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E=''0j9΀2M`M|<>DzwƧ/@Q9"D˘O>g=UBj7lhŚj@-zZH?u-Obsx 4#U -A(8k\l31f@늢nչ4qe-'!j\vc.;-!Յd[NWki1MBLXЪb;j}cսG{$MwR=#e!`d; 6va{mzsy7Bd7s: "7s!ŞCS_tX6 S<1B7  ~[),lIzeH`z#e Bg.8d-ft|[#׺QE/qh#M]tɓEFM/Vmw> =]§s9(.J$7ȶáI5k6~^Xs(~Cn_4Ea|uz10H\H2}^gY,Uuf=Ҥ)b/&Su^.- Wd[ʅGِm!-a;Hl[0\k7hrFw]t!X8,sA5zQ\ZfY/ n[I.h:\wE[&l۰[Vf[^ML whwld,ܻ3-S~lC>Yƛ XTw.f=xzZB{\0P4lx$пiE;xRˆ`CקUl7:' `7 ! F $i2 }f/Bx2BFbMxc`.4,! og24͔mۈsvb:A 3paI7W>: 'v[s!^|(/\d.ܮ>T9\82+!wH6e(σΐ Ll ox.,f;/iā.d(nCPd =QyYˬ@&f-< gEc.ģ[MM6,y=I OuJjX/   )U&l ˲W)EK{ M u|ԅzhs+^i\x{a7d0o&(@IIHR ѿ?₷(.XQ"tj?h̅Wd2>%@[iR,(t5a+0df-ϻsM,ų.!C#1˖.ze.4^hjz?[p:%/KMsurv/NAMESPACE0000644000176200001440000000016412057137504012725 0ustar liggesusers# Export all names exportPattern(".") # Import all packages listed as Imports or Depends # import( # survival # ) KMsurv/man/0000755000176200001440000000000012057137654012266 5ustar liggesusersKMsurv/man/lung.Rd0000644000176200001440000000125411360341665013517 0ustar liggesusers\name{lung} \alias{lung} \non_function{} \title{data from Exercise 4.4, p120} \description{ The \code{lung} data frame has 25 rows and 4 columns. } \format{ This data frame contains the following columns: \describe{ \item{time}{ Days to death } \item{death}{ Death indicator (1=dead), complete follow-up on all patients } \item{time2}{ Days to 3/31/80 or death (interim analysis) } \item{death2}{ Death indicator as of 3/31/80 (1=dead, 0=alive) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. } \examples{ data(lung) } \keyword{datasets} KMsurv/man/bcdeter.Rd0000644000176200001440000000124011360341223014143 0ustar liggesusers\name{bcdeter} \alias{bcdeter} \non_function{} \title{data from Section 1.18} \description{ The \code{bcdeter} data frame has 92 rows and 3 columns. } \format{ This data frame contains the following columns: \describe{ \item{lower}{ Lower limit of interval, months } \item{upper}{ Upper limit of interval, months } \item{treat}{ Treatment regimen (1=radiotherapy only, 2=radiotherapy + chemotherapy) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. Beadle et al Cancer 54 (1984):2911-2918. } \examples{ data(bcdeter) } \keyword{datasets} KMsurv/man/drug6mp.Rd0000644000176200001440000000146411360341427014135 0ustar liggesusers\name{drug6mp} \alias{drug6mp} \non_function{} \title{data from Section 1.2} \description{ The \code{drug6mp} data frame has 21 rows and 5 columns. } \format{ This data frame contains the following columns: \describe{ \item{pair}{ pair number } \item{remstat}{ Remission status at randomization (1=partial, 2=complete) } \item{t1}{ Time to relapse for placebo patients, months } \item{t2}{ Time to relapse for 6-MP patients, months } \item{relapse}{ Relapse indicator (0=censored, 1=relapse) for 6-MP patients } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. Freireich et al. (1963) \emph{Blood} 21: 699-716. } \examples{ data(drug6mp) } \keyword{datasets} KMsurv/man/aids.Rd0000644000176200001440000000117111360341110013451 0ustar liggesusers\name{aids} \alias{aids} \non_function{} \title{data from Section 1.19} \description{ The \code{aids} data frame has 295 rows and 3 columns. } \format{ This data frame contains the following columns: \describe{ \item{infect}{ Infection time for AIDS, years } \item{induct}{ Induction time for AIDS, years } \item{adult}{ Indicator of adult (1=adult, 0=child) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. Lagakos et al. Biometrika 68 (1981): 515-523. } \examples{ data(aids) } \keyword{datasets} KMsurv/man/burn.Rd0000644000176200001440000000320011360341332013500 0ustar liggesusers\name{burn} \alias{burn} \non_function{} \title{data from Section 1.6} \description{ The \code{burn} data