diff --git a/yli/regress.py b/yli/regress.py
index 4c220c1..d00436d 100644
--- a/yli/regress.py
+++ b/yli/regress.py
@@ -103,6 +103,7 @@ def regress(
 	nan_policy='warn',
 	exposure=None,
 	method=None, maxiter=None, start_params=None,
+	reduced=None,
 	bool_baselevels=False, exp=None
 ):
 	"""
@@ -123,6 +124,7 @@ def regress(
 	:param method: See statsmodels *model.fit*
 	:param maxiter: See statsmodels *model.fit*
 	:param start_params: See statsmodels *model.fit*
+	:param reduced: See :meth:`yli.IntervalCensoredCox`
 	:param bool_baselevels: Show reference categories for boolean independent variables even if reference category is *False*
 	:type bool_baselevels: bool
 	:param exp: Report exponentiated parameters rather than raw parameters, default (*None*) is to autodetect based on *model_class*
@@ -149,6 +151,8 @@ def regress(
 		fit_kwargs['maxiter'] = maxiter
 	if start_params is not None:
 		fit_kwargs['start_params'] = start_params
+	if reduced is not None:
+		fit_kwargs['reduced'] = reduced
 	
 	# Fit model
 	result = model_class.fit(dmatrices[0], dmatrices[1], **fit_kwargs)
@@ -689,7 +693,7 @@ class IntervalCensoredCox(RegressionModel):
 		self.lambda_ = None
 	
 	@classmethod
-	def fit(cls, data_dep, data_ind):
+	def fit(cls, data_dep, data_ind, *, reduced=False):
 		if len(data_dep.columns) != 2:
 			raise ValueError('IntervalCensoredCox requires left and right times')
 		
@@ -703,13 +707,18 @@ class IntervalCensoredCox(RegressionModel):
 		result.nevents = np.isfinite(data_dep.iloc[:, 1]).sum()
 		result.dof_model = len(data_ind.columns)
 		
+		# Prepare arguments
+		intcox_args = [config.hpstat_path, 'intcox', '-', '--output', 'json']
+		if reduced:
+			intcox_args.append('--reduced')
+		
 		# Export data to CSV
 		csv_buf = io.StringIO()
 		data_dep.join(data_ind).to_csv(csv_buf, index=False)
 		csv_str = csv_buf.getvalue()
 		
 		# Run intcens binary
-		proc = subprocess.run([config.hpstat_path, 'intcox', '-', '--output', 'json'], input=csv_str, stdout=subprocess.PIPE, stderr=None, encoding='utf-8', check=True)
+		proc = subprocess.run(intcox_args, input=csv_str, stdout=subprocess.PIPE, stderr=None, encoding='utf-8', check=True)
 		raw_result = json.loads(proc.stdout)
 		
 		from IPython.display import clear_output