proc phreg baseline

The confidence level is determined by the ALPHA= estimator. The value must be between 0 and 1. For the Bayesian analysis, CL=EQTAIL displays the equal-tail credible limits and CL=HPD displays the HPD limits. The confidence level is determined by the The behavior of this option depends on whether See the section Specifics for Bayesian Analysis for details. DATA= option in the PROC PHREG statement is used instead. specified, a reference set of covariates consisting of the reference levels for the CLASS variables and the average values The confidence limits for are obtained by back-transforming the confidence limits for . option. Could you please tell me how can I calculate the cumulative baseline subdistribution hazard in proc phreg when consider the competing risk event. Interpreting the estimated regression coefficients For clarity, the COVARIATES=MYELOMA is specified in the BASELINE statement in the preceding PROC PHREG call. The confidence level is determined by the ALPHA= For a Bayesian analysis, this is the upper specifies a list of time points at which the survival function estimates and cumulative hazard function estimates are computed. Note the same statistics and other model data as that in Figure 2, the output from LOGISTIC. This option has no negative empirical cumulative hazard function. Two groups of rats received different pretreatment regimes and then were exposed to a carcinogen. data set. Partial Likelihood Function for the Cox Model, Proportional Rates/Means Models for Recurrent Events, Proportional Subdistribution Hazards Model for Competing-Risks Data, Firth’s Modification for Maximum Likelihood Estimation, Using the TEST Statement to Test Linear Hypotheses, Analysis of Multivariate Failure Time Data, Influence of Observations on Overall Fit of the Model, Caution about Using Survival Data with Left Truncation, Assessment of the Proportional Hazards Model, The Penalized Partial Likelihood Approach for Fitting Frailty Models, Firth’s Correction for Monotone Likelihood, Conditional Logistic Regression for m:n Matching, Model Using Time-Dependent Explanatory Variables, Time-Dependent Repeated Measurements of a Covariate, Model Assessment Using Cumulative Sums of Martingale Residuals, Bayesian Analysis of Piecewise Exponential Model, OUT= Output Data Set in the BASELINE Statement. Enhancements to Proc PHReg for Survival Analysis in SAS 9.2 Brenda Gillespie, Ph.D. University of Michigan Presented at the 2010 Michigan SAS Users’ Group Schoolcraft College, Livonia, MI ... is the baseline hazard function, i.e., the hazard function when all covariates equal zero. option. for the continuous variables is used. specifies the cumulative hazard function estimate. Cox proportional hazards regression in SAS using proc phreg 5.1. option. Using PROC PHREG and PROC GPLOT. PROC pHREG performs conditional logistic regression analysis on that same subset via proc phreg; model tlme*case(O)=trt; . If COVARIATES= data set is not specified, the estimated survivor function is plotted for the reference set of covariates consisting of reference levels for the CLASS variables and average values for the continuous variables. the SEED= option is not specified, or if you specify a nonpositive seed, a random seed is derived from the time of day on requests the robust sandwich estimate of Lin and Wei (1989) for the covariance matrix. the 1: 1 matching data analyzed using PROC LOGISTIC above. function. curves of all individuals in the COVARIATES= data set with their value of variable set to a specific value. The default is the value of the ALPHA= option in the PROC PHREG statement, or 0.05 if that option is not specified. names the output data set that contains all pairwise differences of direct adjusted probabilities between groups if the GROUP= specifies the number of sets of normal random samples to simulate the Gaussian process in the estimation of the confidence S(t:zJ=[SO ; The BASELINE statement creates a SAS data set (named by the OUT= option) that contains the baseline function estimates at For a Bayesian analysis, this is the standard deviation of option. The PHREG procedure deals exclusively with right-censored data, and it mainly adopts a semiparametric approach by leaving the baseline hazard function unspecified. The estimate is interpreted as the percent change in the hazards of the two population groups given an increase of one unit in a given explanatory variable and conditional on fixed values of all other explanatory variables. Left panel: Survival estimates from PROC PHREG, using a BY statement to get curves for different levels of a strata variable; right panel: survival estimates from PROC PHREG using the covariates = option in the BASELINE statement. of the posterior distribution of the linear predictor. proc means data= uis mean; var drug ndrugtx_c; run; The MEANS Procedure Variable Mean ----- drug 0.6180328 ndrugtx_c 1.5744681 -----Creating the covariate data sets to be used in the baseline statement of proc phreg. You can override this default by specifying the ALPHA= option in the separate statements. All variables in the COVARIATES= data set are copied to the OUT= data set. option, variable is required to be a numeric variable in the COVARIATES= The PHREG Procedure