diff --git a/R/flexsurvreg.R b/R/flexsurvreg.R
index 1f56ca1..5ac30b9 100644
--- a/R/flexsurvreg.R
+++ b/R/flexsurvreg.R
@@ -343,21 +343,24 @@ check.flexsurv.response <- function(Y){
     if (!inherits(Y, "Surv"))
         stop("Response must be a survival object")
 ### convert Y from Surv object to numeric matrix
+    type <- attr(Y, "type")
 ### though "time" only used for initial values, printed time at risk, empirical hazard
-    if (attr(Y, "type") == "counting")
+    if (type == "counting")
         Y <- cbind(Y, time=Y[,"stop"] - Y[,"start"], time1=Y[,"stop"], time2=Inf)
-    else if (attr(Y, "type") == "interval"){
+    else if (type == "interval"){ # Surv() converts interval2 to interval
         Y[,"time2"][Y[,"status"]==0] <- Inf   # upper bound with right censoring 
+        Y[,"time2"][Y[,"status"]==1] <- Y[,"time1"][Y[,"status"]==1]  # event time
         Y[,"time2"][Y[,"status"]==2] <- Y[,"time1"][Y[,"status"]==2]
         Y[,"time1"][Y[,"status"]==2] <- 0  # 
         Y <- cbind(Y, start=0, stop=Y[,"time1"], time=Y[,"time1"])
     }
-    else if (attr(Y, "type") == "right")
+    else if (type == "right")
         Y <- cbind(Y, start=0, stop=Y[,"time"], time1=Y[,"time"], time2=Inf)
     else stop("Survival object type \"", attr(Y, "type"), "\"", " not supported")
     if (any(Y[,"time1"]<0)){
         stop("Negative survival times in the data")
     }
+    attr(Y, "type") <- type
     Y
 }
 
diff --git a/R/plot.flexsurvreg.R b/R/plot.flexsurvreg.R
index 5ede4cd..b51a32b 100644
--- a/R/plot.flexsurvreg.R
+++ b/R/plot.flexsurvreg.R
@@ -96,8 +96,8 @@ plot.flexsurvreg <- function(x, newdata=NULL, X=NULL, type="survival", fn=NULL,
                              add=FALSE,...)
 {
     ## don't calculate or plot CIs by default if all covs are categorical -> multiple curves
-  if (!add && is.null(x[["data"]]))
-    stop("Goodness-of-fit plots are not available if the data have been removed from the model object")
+    if (!add && is.null(x[["data"]]))
+        stop("Goodness-of-fit plots are not available if the data have been removed from the model object")
     if (is.null(ci))
         ci <- ((x$ncovs == 0) || (!all(x$covdata$isfac)))
     if (!ci) B <- 0
@@ -112,7 +112,10 @@ plot.flexsurvreg <- function(x, newdata=NULL, X=NULL, type="survival", fn=NULL,
         mf <- model.frame(x)
         Xraw <- mf[,attr(mf, "covnames.orig"), drop=FALSE]
         mm <- as.data.frame(model.matrix(x))
-        form <- "Surv(dat$Y[,\"start\"],dat$Y[,\"stop\"],dat$Y[,\"status\"]) ~ "
+        if (isTRUE(attr(dat$Y, "type")=="interval")){ # guard against NULL from older versions
+            form <- "Surv(dat$Y[,\"time1\"],dat$Y[,\"time2\"],type=\"interval2\") ~ "
+        } else 
+            form <- "Surv(dat$Y[,\"start\"],dat$Y[,\"stop\"],dat$Y[,\"status\"]) ~ "
         form <- paste(form, if (x$ncovs > 0 && all(x$covdata$isfac)) paste("mm[,",1:x$ncoveffs,"]", collapse=" + ") else 1)
         form <- as.formula(form)
         ## If any continuous covariates, it is hard to define subgroups
@@ -139,7 +142,7 @@ plot.flexsurvreg <- function(x, newdata=NULL, X=NULL, type="survival", fn=NULL,
                 group <- if(x$ncovs>0) do.call("interaction", mm) else factor(rep(0,nrow(dat$Y)))
                 Xgroup <- factor(do.call("interaction", as.data.frame(X)), levels=levels(group))
                 haz <- list()
-              for (i in 1:nrow(X)) {
+                for (i in 1:nrow(X)) {
                     mha <- muhaz.args
                     if (is.null(mha$max.time)) mha$max.time <- with(as.data.frame(dat$Y[group==Xgroup[i],,drop=FALSE]), max(time[status==1]))
                     haz[[i]] <- do.call("muhaz", c(list(times=dat$Y[,"time"], delta=dat$Y[,"status"], subset=(group==Xgroup[i])), mha))
diff --git a/tests/testthat/test_flexsurvreg.R b/tests/testthat/test_flexsurvreg.R
index d71a837..88a0206 100644
--- a/tests/testthat/test_flexsurvreg.R
+++ b/tests/testthat/test_flexsurvreg.R
@@ -367,10 +367,12 @@ test_that("Interval censoring",{
     sr2 <- survreg(Surv(tmin, status) ~ 1, dist="weibull")
     expect_equal(sr1$loglik[2], sr2$loglik[2])
     
-    fs1 <- flexsurvreg(Surv(tmin, tmax.sr, type="interval2") ~ 1, dist="weibull")
+    fs1_inf <- flexsurvreg(Surv(tmin, tmax, type="interval2") ~ 1, dist="weibull")
+    fs1_na <- flexsurvreg(Surv(tmin, tmax.sr, type="interval2") ~ 1, dist="weibull")
     fs2 <- flexsurvreg(Surv(simt, status) ~ 1, dist="weibull")
-    expect_equal(fs1$loglik, fs2$loglik)
-    expect_equal(fs1$loglik, sr1$loglik[2])
+    expect_equal(fs1_inf$loglik, fs2$loglik)
+    expect_equal(fs1_na$loglik, fs2$loglik)
+    expect_equal(fs1_inf$loglik, sr1$loglik[2])
 
     ## put an upper bound on censored times
     tmax <- ifelse(status==1, simt, 0.7)
@@ -382,7 +384,14 @@ test_that("Interval censoring",{
     status[status==0] <- 3
     fs3 <- flexsurvreg(Surv(tmin, tmax, status, type="interval") ~ 1, dist="weibull")
     expect_equal(fs1$loglik, fs3$loglik)
-
+    
+    ## interval censoring with zero width interval
+    set.seed(1)
+    tmin <- tmax <- rweibull(100, 1.1, 1.5)
+    fs1 <- flexsurvreg(Surv(tmin, tmax, type="interval2") ~ 1, dist="weibull")
+    fs2 <- flexsurvreg(Surv(tmin) ~ 1, dist="weibull")
+    expect_equal(fs1$loglik, fs2$loglik)
+    
     ## interval censoring close around the event
     set.seed(1)
     tev <- rweibull(100, 1.1, 1.5)
@@ -391,7 +400,7 @@ test_that("Interval censoring",{
     fs1 <- flexsurvreg(Surv(tev) ~ 1, dist="weibull")
     fs2 <- flexsurvreg(Surv(tmin, tmax, type="interval2") ~ 1, dist="weibull")
     expect_equal(fs2$res["shape","est"], fs1$res["shape","est"], tol=1e-03)
-
+    
     ## relative survival with left and interval censoring
     ## at left cens times, bhazard contains the background cond prob of surviving interval
     bh <- rep(0.01, length(tmax))