生存分析：船尾模型，R中的simexaft包

Question

We are trying to reproduce the results of an accelarated failure time (aft) model in R, which has been coded in SAS.

The data set we use is here

There you can find the SAS code as well.

    formula <- survreg(Surv(Duration, Censor) ~ Acq_Expense + Acq_Expense_SQ + Ret_Expense + Ret_Expense_SQ + Crossbuy + Frequency + Frequency_SQ + Industry + Revenue + Employees, dist='weibull', data = daten [daten$Acquisition==1, ])
    out1 <- survreg(formula = formula, data = daten [daten$Acquisition==1, ], dist = "weibull")
    summary(out1)

    ind <- c("Duration", "Censor")

    err.mat <- ???

    out2 <- simexaft(formula = formula, data = daten [daten$Acquisition==1, ], SIMEXvariable = ind, repeated = FALSE, err.mat = err.mat, dist = "weibull")
    summary(out2)

Our question is how to define the err.mat term? err.mat specifies the variables with measurement errors. Since our data set is right censored I thought the variables with measurement error are probably Duration and/or Censor. But it is not as simple as that, err.mat must be a square symmetric numeric matrix.

Answer 1

If you read the Journal of Statistical Software,January 2012, Volume 46, article describing the simexaft package , it becomes clear that in the situation without repeated measurements to estimate the measurement errors from data, that you must supply these estimates yourself from domain knowledge. See the example in pages 6-8. Also see the cited "Statistics in Medicine" article available at Dr Yi's website . The measurement errors are the first two predictor variables, systolic blood pressure (SBP) and serum cholesterol(CHOL) in that example. If you are using the text from which you are extracting that data, then you will need to read the chapter text (which does not appear to be available at that website) to determine what assumptions they make about the measurement errors.