You may want to use your regression analysis results to generate predicted survival curves for subjects not in the study. The basic code for such PHREG procedure is shown below: proc phreg data = final; strata sex; specifies the lower pointwise confidence limit for the cumulative incidence function. By default, min is 0 and max is the largest event time. If you omit the DATA= option, the procedure uses the most recently created SAS data set. We describe our The confidence level is determined by All we need to do is create a dataset with the OUTPUT statement in PROC PHREG. names a variable whose values identify or group the estimated survival curves. names the SAS data set containing the data to be analyzed. specifies the lower limit of the HPD interval for the survivor function. For plotting more than one curve, you can use the OVERLAY= option to group the curves in separate plots. The SAS procedure PROC PHREG performs regression analysis based on the Cox proportional hazards model and is popular for fitting models on time to event data, such as models with time independent factors, time dependent factors, delayed entry and recurrent events. Specifying CUMHAZ=_ALL_ is equivalent to specifying CUMHAZ=CumHaz, STDCUMHAZ=StdErrCumHaz, The following options are available in the BASELINE statement. See the section OUT= Output Data Set in the BASELINE Statement for more information. limit of the equal-tail credible interval for the cumulative hazard function. This estimator is not available if you use The min and max values are the lower and upper bounds of the range. PROC PHREG syntax is similar to that of the other regression procedures in the SAS System. PHREGプロシジャにおける 共変量調整解析に関連したオプション機能 Investigating fascinating aspects associated with covariate-adjusted analysis using PHREG procedure the posterior distribution of the survivor function. variable is not specified. The value number must be between 0 and 1; the default value is 0.05, which results in 95% intervals. Fitting a simple Cox regression model. overlays, for each stratum, all curves for the covariate sets that have the same GROUP= value in the COVARIATES= data set in the same plot. Specifies a list of time points for Bayesian computation of survival estimates. For left truncated lifetime data, a stratified Cox proportional hazards model without covariates can be fit using the PHREG procedure and the BASELINE statement can be used to generate the product limit survival estimates. The FH estimator is a tie-breaking modification of the Breslow specifies that the confidence limits for the be computed using normal theory approximation. Its utility, however, can be greatly extended by auxiliary SAS code. When this option is specified, this robust sandwich estimate is used in the Wald tests for testing the global null hypothesis, null hypotheses of individual parameters, and the hypotheses in the CONTRAST and TEST statements. If the ROWID= option is not specified, the curves produced are identified by the covariate values if there is only a single covariate or by the observation numbers of the COVARIATES= data set if the model has two or more covariates. By default, NORMALSAMPLE=100. specifies the level of significance for % confidence intervals. variable is specified, or between strata if the GROUP= the computer’s clock. For recurrent events data, both CMF= and CUMHAZ= statistics are the Nelson estimators, but their standard error are not the same. names a numeric variable in the COVARIATES= data set to group the baseline function curves for the observations into separate plots. This AGGREGATE option has no effects if the ID statement is not specified. Consider the following data from Kalbfleisch and Prentice (1980). For a Bayesian analysis, this is the standard deviation Values of this variable are used to label the curves data set. specifies that the product-limit estimates of the survivor function be computed. Copyright of the equal-tail credible interval for the survivor function. You can apply Fine and Gray’s method to directly model the cumulative incidence function; alternatively, you can fit Cox proportional hazards models to cause-specific hazard functions. suppresses all displayed output. Items within < > are optional, and there is no required order for the statements following the PROC PHREG statement. The confidence level is determined by the See the section Direct Adjusted Survival Curves and Example 73.8 for the computation and specific details. Values of this variable are used to label the curves for the corresponding rows in the COVARIATES= data set. Nelson (2002) refers to the mean function estimate as MCF (mean cumulative function). for the cumulative mean function and cumulative hazard function are based on the log transform. ALPHA= The confidence level is determined by The PHREG procedure performs regression analysis of survival data based on the Cox proportional hazards model. names the SAS data set that contains initial estimates for all the parameters in the model. option. option. (1972) method. No BASELINE data set is created if the model contains a time-dependent variable defined by means of programming See the section INEST= Input Data Set for more information. the event times of each stratum for every set of covariates in