diff --git a/pyproject.toml b/pyproject.toml
index 5eeae69..9df5899 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -14,7 +14,8 @@ dependencies = ["ipython",
                 "matplotlib",
 		"numpy",
 		"scipy",
-		"pandas",
+        "pandas>=1.5,<2.0; python_version < '3.9'",
+        "pandas==2.3.3; python_version >= '3.9'",
 		"openpyxl",
 		"xlrd"]
 # 		"pyreadstat"]
diff --git a/src/pyWitness/DataProcessed.py b/src/pyWitness/DataProcessed.py
index 2649690..ab47de6 100644
--- a/src/pyWitness/DataProcessed.py
+++ b/src/pyWitness/DataProcessed.py
@@ -489,11 +489,18 @@ def p0(x, a,b) :
         return dPrime
 
     def calculateCriterion(self):
-        zT = _special.ndtri(self.data_rates.loc['targetPresent','suspectId'])
+        epsilon = 0.5 / len(self.dataRaw.data)
+        hit_rate = self.data_rates.loc['targetPresent','suspectId'].copy()
+
         try :
-            zL = _special.ndtri(self.data_rates.loc['targetAbsent','suspectId'])
-        except : # only for TA showups and the participant never made a suspectId
-            zL = _special.ndtri(self.data_rates.loc['targetAbsent','rejectId'])
+            fa_rate = self.data_rates.loc['targetAbsent','suspectId'].copy()
+        except KeyError:
+            fa_rate = self.data_rates.loc['targetAbsent','rejectId'].copy()
+
+        hit_rate = hit_rate.clip(lower=epsilon, upper=1 - epsilon)
+        fa_rate = fa_rate.clip(lower=epsilon, upper=1 - epsilon)
+        zT = _special.ndtri(hit_rate)
+        zL = _special.ndtri(fa_rate)
 
         dCriterion = - (zT + zL)/2.0
         dCriterion.name = ("criterion", "central")