diff --git a/yli/survival.py b/yli/survival.py
index b5d8586..046068e 100644
--- a/yli/survival.py
+++ b/yli/survival.py
@@ -224,7 +224,7 @@ def plot_survfunc_turnbull(ax, time_left, time_right, ci, step_loc=0.5, maxiter=
 	
 	return handle
 
-def calc_survfunc_turnbull(time_left, time_right, ci, step_loc=0.5, maxiter=None, fail_prob_tolerance=None, se_method=None, zero_tolerance=None, transform_x=None, transform_y=None):
+def calc_survfunc_turnbull(time_left, time_right, ci, step_loc=0.5, maxiter=None, ll_tolerance=None, se_method=None, zero_tolerance=None, transform_x=None, transform_y=None):
 	# Estimate the survival function
 	
 	# Prepare arguments
@@ -232,9 +232,9 @@ def calc_survfunc_turnbull(time_left, time_right, ci, step_loc=0.5, maxiter=None
 	if maxiter:
 		hpstat_args.append('--max-iterations')
 		hpstat_args.append(str(maxiter))
-	if fail_prob_tolerance:
-		hpstat_args.append('--fail-prob-tolerance')
-		hpstat_args.append(str(fail_prob_tolerance))
+	if ll_tolerance:
+		hpstat_args.append('--ll-tolerance')
+		hpstat_args.append(str(ll_tolerance))
 	if se_method:
 		hpstat_args.append('--se-method')
 		hpstat_args.append(se_method)
@@ -270,12 +270,17 @@ def calc_survfunc_turnbull(time_left, time_right, ci, step_loc=0.5, maxiter=None
 		ypoints = transform_y(ypoints)
 	
 	if ci:
-		zstar = -stats.norm.ppf(config.alpha/2)
-		survival_prob_se = np.array(raw_result['survival_prob_se'])
-		
 		# Get confidence intervals
-		ci0 = survival_prob - zstar * survival_prob_se
-		ci1 = survival_prob + zstar * survival_prob_se
+		if raw_result['survival_prob_se']:
+			zstar = -stats.norm.ppf(config.alpha/2)
+			survival_prob_se = np.array(raw_result['survival_prob_se'])
+			
+			ci0 = survival_prob - zstar * survival_prob_se
+			ci1 = survival_prob + zstar * survival_prob_se
+		else:
+			survival_prob_ci = np.array(raw_result['survival_prob_ci'])
+			ci0 = survival_prob_ci.T[0]
+			ci1 = survival_prob_ci.T[1]
 		
 		# Plot confidence intervals
 		ypoints0 = np.concatenate([[1], ci0]).repeat(2)[:-1]