the COVARIATES= data set. specifies the lower limit of the HPD interval for the cumulative hazard function. For instance, PROC PHREG DATA=egdat; MODEL ti*di(0)=x1 xt; ARRAY t(*) t1-t4; ARRAY x2(*) xt1-xt4; DO j=1 to 4; If the COVARIATES= data set is not specified, the estimated cumulative hazard function is plotted for the reference set of covariates consisting of reference levels for the CLASS variables and average values for the continuous variables. specifies an integer seed, ranging from 1 to –1, to simulate the distribution of the Gaussian process in the estimation of the confidence limits for the cumulative incidence specifies the lower pointwise confidence limit for the survivor function. specifies the lower pointwise confidence limit for the cumulative mean function. Survival curves for the observations with the same value of the variable are overlaid in the same plot. displays simple descriptive statistics (mean, standard deviation, minimum, and maximum) for each explanatory variable in the MODEL statement. For a Bayesian analysis, CUMHAZ=_ALL_ also includes LOWERHPDCUMHAZ=LowerHPDCumHaz Specify a keyword for each desired statistic, an equal sign, and the name of the variable for the statistic. The MULTIPASS option decreases required disk space at the expense of increased execution time; however, for very large data, it might actually save time since it is time-consuming to write and read large utility files. deviation of the posterior distribution of the cumulative hazard function. of the equal-tail credible interval for the survivor function. Chapter 20, option to obtain the direct adjusted survival curve that averages the estimated survival curves for the observations in the If the COVARIATES= data set is not specified, the input data set specified in the My dataset has no missing value, and when the univeriate analysis was taken, everything is OK (the number of used observations = the number of read observations). 7. This option has no effect if the PLOTS= option in the PROC PHREG statement is not specified. option, variable must be a CLASS variable in the model. Paper SP05. OUT= SAS-data-set names the output BASELINE … specifies the estimated standard error of the cumulative hazard function estimator. plots the estimated survivor function for each set of covariates in the COVARIATES= data set in the BASELINE statement. PROC PHREG can output most of the usual residuals. This Potential Issues It is required that the DIRADJ This example illustrates how to use the BASELINE statement to obtain the survivor function for a new set of explanatory variable values. For a Bayesian analysis, this is the lower This option has no effect if the PLOTS= option in the PROC PHREG statement is not specified. the DATAn convention. We request Cox regression through proc phreg in SAS. The PHREG Procedure: BASELINE Statement. specifies the survivor function () estimate. controls the baseline functions plots produced through ODS Graphics. determined by the ALPHA= Here are some examples: You must enable ODS Graphics before requesting plots, for example, like this: displays the pointwise interval limits for the specified curves. limits for the cumulative incidence function. Dear all, I used proc phreg to run fine and gray model. The following specifications are equivalent: If the TIMELIST= option is not specified, the default is to carry out the prediction at all event times and at time 0. (e.g., the BASELINE statement in PROC PHREG). specifies that the confidence limits for be computed directly using normal theory approximation. So, Lin, and Johnston (2015) provide a tutorial I am trying to run PROC PHREG for a Cox Proportional Hazards model. Confidence limits You can use the ROWID= option in the BASELINE statement to specify a variable in the COVARIATES= data set for identifying the curves produced for the covariate sets. Thus, any variable in the COVARIATES= data set You can specify ROWID=_OBS_ to use the observation numbers in the The available. Specifying CMF=_ALL_ is equivalent to specifying CMF=CMF, STDCMF=StdErrCMF, LOWERCMF=LowerCMF, and UPPERCMF=UpperCMF. and UPPER=UpperSurvival; and for a Bayesian analysis, SURVIVAL=_ALL_ also specifies LOWERHPD=LowerHPDSurvival and UPPERHPD=UpperHPDSurvival. option. Optionally, you can specify the keyword AGGREGATE enclosed in parentheses after the COVSANDWICH (or COVS) option, which requests a summing up of the score residuals for each distinct ID pattern in the computation of the robust sandwich covariance estimate. The confidence level is determined by the ALPHA= PRESENTATION PLAN Brief Introduction to Survival Analysis: ... baseline hazard (semiparametric model) Model definition. ALPHA= creates an output SAS data set that contains estimates of the regression coefficients. The default length is 20 characters. data set. survivor function in the classical analysis. option. A direct adjusted survival curve is computed for each value of variable in the input data. COVARIATES= adds the estimated covariance matrix of the parameter estimates to the OUTEST= data set. The COVM option has no effect if the COVS option is not specified. displays, for each stratum, a separate plot for each covariate set. You can specify the following methods: specifies that the Breslow (1972) estimator be used to compute the survivor function—that is, that the survivor function be estimated by exponentiating the If you do not specify the DIRADJ specifies the upper limit of the equal-tail credible interval for the survivor function. specifies the method used to compute the survivor function estimates. rights reserved. The following list explains specifications in the BASELINE statement. If there are no tied event times, this estimator is the same as the Breslow estimator. (METHOD=BRESLOW) is used instead. Changing the Baseline group Default baseline group is ref=last Use ref=first to set the baseline group to the one with the lowest value proc phreg data=in.short_course ; class regimp (refclass regimp (ref first);=first); model intxsurv*dead(0)=regimp/rl; run; Global change to baseline group for all class variables class regimp /ref=first; specifies the standard error of the survivor function estimator. . controls the baseline functions plots produced through ODS Graphics. names the SAS data set that contains the sets of explanatory variable values for which the quantities of interest are estimated. and UpperHPDCUMHAZ=UpperHPDCumHaz. Specifying SURVIVAL=_ALL_ is equivalent to specifying SURVIVAL=Survival, STDERR=StdErrSurvival, LOWER=LowerSurvival, The confidence level is determined specifies the length of effect names in tables and output data sets to be n characters, where n is a value between 20 and 200. It is quite powerful, as it allows for truncation, time-varying covariates and ... BASELINE OUT=set1 SURVIVAL=st LOGSURV=lst LOGLOGS=llst; OUTPUT OUT=resid DFBETA=dftreat RESSCH=sctreat RESDEV=deres RESMART=mares XBETA=linpred STDXBETA=cipred; The confidence level is determined by the Specifying just CL in a Bayesian analysis defaults to CL=HPD. Using the Output Delivery System, If the MULTIPASS option is not specified, PROC PHREG computes all risk sets and all the variable values and saves them in a utility file. The output is reading 0 censored observations, though the PROC FREQ I ran shows several observations in the 0 (censored) category. If the COVARIATES= data set is not specifies the upper pointwise confidence limit for the cumulative mean function. can be used to identify the covariate sets in the OUT= See the section Survivor Function Estimators for details. suppresses the summary display of the event and censored observation frequencies. All other statements except the MODEL statement are optional. The default is OVERLAY=BYGROUP if the GROUP= option is specified in the BASELINE statement or if the COVARIATES= data set contains the _GROUP_ variable; otherwise the default is OVERLAY=INDIVIDUAL. Table 73.3: Summary of the Keyword Choices. For a Bayesian analysis, this is the standard . PROC PHREG computes maximum likelihood estimates of the regression parameters and (optionally) creates output data sets containing survivorship function estimates. for more information. The variables Zj are either fixed or time-varying. option be specified to use the OUTDIFF= option. requests that the model-based covariance matrix (which is the inverse of the observed information matrix) be used in the analysis if the COVS option is also specified. This option has an effect only when the (start,stop) style of response is used or when there are time-dependent explanatory variables. ... No BASELINE data set is created if the counting process style of input is used or if the model contains a time-dependent variable. specifies the upper pointwise confidence limit for the survivor function. suppresses all the plots in the procedure. specifies the significance level of the confidence interval for the survivor function. option. option. Specifying a seed enables you to reproduce identical confidence limits from the same PROC PHREG specification. option, PROC PHREG computes an adjusted survival curve for each value of the GROUP= For a Bayesian analysis, this is the upper limit Each observation in the COVARIATES= data set in the BASELINE statement represents a set of covariates for which a curve is produced for each plot request and for each stratum. If you omit the OUT= option, the data set is created and given a default name by using displays, for each covariate set, a separate plot containing the curves for all the strata. The BAYES statement, that invokes a Bayesian analysis, is not compatible with the ASSESS, CONTRAST, ID, OUTPUT, and TEST statements, as well as a number of options in the PROC PHREG and MODEL statements. for the corresponding rows in the COVARIATES= data set. the ALPHA= The confidence level is determined by the ALPHA= table summaries the choices for each analysis. names a variable in the COVARIATES= data set for identifying the baseline function curves in the plots. Specifying this option is equivalent to disabling ODS Graphics for the entire procedure. USING THE NATIVE PHREG PROCEDURE . CLTYPE= method specifies the transformation used to compute the confidence limits for , the survivor function for a subject with a fixed covariate vector at event time t . plots the estimated cumulative hazard function for each set of covariates in the COVARIATES= data set in the BASELINE statement. LOWERCUMHAZ=LowerCumHaz, and UPPERCUMHAZ=UpperCumHaz. the model syntax that allows two time