frame has 154 rows and 17 columns. } \format{ This data frame contains the following columns: \describe{ \item{Obs}{ Observation number } \item{Z1}{ Treatment: 0-routine bathing 1-Body cleansing } \item{Z2}{ Gender (0=male 1=female) } \item{Z3}{ Race: 0=nonwhite 1=white } \item{Z4}{ Percentage of total surface area burned } \item{Z5}{ Burn site indicator: head 1=yes, 0=no } \item{Z6}{ Burn site indicator: buttock 1=yes, 0=no } \item{Z7}{ Burn site indicator: trunk 1=yes, 0=no } \item{Z8}{ Burn site indicator: upper leg 1=yes, 0=no } \item{Z9}{ Burn site indicator: lower leg 1=yes, 0=no } \item{Z10}{ Burn site indicator: respiratory tract 1=yes, 0=no } \item{Z11}{ Type of burn: 1=chemical, 2=scald, 3=electric, 4=flame } \item{T1}{ Time to excision or on study time } \item{D1}{ Excision indicator: 1=yes 0=no } \item{T2}{ Time to prophylactic antibiotic treatment or on study time } \item{D2}{ Prophylactic antibiotic treatment: 1=yes 0=no } \item{T3}{ Time to straphylocous aureaus infection or on study time } \item{D3}{ Straphylocous aureaus infection: 1=yes 0=no } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. Ichida et al. Stat. Med. 12 (1993): 301-310. } \examples{ data(burn) } \keyword{datasets} KMsurv/man/larynx.Rd0000644000176200001440000000143611360341614014063 0ustar liggesusers\name{larynx} \alias{larynx} \non_function{} \title{data from Section 1.8} \description{ The \code{larynx} data frame has 90 rows and 5 columns. } \format{ This data frame contains the following columns: \describe{ \item{stage}{ Stage of disease (1=stage 1, 2=stage2, 3=stage 3, 4=stage 4) } \item{time}{ Time to death or on-study time, months } \item{age}{ Age at diagnosis of larynx cancer } \item{diagyr}{ Year of diagnosis of larynx cancer } \item{delta}{ Death indicator (0=alive, 1=dead) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. Kardaun Stat. Nederlandica 37 (1983), 103-126. } \examples{ data(larynx) } \keyword{datasets} KMsurv/man/channing.Rd0000644000176200001440000000147711360341407014340 0ustar liggesusers\name{channing} \alias{channing} \non_function{} \title{data from Section 1.16} \description{ The \code{channing} data frame has 462 rows and 6 columns. } \format{ This data frame contains the following columns: \describe{ \item{obs}{ Observation number } \item{death}{ Death status (1=dead, 0=alive) } \item{ageentry}{ Age of entry into retirement home, months } \item{age}{ Age of death or left retirement home, months } \item{time}{ Difference between the above two ages, months } \item{gender}{ Gender (1=male, 2=female) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. Hyde Biometrika (1977), 225-230. } \examples{ data(channing) } \keyword{datasets} KMsurv/man/bmt.Rd0000644000176200001440000000403411360341262013324 0ustar liggesusers\name{bmt} \alias{bmt} \non_function{} \title{data from Section 1.3} \description{ The \code{bmt} data frame has 137 rows and 22 columns. } \format{ This data frame contains the following columns: \describe{ \item{group}{ Disease Group 1-ALL, 2-AML Low Risk, 3-AML High Risk } \item{t1}{ Time To Death Or On Study Time } \item{t2}{ Disease Free Survival Time (Time To Relapse, Death Or End Of Study) } \item{d1}{ Death Indicator 1-Dead 0-Alive } \item{d2}{ Relapse Indicator 1-Relapsed, 0-Disease Free } \item{d3}{ Disease Free Survival Indicator 1-Dead Or Relapsed, 0-Alive Disease Free) } \item{ta}{ Time To Acute Graft-Versus-Host Disease } \item{da}{ Acute GVHD Indicator 1-Developed Acute GVHD 0-Never Developed Acute GVHD) } \item{tc}{ Time To Chronic Graft-Versus-Host Disease } \item{dc}{ Chronic GVHD Indicator 1-Developed Chronic GVHD 0-Never Developed Chronic GVHD } \item{tp}{ Time To Chronic Graft-Versus-Host Disease } \item{dp}{ Platelet Recovery Indicator 1-Platelets Returned To Normal, 0-Platelets Never Returned to Normal } \item{z1}{ Patient Age In Years } \item{z2}{ Donor Age In Years } \item{z3}{ Patient Sex: 1-Male, 0-Female } \item{z4}{ Donor Sex: 1-Male, 0-Female } \item{z5}{ Patient CMV Status: 1-CMV Positive, 0-CMV Negative } \item{z6}{ Donor CMV Status: 1-CMV Positive, 0-CMV Negative } \item{z7}{ Waiting Time to Transplant In Days } \item{z8}{ FAB: 1-FAB Grade 4 Or 5 and AML, 0-Otherwise } \item{z9}{ Hospital: 1-The Ohio State University, 2-Alferd , 3-St. Vincent, 4-Hahnemann } \item{z10}{ MTX Used as a Graft-Versus-Host- Prophylactic: 1-Yes 0-No } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. } \examples{ data(bmt) } \keyword{datasets} KMsurv/man/alloauto.Rd0000644000176200001440000000130411360342057014362 0ustar liggesusers\name{alloauto} \alias{alloauto} \non_function{} \title{data from Section 1.9} \description{ The \code{alloauto} data frame has 90 rows and 5 columns. } \format{ This data frame contains the following columns: \describe{ \item{time}{ Time to death or relapse, months } \item{type}{ Type of transplant (1=allogeneic, 2=autologous) } \item{delta}{ Leukemia-free survival indicator (0=alive without relapse, 1=dead or relapse) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. Kardaun Stat. Nederlandica 37 (1983), 103-126. } \examples{ data(alloauto) } \keyword{datasets} KMsurv/man/psych.Rd0000644000176200001440000000122511360341700013664 0ustar liggesusers\name{psych} \alias{psych} \non_function{} \title{data from Section 1.15} \description{ The \code{psych} data frame has 927 rows and 10 columns. } \format{ This data frame contains the following columns: \describe{ \item{sex}{ Patient sex (1=male, 2=female) } \item{age}{ Patient age } \item{time}{ Time to death or on-study time } \item{death}{ Death indicator (0=alive, 1=dead) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. Woolsen Biometrics 37 (1981): 687-696. } \examples{ data(psych) } \keyword{datasets} KMsurv/man/hodg.Rd0000644000176200001440000000152711360341475013475 0ustar liggesusers\name{hodg} \alias{hodg} \non_function{} \title{data from Section 1.10} \description{ The \code{hodg} data frame has 43 rows and 6 columns. } \format{ This data frame contains the following columns: \describe{ \item{gtype}{ Graft type (1=allogenic, 2=autologous) } \item{dtype}{ Disease type (1=Non Hodgkin lymphoma, 2=Hodgkins disease) } \item{time}{ Time to death or relapse, days } \item{delta}{ Death/relapse indicator (0=alive, 1=dead) } \item{score}{ Karnofsky score } \item{wtime}{ Waiting time to transplant in months } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. Avalos et al. Bone Marrow Transplantation 13(1993):133-138. } \examples{ data(hodg) } \keyword{datasets} KMsurv/man/tongue.Rd0000644000176200001440000000123611360341771014051 0ustar liggesusers\name{tongue} \alias{tongue} \non_function{} \title{data from Section 1.11} \description{ The \code{tongue} data frame has 80 rows and 3 columns. } \format{ This data frame contains the following columns: \describe{ \item{type}{ Tumor DNA profile (1=Aneuploid Tumor, 2=Diploid Tumor) } \item{time}{ Time to death or on-study time, weeks } \item{delta}{ Death indicator (0=alive, 1=dead) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. Sickle-Santanello et al. Cytometry 9 (1988): 594-599. } \examples{ data(tongue) } \keyword{datasets} KMsurv/man/std.Rd0000644000176200001440000000354711360342001013334 0ustar liggesusers\name{std} \alias{std} \non_function{} \title{data from Section 1.12} \description{ The \code{std} data frame has 877 rows and 3 columns. } \format{ This data frame contains the following columns: \describe{ \item{obs}{ Observation number } \item{race}{ Race (W=white, B=black) } \item{marital}{ Marital status (D=divorced / separated, M=married, S=single) } \item{age}{ AGE } \item{yschool}{ Years of schooling } \item{iinfct}{ Initial infection (1= gonorrhea, 2=chlamydia, 3=both) } \item{npartner}{ Number of partners } \item{os12m}{ Oral sex within 12 months (1=yes, 0=no) } \item{os30d}{ Oral sex within 30 days (1=yes, 0=no) } \item{rs12m}{ Rectal sex within 12 months (1=yes, 0=no) } \item{rs30d}{ Rectal sex within 30 days (1=yes, 0=no) } \item{abdpain}{ Presence of abdominal pain (1=yes, 0=no) } \item{discharge}{ Sign of discharge (1=yes, 0=no) } \item{dysuria}{ Sign of dysuria (1=yes, 0=no) } \item{condom}{ Condom use (1=always, 2=sometime, 3=never) } \item{itch}{ Sign of itch (1=yes, 0=no) } \item{lesion}{ Sign of lesion (1=yes, 0=no) } \item{rash}{ Sign of rash (1=yes, 0=no) } \item{lymph}{ Sign of lymph (1=yes, 0=no) } \item{vagina}{ Involvement vagina at exam (1=yes, 0=no) } \item{dchexam}{ Discharge at exam (1=yes, 0=no) } \item{abnode}{ Abnormal node at exam (1=yes, 0=no) } \item{rinfct}{ Reinfection (1=yes, 0=no) } \item{time}{ Time to reinfection } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. } \examples{ data(std) } \keyword{datasets} KMsurv/man/drughiv.Rd0000644000176200001440000000131411360341447014215 0ustar liggesusers\name{drughiv} \alias{drughiv} \non_function{} \title{data from Exercise 7.6, p222} \description{ The \code{drughiv} data frame has 34 rows and 3 columns. } \format{ This data frame contains the following columns: \describe{ \item{drug}{ Drug combination (1=AZT + zalcitabine, 2=AZT + zalcitabine + saquinavir) } \item{time}{ Time after drug administration to CD4 count at a specified level, days } \item{delta}{ Indicator of CD4 count reaching specified level (1=yes, 0=no) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. } \examples{ data(drughiv) } \keyword{datasets} KMsurv/man/allograft.Rd0000644000176200001440000000130411360341162014511 0ustar liggesusers\name{allograft} \alias{allograft} \non_function{} \title{data from Exercise 13.1, p418} \description{ The \code{allograft} data frame has 34 rows and 4 columns. } \format{ This data frame contains the following columns: \describe{ \item{patient}{ Patient } \item{time}{ Time to graft rejection, days } \item{rejection}{ Indicator of graft rejection (1=yes, 0=no) } \item{match}{ Good HLA skin match (1=yes, 0=no) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. Batchelor and Hackett Lancet 2 (1970): 581-583. } \examples{ data(allograft) } \keyword{datasets} KMsurv/man/rats.Rd0000644000176200001440000000120311360342040013501 0ustar liggesusers\name{rats} \alias{rats} \non_function{} \title{data from Exercise 7.13, p225} \description{ The \code{rats} data frame has 50 rows and 4 columns. } \format{ This data frame contains the following columns: \describe{ \item{time}{ Time to tumor development } \item{tumor}{ Indicator of tumor development (1=yes, 0=no) } \item{trt}{ Treatment (1=treated with drug, 0=given placebo) } \item{litter}{ Litter } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. } \examples{ data(rats) } \keyword{datasets} KMsurv/man/bnct.Rd0000644000176200001440000000113611360341276013475 0ustar liggesusers\name{bnct} \alias{bnct} \non_function{} \title{data from Exercise 7.7, p223} \description{ The \code{bnct} data frame has 34 rows and 3 columns. } \format{ This data frame contains the following columns: \describe{ \item{trt}{ Treatment (1=untreated, 2=radiated, 3=radiated + BPA) } \item{time}{ Death time or on-study time, days } \item{death}{ Death indicator (1=dead, 0=alive) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. } \examples{ data(bnct) } \keyword{datasets} KMsurv/man/stddiag.Rd0000644000176200001440000000104411360341747014167 0ustar liggesusers\name{stddiag} \alias{stddiag} \non_function{} \title{data from Exercise 5.6, p146} \description{ The \code{stddiag} data frame has 25 rows and 2 columns. } \format{ This data frame contains the following columns: \describe{ \item{encounter}{ Months from 1/93 to encounter } \item{diagnosed}{ Months until STD diagnosed in the clinic } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. } \examples{ data(stddiag) } \keyword{datasets} KMsurv/man/azt.Rd0000644000176200001440000000120111360341175013334 0ustar liggesusers\name{azt} \alias{azt} \non_function{} \title{data from Exercise 4.7, p122} \description{ The \code{azt} data frame has 45 rows and 4 columns. } \format{ This data frame contains the following columns: \describe{ \item{patient}{ Patient number } \item{ageentry}{ Age at entry into AZT study, months } \item{age}{ Age at death or censoring time, months } \item{death}{ Death indicator (1=dead, 0=alive) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. } \examples{ data(azt) } \keyword{datasets} KMsurv/man/pneumon.Rd0000644000176200001440000000311611360341654014230 0ustar liggesusers\name{pneumon} \alias{pneumon} \non_function{} \title{data from Section 1.13} \description{ The \code{pneumon} data frame has 3470 rows and 15 columns. } \format{ This data frame contains the following columns: \describe{ \item{chldage}{ Age child had pneumonia, months } \item{hospital}{ Indicator for hospitalization for pneumonia (1=yes, 0=no) } \item{mthage}{ Age of the mother, years } \item{urban}{ Urban environment for mother (1=yes, 0=no) } \item{alcohol}{ Alcohol use by mother during pregnancy (1=yes, 0=no) } \item{smoke}{ Cigarette use by mother during pregnancy (1=yes, 0=no) } \item{region}{ Region of the coutry (1=northeast, 2=north central, 3=south, 4=west) } \item{poverty}{ Mother at poverty level (1=yes, 0=no) } \item{bweight}{ Normal birthweight (>5.5 lbs.) (1=yes, 0=no) } \item{race}{ Race of the mother (1=white, 2=black, 3=other) } \item{education}{ Education of the mother, years of school } \item{nsibs}{ Number of siblings of the child } \item{wmonth}{ Month the child was weaned } \item{sfmonth}{ Month the child on solid food } \item{agepn}{ Age child in the hospital for pneumonia, months } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. \emph{National Longitudinal Survey of Youth Handbook} The Ohio State University, 1995. } \examples{ data(pneumon) } \keyword{datasets} KMsurv/man/btrial.Rd0000644000176200001440000000123011360341311014005 0ustar liggesusers\name{btrial} \alias{btrial} \non_function{} \title{data from Section 1.5} \description{ The \code{btrial} data frame has 45 rows and 3 columns. } \format{ This data frame contains the following columns: \describe{ \item{time}{ Time to death or on-study time, months } \item{death}{ Death indicator (0=alive, 1=dead) } \item{im}{ Immunohistochemical response (1=negative, 2=positive) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. Sedmak el al. Modern Pathology 2 (1989): 516-520. } \examples{ data(btrial) } \keyword{datasets} KMsurv/man/twins.Rd0000644000176200001440000000124611360342013013703 0ustar liggesusers\name{twins} \alias{twins} \non_function{} \title{data from Exercise 7.14, p225} \description{ The \code{twins} data frame has 24 rows and 3 columns. } \format{ This data frame contains the following columns: \describe{ \item{id}{ Twin number } \item{age}{ Age of twin's death from CHD, months } \item{death}{ Death (male twin) from CHD indicator (1=dead from CHD, 0=alive or other cause of death) } \item{gender}{ 1=male, 2=female } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. } \examples{ data(twins) } \keyword{datasets} KMsurv/man/kidrecurr.Rd0000644000176200001440000000177111360341552014543 0ustar liggesusers\name{kidrecurr} \alias{kidrecurr} \docType{data} \title{Data on 38 individuals using a kidney dialysis machine} \description{ Data on 38 individuals using a kidney dialysis machine See Problem 13.5.2 } \usage{data(kidrecurr)} \format{ A data frame with 38 observations on the following 10 variables. \describe{ \item{patient}{Patient number} \item{time1}{Time one of recurrence of infection, days} \item{infect1}{Indicator infection one (1=yes, 0=no)} \item{time2}{Time two of recurrence of infection, days} \item{infect2}{Indicator infection two (1=yes, 0=no)} \item{age}{Patient's age} \item{gender}{Patient's gender} \item{gn}{Disease type GN (1=yes, 0=no)} \item{an}{Disease type AN (1=yes, 0=no)} \item{pkd}{Disease type PKD (1=yes, 0=no)} } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. McGilchrist and Aisbett 47 (1991):461-466. } \examples{ data(kidrecurr) } \keyword{datasets} KMsurv/man/bfeed.Rd0000644000176200001440000000225511360341242013610 0ustar liggesusers\name{bfeed} \alias{bfeed} \non_function{} \title{data from Section 1.14} \description{ The \code{bfeed} data frame has 927 rows and 10 columns. } \format{ This data frame contains the following columns: \describe{ \item{duration}{ Duration of breast feeding, weeks } \item{delta}{ Indicator of completed breast feeding (1=yes, 0=no) } \item{race}{ Race of mother (1=white, 2=black, 3=other) } \item{poverty}{ Mother in poverty (1=yes, 0=no) } \item{smoke}{ Mother smoked at birth of child (1=yes, 0=no) } \item{alcohol}{ Mother used alcohol at birth of child (1=yes, 0=no) } \item{agemth}{ Age of mother at birth of child } \item{ybirth}{ Year of birth } \item{yschool}{ Education level of mother (years of school) } \item{pc3mth}{ Prenatal care after 3rd month (1=yes, 0=no) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. \emph{National Longitudinal Survey of Youth Handbook} The Ohio State University, 1995. } \examples{ data(bfeed) } \keyword{datasets} KMsurv/man/kidtran.Rd0000644000176200001440000000130511360341524014175 0ustar liggesusers\name{kidtran} \alias{kidtran} \non_function{} \title{data from Section 1.7} \description{ The \code{kidtran} data frame has 863 rows and 6 columns. } \format{ This data frame contains the following columns: \describe{ \item{obs}{ Observation number } \item{time}{ Time to death or on-study time } \item{delta}{ Death indicator (0=alive, 1=dead) } \item{gender}{ 1=male, 2=female } \item{race}{ 1=white, 2=black } \item{age}{ Age in years } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. } \examples{ data(kidtran) } \keyword{datasets} KMsurv/man/baboon.Rd0000644000176200001440000000113511360341210013772 0ustar liggesusers\name{baboon} \alias{baboon} \non_function{} \title{data from Exercise 5.8, p147} \description{ The \code{baboon} data frame has 25 rows and 2 columns. } \format{ This data frame contains the following columns: \describe{ \item{date}{ Date (day/month/year) } \item{time}{ Descent time (military time) } \item{observed}{ Indicator of observed or not (1=observed, 0=not observed) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. } \examples{ data(baboon) } \keyword{datasets} KMsurv/man/lifetab.Rd0000644000176200001440000000362411360347503014160 0ustar liggesusers\name{lifetab} \alias{lifetab} \title{ Create cohort life table } \description{ Create cohort life table. } \usage{ lifetab(tis, ninit, nlost, nevent) } \arguments{ \item{tis}{ a vector of end points of time intervals, whose length is 1 greater than nlost and nevent. } \item{ninit}{ the number of subjects initially entering the study. } \item{nlost}{ a vector of the number of individuals lost follow or withdrawn alive for whatever reason. } \item{nevent}{ a vector of the number of individuals who experienced the event } } \value{ A data.frame with the following columns: \item{nsubs}{ the number of subject entering the intervals who have not experienced the event.