diff --git a/.travis.yml b/.travis.yml
index e294b14..423a934 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -4,12 +4,8 @@ python:
   - '2.7'
   - '3.5'
   - '3.6'
-
-matrix:
-  include:
-    - python: '3.7'  # temp solution until python 3.7 is more cleanly supported
-      dist: xenial
-      sudo: true
+  - '3.7'
+  - '3.8'
 
 install:
   - pip install .
diff --git a/requirements.txt b/requirements.txt
deleted file mode 100644
index c3584b4..0000000
--- a/requirements.txt
+++ /dev/null
@@ -1,9 +0,0 @@
-# minimal requirements for model management and core templates
-
-choicemodels >= 0.2.dev4
-numpy >= 1.14
-orca >= 1.4
-pandas >= 0.23
-patsy >= 0.4
-statsmodels >= 0.8
-urbansim >= 3.1
diff --git a/setup.py b/setup.py
index 511b093..2d7a28f 100644
--- a/setup.py
+++ b/setup.py
@@ -1,12 +1,8 @@
 from setuptools import setup, find_packages
 
-with open('requirements.txt') as f:
-    requirements = f.readlines()
-requirements = [item.strip() for item in requirements]
-
 setup(
     name='urbansim_templates',
-    version='0.2.dev7',
+    version='0.2.dev8', 
     description='UrbanSim extension for managing model steps',
     author='UrbanSim Inc.',
     author_email='info@urbansim.com',
@@ -17,8 +13,19 @@
         'Programming Language :: Python :: 3',
         'Programming Language :: Python :: 3.5',
         'Programming Language :: Python :: 3.6',
+        'Programming Language :: Python :: 3.7',
+        'Programming Language :: Python :: 3.8',
         'License :: OSI Approved :: BSD License'
     ],
     packages=find_packages(exclude=['*.tests']),
-    install_requires=requirements
-)
\ No newline at end of file
+    install_requires=[
+        'choicemodels >= 0.2.2.dev1',
+        'numpy >= 1.14',
+        'orca >= 1.4',
+        'pandas >= 0.23',
+        'patsy >= 0.4',
+        'statsmodels >= 0.8, <0.11; python_version <"3.6"',
+        'statsmodels >= 0.8; python_version >="3.6"',
+        'urbansim >= 3.1'
+    ]
+)
diff --git a/urbansim_templates/models/large_multinomial_logit.py b/urbansim_templates/models/large_multinomial_logit.py
index 12004cc..fab92ce 100644
--- a/urbansim_templates/models/large_multinomial_logit.py
+++ b/urbansim_templates/models/large_multinomial_logit.py
@@ -1,13 +1,15 @@
 from __future__ import print_function
 
 import orca
-from urbansim.models.util import columns_in_formula
+from urbansim.models.util import columns_in_formula, apply_filter_query
+from choicemodels.tools import MergedChoiceTable
 
 from .. import modelmanager
 from ..utils import get_data, update_column, to_list, version_greater_or_equal
 from .shared import TemplateStep
 
 
+
 def check_choicemodels_version():
     try:
         import choicemodels
@@ -458,8 +460,13 @@ def fit(self, mct=None):
         from choicemodels.tools import MergedChoiceTable
         
         if (mct is not None):
-            data = mct
-            
+            df_from_mct = mct.to_frame()
+            idx_names = df_from_mct.index.names
+            df_from_mct = df_from_mct.reset_index()
+            df_from_mct = apply_filter_query(
+                df_from_mct, self.chooser_filters).set_index(idx_names)
+            mct = MergedChoiceTable.from_df(df_from_mct)
+
         else:        
             observations = get_data(tables = self.choosers, 
                                     filters = self.chooser_filters,
@@ -606,4 +613,3 @@ def probs(mct):
                       column = self.out_column, 
                       fallback_column = self.choice_column,
                       data = choices)
-
diff --git a/urbansim_templates/models/segmented_large_multinomial_logit.py b/urbansim_templates/models/segmented_large_multinomial_logit.py
index 1d0b19a..d290072 100644
--- a/urbansim_templates/models/segmented_large_multinomial_logit.py
+++ b/urbansim_templates/models/segmented_large_multinomial_logit.py
@@ -120,31 +120,41 @@ def to_dict(self):
         return d
 
 
-    def get_segmentation_column(self):
+    def get_segmentation_column(self, mct=None):
         """
         Get the column of segmentation values from Orca. Chooser and alternative filters
         are applied to identify valid observations.
 
+        Parameters
+        ----------
+        mct : choicemodels.tools.MergedChoiceTable
+            This parameter is a temporary backdoor allowing us to pass in a more
+            complicated choice table than can be generated within the template, for
+            example including sampling weights or interaction terms.
+
         Returns
         -------
         pd.Series
 
         """
-        obs = get_data(tables = self.defaults.choosers,
-                       filters = self.defaults.chooser_filters,
-                       extra_columns = [self.defaults.choice_column,
-                                        self.segmentation_column])
+        if mct is not None:
+            df = mct.to_frame()
+        else:
+            obs = get_data(tables = self.defaults.choosers,
+                           filters = self.defaults.chooser_filters,
+                           extra_columns = [self.defaults.choice_column,
+                                            self.segmentation_column])
 
-        alts = get_data(tables = self.defaults.alternatives,
-                        filters = self.defaults.alt_filters)
+            alts = get_data(tables = self.defaults.alternatives,
+                            filters = self.defaults.alt_filters)
 
-        df = pd.merge(obs, alts, how='inner',
-                      left_on=self.defaults.choice_column, right_index=True)
+            df = pd.merge(obs, alts, how='inner',
+                          left_on=self.defaults.choice_column, right_index=True)
 
         return df[self.segmentation_column]
 
 
-    def build_submodels(self):
+    def build_submodels(self, mct=None):
         """
         Create a submodel for each category of choosers identified in the segmentation
         column. Only categories with at least one observation remaining after applying
@@ -152,11 +162,18 @@ def build_submodels(self):
 
         Running this method will overwrite any previous submodels.
 
+        Parameters
+        ----------
+        mct : choicemodels.tools.MergedChoiceTable
+            This parameter is a temporary backdoor allowing us to pass in a more
+            complicated choice table than can be generated within the template, for
+            example including sampling weights or interaction terms.
+
         """
         self.submodels = {}
         submodel = LargeMultinomialLogitStep.from_dict(self.defaults.to_dict())
 
-        col = self.get_segmentation_column()
+        col = self.get_segmentation_column(mct=mct)
 
         if (len(col) == 0):
             print("Warning: No valid observations after applying the chooser and "+
@@ -214,7 +231,7 @@ def update_submodels(self, param, value):
 
     def fit_all(self, mct=None):
         """
-        Fit all the submodels. Build the subomdels first, if they don't exist yet. This
+        Fit all the submodels. Build the submodels first, if they don't exist yet. This
         method can be run as many times as desired.
 
         Parameters
@@ -227,7 +244,7 @@ def fit_all(self, mct=None):
 
         """
         if (len(self.submodels) == 0):
-            self.build_submodels()
+            self.build_submodels(mct=mct)
 
         for k, m in self.submodels.items():
             print(' SEGMENT: {0} = {1} '.format(