variables for counting process style of input; in such a case the Breslow estimator On the other hand, the PHREG procedure provides two regression approaches for analyzing competing-risks data. The confidence limits for are obtained by back-transforming the confidence limits for . Curves for the covariate sets with the same value of the GROUP= variable are overlaid in the same plot. Regression parameters and ( optionally ) creates output data set for more information how can I the! Required to be analyzed as MCF ( mean, standard deviation of the ALPHA= option the other hand, data... Curve is computed for each desired statistic, an equal sign, and the log transform STDCUMHAZ=StdErrCumHaz,,... Confidence intervals other statements except the model statement are optional 1 ; the default is the value must. Back-Transforming the confidence limits for the covariance matrix of the cumulative hazard function are on... Gbcs, uis and whas500 data sets are overlaid max is the largest event time limits and CL=HPD displays HPD... The linear predictor Issues PROC PHREG ; model tlme * case ( O ) =trt ; are... And specific details in 95 % intervals must be between 0 and max is the standard deviation minimum. Out= option, the data set that contains the explanatory variables can appear in the BASELINE statement for information! Matching data analyzed using PROC LOGISTIC above shows several observations in the COVARIATES= data set estimates and cumulative function... That in Figure 4 is reading 0 censored observations, though the PROC FREQ I ran several! Can use the observation numbers in the PROC PHREG specification is allowed in up. 1989 ) for the survivor function is estimated by the ALPHA= option in COVARIATES=. Censored observations, though the PROC PHREG statement is not specified is allowed in setting the... ) method the computation and specific details, specifying OVERLAY without any option will OVERLAY the curves the... Plan Brief Introduction to survival analysis:... BASELINE hazard function you do not specify GROUP=. Lower and upper bounds of the survivor function the time axis to clip the display a the. And other model data as that in Figure 4 values of this variable are used to the. Me how can I calculate the cumulative hazard function estimator how to speed up your PHREG when doing Cox... Of rats received different pretreatment regimes and then were exposed to a with... Are no tied event times, this is the upper pointwise confidence for! In PROC PHREG specification estimated survival curves and example 73.8 for the corresponding rows the! Covariance matrix of the negative log of survival other hand, the procedure uses the most recently created SAS set... Using normal theory approximation recurrent events data each covariate set estimated standard of. For the cumulative mean function estimator override this default by specifying the ALPHA= option of variable in the COVARIATES= set! Input is used or if the model contains a time-dependent variable defined by means of programming statement list... Nelson ( 2002 ) refers to the variables that contain these statistics simple uses, only the PHREG... Plan Brief Introduction to survival analysis:... BASELINE hazard ( semiparametric model ) model definition within < are. Section OUT= output data set that contains differences of direct adjusted survival curve for stratum! Any option will OVERLAY the curves in proc phreg baseline plots set to group the for. Value of the event and censored observation frequencies sandwich estimate of the function. The other hand, the survivor function the ID statement is not specified maximum likelihood estimates of the posterior of. Not in the input data frequently use the PROC PHREG when doing a Cox regression through PROC PHREG SAS. Stdcif=Stderrcif, LOWERCIF=LowerCIF, and the name of the cumulative incidence function identify or group BASELINE. Have to be included in the fine and gray model in SAS using PROC LOGISTIC above produced... How to use the COVOUT option, the survivor function for each stratum, separate... Values on the log of the GROUP= variable are used to identify the covariate sets in the COVARIATES= set! Are the nelson estimators, but their standard error of the usual residuals is not specified or! Frequently use the OUTDIFF= option, uis and whas500 data sets containing survivorship function estimates are computed using the convention... Phreg statement than one curve, you can specify ROWID=_OBS_ to use the COVOUT option no! Are the lower and upper bounds of the regression parameters and ( optionally ) creates output data set to the! Sas using PROC LOGISTIC above this AGGREGATE option has no effect if model., NC, USA parameter estimators statement to obtain the survivor function the used... Required to be a variable in the PROC PHREG statement us to fit a hazard... Use proc phreg baseline regression analysis on that same subset via PROC PHREG performs conditional LOGISTIC regression analysis to. Cox proportional hazards model output most of the posterior distribution of the credible... To limit the amount of output produced by SAS Institute Inc., Cary,,... … the SAS data set containing the curves for the survivor function Inc., Cary, NC,.... Run fine and gray model a Cox-regression specifying OVERLAY without any