} \item{nlost}{ the number of individuals lost follow or withdrawn alive for whatever reason. } \item{nrisk}{ the estimated number of individuals at risk of experiencing the event. } \item{nevent}{ the number of individuals who experienced the event. } \item{surv}{ the estimated survival function at the start of the intervals. } \item{pdf}{ the estimated probability density function at the midpoint of the intervals. } \item{hazard}{ the estimated hazard rate at the midpoint of the intervals. } \item{se.surv}{ the estimated standard deviation of survival at the beginning of the intervals. } \item{se.pdf}{ the estimated standard deviation of the prbability density function at the midpoint of the intervals. } \item{se.hazard}{ the estimated standard deviation of the hazard function at the midpoint of the intervals} The row.names are the intervals. } \author{ Jun Yan \email{jyan@stat.uconn.edu} } \examples{ tis <- c(0, 2, 3, 5, 7, 11, 17, 25, 37, 53, NA) nsubs <- c(927, 848, 774, 649, 565, 449, 296, 186, 112, 27) nlost <- c(2, 3, 6, 9, 7, 5, 3, rep(0, 3)) nevent <- c(77, 71, 119, 75, 109, 148, 107, 74, 85, 27) lifetab(tis, nsubs[1], nlost, nevent) } \keyword{ manip } KMsurv/man/kidney.Rd0000644000176200001440000000122111360341511014015 0ustar liggesusers\name{kidney} \alias{kidney} \non_function{} \title{data from Section 1.4} \description{ The \code{kidney} data frame has 119 rows and 3 columns. } \format{ This data frame contains the following columns: \describe{ \item{time}{ Time to infection, months } \item{delta}{ Infection indicator (0=no, 1=yes) } \item{type}{ Catheter placement (1=surgically, 2=percutaneously) } } } \source{ Klein and Moeschberger (1997) \emph{Survival Analysis Techniques for Censored and truncated data}, Springer. Nahman el at. J. Am Soc. Nephrology 3 (1992): 103-107. } \examples{ data(kidney) } \keyword{datasets} KMsurv/R/0000755000176200001440000000000007541770273011716 5ustar liggesusersKMsurv/R/lifetab.R0000644000176200001440000000156307501665340013446 0ustar liggesuserslifetab <- function (tis, ninit, nlost, nevent) { ## tis has length 1 more than other vectors Ypj <- c(ninit, ninit - cumsum(nlost + nevent)[-length(nevent)]) Yj <- Ypj - nlost/2 Sj <- cumprod(1 - nevent/Yj) qj <- nevent/Yj pj <- 1 - qj n <- length(Yj) Sj <- c(1, Sj[-n]) fmj <- c(diff(-1 * Sj), NA)/diff(tis) hmj <- nevent / diff(tis) / (Yj - nevent/2) hmj[n] <- NA Sj.se <- c(0, Sj[-1] * sqrt(cumsum(nevent/Yj/(Yj - nevent))[-length(Sj)])) fmj.se <- Sj*qj/diff(tis) * sqrt(c(0,cumsum(qj/Yj/pj)[-n]) + (pj/Yj/qj)) fmj.se[n] <- NA hmj.se <- sqrt(1 - (hmj * diff(tis)/2)^2) * sqrt(hmj^2/Yj/qj) hmj.se[n] <- NA data.frame(nsubs=Ypj, nlost=nlost, nrisk=Yj, nevent=nevent, surv=Sj, pdf=fmj, hazard=hmj, se.surv=Sj.se, se.pdf=fmj.se, se.hazard=hmj.se, row.names=paste(tis[-n-1], tis[-1], sep="-")) } KMsurv/DESCRIPTION0000644000176200001440000000102612057145172013212 0ustar liggesusersPackage: KMsurv Version: 0.1-5 Date: 2012/12/03 Title: Data sets from Klein and Moeschberger (1997), Survival Analysis Author: Original by Klein and Moeschberger, modifications by Jun Yan Maintainer: Jun Yan Description: Data sets and functions for Klein and Moeschberger (1997), "Survival Analysis, Techniques for Censored and Truncated Data", Springer. License: GPL (>= 3) Packaged: 2012-12-03 15:34:43 UTC; jyan Repository: CRAN Date/Publication: 2012-12-03 15:51:22