata mystrata2index pairRisk
Concordance Computes concordance and casewise concordance	concordance.cor concordanceCor
Cross-odds-ratio, OR or RR risk regression for competing risks	cor.cif or.cif rr.cif
Counts the number of previous events of two types for recurrent events processes	count.history count.historyVar
Estimation of covariance for bivariate recurrent events with terminal event	Bootcovariancerecurrence BootcovariancerecurrenceS covarianceRecurrent covarianceRecurrentS plot.covariace.recurrent
aggregating for for data frames	daggr daggregate
Derivatives of the bivariate normal cumulative distribution function	Dbvn
Calculate summary statistics grouped by	dby dby2 dby2<- dby<- dbyr
summary, tables, and correlations for data frames	dcor dcount deval deval2 dmean dmeansd dquantile dscalar dsd dstr dsubset dsum dsummary
Cutting, sorting, rm (removing), rename for data frames	dcut dcut<- ddrop ddrop<- dkeep dkeep<- dnames dnames<- drename drename<- drm drm<- dunique
Dermal ridges data (families)	dermalridges
Dermal ridges data (monozygotic twins)	dermalridgesMZ
The Diabetic Retinopathy Data	diabetes
Split a data set and run function	divide.conquer
Split a data set and run function from timereg and aggregate	divide.conquer.timereg
Lag operator	dlag dlag<-
Double CIF Fine-Gray model with two causes	bplotdFG doubleFGR predictdFG
list, head, print, tail	dhead dlist dprint dtail
Rate for leaving HPN program for patients of Copenhagen	drcumhaz
Regression for data frames with dutility call	dreg
relev levels for data frames	dfactor dfactor<- dlev dlev<- dlevel dlevel<- dlevels dnumeric dnumeric<- drelev drelev<- drelevel drelevel<-
Sort data frame	dsort dsort2 dsort<-
Simple linear spline	dspline dspline<-
tables for data frames	dtab dtable
Transform that allows condition	dtrans dtrans<- dtransform dtransform<-
Fits two-stage binomial for describing depdendence in binomial data using marginals that are on logistic form using the binomial.twostage funcion, but call is different and easier and the data manipulation is build into the function. Useful in particular for family design data.	easy.binomial.twostage
Efficient IPCW for binary data	Effbinreg
Relative risk for additive gamma model	EVaddGam
Extract survival estimates from lifetable analysis	eventpois pcif
Event split with two time-scales, time and gaptime	EventSplit
Finds all pairs within a cluster (family)	familycluster.index
Finds all pairs within a cluster (famly) with the proband (case/control)	familyclusterWithProbands.index
Fast approximation	cpred fast.approx indexstrata predictCumhaz
Fast pattern	fast.pattern
Fast reshape	dreshape fast.reshape
Augmentation for Fine-Gray model based on stratified NPMLE Cif (Aalen-Johansen)	drop.strata FG_AugmentCifstrata setup.cif simul.cifs strataC
ghaplos haplo-types for subjects of haploX data	ghaplos
IPTW GLM, Inverse Probaibilty of Treatment Weighted GLM	glm_IPTW
GOF for Cox PH regression	gof.phreg
Stratified baseline graphical GOF test for Cox covariates in PH regression	gofG.phreg
GOF for Cox covariates in PH regression	gofM.phreg
GOF for Cox covariates in PH regression	cumContr gofZ.phreg
Additive Random effects model for competing risks data for polygenetic modelling	Grandom.cif
hapfreqs data set	hapfreqs
Discrete time to event haplo type analysis	haplo.surv.discrete plotSurvd predictSurvd simTTP
haploX covariates and response for haplo survival discrete survival	haploX
Discrete time to event interval censored data	cumODDS dInterval Interval interval.logitsurv.discrete predictlogitSurvd simlogitSurvd
Inverse Probability of Censoring Weights	ipw
Inverse Probability of Censoring Weights	ipw2
Kaplan-Meier with robust standard errors	km
Life-course plot	lifecourse
Life table	lifetable lifetable.formula lifetable.matrix
Simple linear spline	LinSpline
Proportional odds survival model	logitSurv
Mediation analysis in survival context	BootmediatorSurv mediatorSurv
Computes mediation weights	medweight
The Melanoma Survival Data	melanoma
Menarche data set	mena
Set global options for 'mets'	mets.options
Migraine data	migr
Multinomial regression based on phreg regression	mlogit predictmlogit
Multivariate Cumulative Incidence Function example data set	multcif
np data set	np
For internal use	ace.family.design alpha2kendall alpha2spear ascertained.pairs CCbinomial.twostage coarse.clust coefmat concordanceTwinACE concordanceTwostage corsim.prostate corsim.prostate.random drop.specials fast.cluster faster.reshape folds force.same.cens grouptable ilap jumptimes kendall.ClaytonOakes.twin.ace kendall.normal.twin.ace make.pairwise.design make.pairwise.design.competing matplot.mets.twostage nonparcuminc npc object.defined p11.binomial.twostage.RV piecewise.data piecewise.twostage plotcr predictPairPlack procform procform3 procformdata sim simbinClaytonOakes.family.ace simbinClaytonOakes.pairs simbinClaytonOakes.twin.ace simBinFam simBinFam2 simBinPlack simClaytonOakes.family.ace simClaytonOakes.twin.ace simCompete.simple simCompete.twin.ace simCox simFrailty.simple simnordic simnordic.random simSurvFam surv.boxarea twin.polygen.design