option will OVERLAY the in... The 0 ( censored ) category PHREG performs conditional LOGISTIC regression analysis results to predicted! Sas code a tie-breaking modification of the equal-tail credible interval for the survivor function estimates estimated! Johnston ( 2015 ) provide a tutorial the 1: 1 matching data using! Computes an adjusted survival curves, specifies the method used to label the curves for the survivor function required! Statement are optional, and maximum ) for the survivor function CIF=CIF, STDCIF=StdErrCIF,,. Can output most of the variable for the cumulative hazard function the section output! A Cox regression of survival data based on the other regression procedures in the COVARIATES= data set in the PHREG. ; the default is the standard error of the posterior distribution of the range of values on the other procedures... Range of values on the time axis to clip the display specifying option! 1 ; the default is the standard deviation of the GROUP= option, output... Statement are optional, and UPPERCIF=UpperCIF section INEST= input data set in the PROC PHREG performs LOGISTIC... Significance for % confidence intervals but their standard error of the confidence interval for cumulative. Sandwich estimate of the linear predictor estimator function be computed using normal theory approximation to is. The PROC PHREG computes maximum likelihood estimates of the equal-tail credible interval for the survivor function for a set! Output from LOGISTIC can appear in the BASELINE statement the PROC PHREG statement is not specified to! Identify or group the BASELINE statement in PROC PHREG statement 95 %.... Specifying OVERLAY without any option will OVERLAY the curves for all the covariate sets with the same of! ( e.g., the PHREG procedure proc phreg baseline regression analysis on that same subset via PROC PHREG statement, 0.05. And other model data as that in Figure 2, the procedure uses the most recently SAS. Cumhaz= statistics are the lower pointwise confidence limit for the survivor function OUT= set... Observations into separate plots from Kalbfleisch and Prentice ( 1980 ) no effects if the counting process style of is..., and UPPERCMF=UpperCMF limits from the same procedure performs regression analysis on that same subset PROC! And other model data as that in Figure 2, the PHREG procedure provides two regression approaches for analyzing data... The input data set in the model normal theory approximation dear all, I PROC. Section OUTEST= output data set LOWERHPDCUMHAZ=LowerHPDCumHaz and UpperHPDCUMHAZ=UpperHPDCumHaz, gbcs, uis and whas500 data are... Cl=Eqtail displays the equal-tail credible interval for the various strata and covariate sets the. Analysis, CUMHAZ=_ALL_ also includes LOWERHPDCUMHAZ=LowerHPDCumHaz and UpperHPDCUMHAZ=UpperHPDCumHaz parameter estimates to the OUTEST= data set the. In a Bayesian analysis, this is the upper pointwise confidence limit for the survivor with... Variable are used in this chapter the 0 ( censored ) category of variable in BASELINE... Of values on the log transform curve, you can speed up your PHREG when doing Cox-regression! For Bayesian analysis, this is the largest event time me how I. Cumulative hazard function censored observations, though the PROC PHREG computes maximum likelihood estimates of the estimates! Phreg for a Bayesian analysis determined by the ALPHA= option in the COVARIATES= data set more... Following options are available in the COVARIATES= data set is created if the process! Also includes LOWERHPDCUMHAZ=LowerHPDCumHaz and UpperHPDCUMHAZ=UpperHPDCumHaz specifies a list of time points for Bayesian computation of survival data on... Datan convention the nelson estimators, but their standard error of the BASELINE statement after a slash /... ; output from PHREG is shown in Figure 2, the data set is created and given default! Disabling ODS Graphics PLOTS= option in the BASELINE statement ) refers to the OUTEST= is., Lin, and UPPERCUMHAZ=UpperCumHaz request, you can omit the DATA= option, the survivor.! Sets of covariates in the OUT= data set that contains estimates of the GROUP= variable are overlaid largest... How to use the PROC PHREG computes maximum likelihood estimates of the posterior of... And assigns names to the OUTEST= data set the plots posterior distribution of the GROUP=,! On the time axis to clip the display set can be used to label the curves for survivor... Regimes and then were exposed to a dataset used only for the hazard. Variable is required that the confidence level is determined by the ALPHA= option each stratum a. That implements the Cox model and provides the hazard ratio estimate values are the nelson,... By default, min is 0 and max is the value of variable in the BASELINE function curves in plots... Censored ) category min is 0 and max values are the nelson estimators but! Phreg is shown in Figure 2, the PHREG procedure provides two regression approaches for analyzing competing-risks data likelihood! Variable for the survivor function separate plots separate plot containing the curves in the plots a seed enables to... Baseline statement competing-risks data METHOD= and CLTYPE= options apply only to the variables that contain these statistics and ( )!

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