def print_comparative_outcomes(calibrated_model_no_drug,
calibrated_model_with_drug):
""" prints expected and percentage increase in average survival time when drug is available
:param calibrated_model_no_drug: calibrated model simulated when drug is not available
:param calibrated_model_with_drug: calibrated model simulated when drug is available
"""
# increase in survival time
increase_stat = Stat.DifferenceStatPaired(
name='Increase in mean survival time',
x=calibrated_model_with_drug.multiCohorts.multiCohortOutcomes.
meanSurvivalTimes,
y_ref=calibrated_model_no_drug.multiCohorts.multiCohortOutcomes.
meanSurvivalTimes)
# mean and prediction interval
mean = increase_stat.get_mean()
pred_int = increase_stat.get_PI(alpha=D.ALPHA)
print(
"Expected increase in mean survival time (years) and {:.{prec}%} prediction interval:"
.format(1 - D.ALPHA, prec=0), mean, pred_int)
# % increase in mean survival time
relative_diff_stat = Stat.RelativeDifferencePaired(
name='% increase in mean survival time',
x=calibrated_model_with_drug.multiCohorts.multiCohortOutcomes.
meanSurvivalTimes,
y_ref=calibrated_model_no_drug.multiCohorts.multiCohortOutcomes.
meanSurvivalTimes)
# estimate and prediction interval
mean = relative_diff_stat.get_mean()
pred_int = relative_diff_stat.get_PI(alpha=D.ALPHA)
print(
"Expected percentage increase in mean survival time and {:.{prec}%} confidence interval:"
.format(1 - D.ALPHA, prec=0), mean, pred_int)
def get_relative_diff_mean_interval(self,
scenario_name_base,
scenario_names,
outcome_name,
deci=0,
form=None):
"""
:return: dictionary of mean and percentile interval of the relative difference of the selected outcome
"""
if type(scenario_names) is not list:
scenario_names = [scenario_names]
list_mean_PI = {}
for name in scenario_names:
ratio_state = Stat.RelativeDifferencePaired(
name='',
x=self.scenarios[name].outcomes[outcome_name],
y_ref=self.scenarios[scenario_name_base].
outcomes[outcome_name],
order=1)
list_mean_PI[name] = Support.get_mean_interval(stat=ratio_state,
interval_type='p',
deci=deci,
form=form)
if len(scenario_names) == 1:
return list_mean_PI[scenario_names[0]]
else:
return list_mean_PI
def get_relative_diff_mean_PI(self,
time_index0,
time_index1,
order=0,
deci=0,
format=None):
"""
:return: the mean relative difference of trajectories at two time indeces
"""
stat = Stat.RelativeDifferencePaired('',
x=self.get_obss(time_index1),
y_ref=self.get_obss(time_index0),
order=order)
if format is None:
return stat.get_mean(), stat.get_PI(alpha=0.05)
else:
return stat.get_formatted_mean_and_interval(interval_type='p',
alpha=0.05,
deci=deci,
form=format)
def mytest_relativeDiff_stat_paied(x, y):
# define
stat = Stat.RelativeDifferencePaired(x, y, name='Test RelativeDifferencePaired')
print('Testing RelativeDifferencePaired:')
print_results(stat)