Fast Cox PH regression	IIDbaseline.phreg phreg phreg.par readPhreg robust.phreg
IPTW Cox, Inverse Probaibilty of Treatment Weighted Cox regression	phreg_IPTW
Lu-Tsiatis More Efficient Log-Rank for Randomized studies with baseline covariates	phreg_rct
Fast Cox PH regression and calculations done in R to make play and adjustments easy	FastCoxPLstrataR phregR
plack Computes concordance for or.cif based model, that is Plackett random effects model	plack.cif plack.cif2
Multivariate normal distribution function	dmvn loglikMVN pbvn pmvn rmvn scoreMVN
Predictions from proportional hazards model	covfr covfridstrata covfridstrataCov cumsum2strata cumsumidstratasum cumsumidstratasumCov cumsumstrata cumsumstratasum headstrata matdoubleindex mdi predict.phreg revcumsum revcumsum2strata revcumsum2stratafdN revcumsumidstratasum revcumsumidstratasumCov revcumsumstrata revcumsumstratasum robust.basehaz.phreg sumstrata tailstrata
prints Concordance test	print.casewise
Estimation of probability of more that k events for recurrent events process	prob.exceed.recurrent prob.exceedBiRecurrent prob.exceedBiRecurrentStrata prob.exceedRecurrent prob.exceedRecurrentStrata summaryTimeobject
Prostate data set	prt
Random effects model for competing risks data	random.cif
Simulation of Piecewise constant hazard model (Cox).	addCums lin.approx rchaz simrchaz
Piecewise constant hazard distribution	rchazC
Simulation of Piecewise constant hazard models with two causes (Cox).	cause.pchazard.sim rcrisk rcrisks
Recurrent events regression with terminal event	GLprediid recreg recregIPCW scalecumhaz strataAugment twostageREC
Fast recurrent marginal mean when death is possible	recmarg recurrentMarginal recurrentMarginalAIPCW recurrentMarginalAIPCWdata recurrentMarginalIPCW tie.breaker
Restricted mean for stratified Kaplan-Meier or Cox model with martingale standard errors	cif.yearslost resmean.phreg rmst.phreg
Average Treatment effect for Restricted Mean for censored competing risks data using IPCW	resmeanATE rmstATE
Restricted IPCW mean for censored survival data	resmeanIPCW rmstIPCW
Piecewise constant hazard distribution	ppch rpch
Simulation of cause specific from Cox models.	sim.cause.cox
Simulation of output from Cumulative incidence regression model	invsubdist pre.cifs sim.cif sim.cifs sim.cifsRestrict simsubdist subdist
Simulation of output from Cox model.	read.fit sim.base sim.cox simulate.cox
Simulate from the Aalen Frailty model	simAalenFrailty
Simulate from the Clayton-Oakes frailty model	simClaytonOakes simClaytonOakesLam
Simulate from the Clayton-Oakes frailty model	simClaytonOakesWei
Simulation of illness-death model	extendCums simMultistate
Simulation of recurrent events data based on cumulative hazards II	covIntH1dM1IntH2dM2 showfitsim simRecurrent simRecurrentII squareintHdM
Simulation of recurrent events data based on cumulative hazards: Two-stage model	simRecurrentTS
Summary for dependence models for competing risks	summary.cor
Reporting OR (exp(coef)) from glm with binomial link and glm predictions	predictGLM summaryGLM
Twostage survival model for multivariate survival data	randomDes readmargsurv survival.twostage twostage.aalen twostage.cox.aalen twostage.coxph twostage.phreg
G-estimator for Cox and Fine-Gray model	survivalG
Concordance test Compares two concordance estimates	test.conc
Estimate parameters from odds-ratio	or2prob tetrachoric
The TRACE study group of myocardial infarction	sTRACE TRACE tTRACE
ttpd discrete survival data on interval form	ttpd
Estimation of twostage model with cluster truncation in bivariate situation	twin.clustertrunc
BMI data set	twinbmi
Classic twin model for quantitative traits	twinlm twinlm.strata
Simulate twin data	twinsim
Stutter data set	twinstut
Twostage survival model fitted by pseudo MLE	twostageMLE

Package: mets 1.3.4

mets: Analysis of Multivariate Event Times

A practical guide to Human Genetics with Lifetime Data

Analysis of bivariate binomial data: Twin analysis

Analysis of multivariate binomial data: family analysis

Analysis of multivariate survival data

G-Computation or standardization for the Cox, Fine-Gray and binomial regression models for survival data

Average treatment effect (ATE) for Competing risks and binary outcomes

Average treatment effect (ATE) for Restricted mean survival and years lost of Competing risks

Binomial Regression for Survival and Competing Risks Data

Cumulative Incidence Regression

Discrete Interval Censored Survival Models

dUtility data-frame manipulations

GEE cluster standard errors and predictions for glm objects

Haplotype Discrete Survival Models

Marginal modelling of clustered survival data

Mediation Analysis for survival data

Recurrent events

Twin models

Two-Stage Randomization for for Competing risks and Survival outcomes

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)