0.11.0-master

0.11.0

• fixes regression in KaplanMeierFitter.plot when using Seaborn and lifelines.
• introduce a new .plot function to a fitted CoxPHFitter instance. This plots the hazard coefficients and their confidence intervals.
• in all plot methods, the ix kwarg has been deprecated in favour of a new loc kwarg. This is to align with Pandas deprecating ix

0.10.1

0.10.1

• fix in internal normalization for CoxPHFitter predict methods.

0.10.0

• corrected bug that was returning the wrong baseline survival and hazard values in CoxPHFitter when normalize=True.
• removed normalize kwarg in CoxPHFitter. This was causing lots of confusion for users, and added code complexity. It's really nice to be able to remove it.
• correcting column name in CoxPHFitter.baseline_survival_
• CoxPHFitter.baseline_cumulative_hazard_ is always centered, to mimic R's basehaz API.
• new predict_log_partial_hazards to CoxPHFitter

0.8.0

• reorganized lifelines directories:
  • moved test files out of main directory.
  • moved utils.py into it's down directory.
  • moved all estimators fitters directory.
• added a at_risk column to the output of group_survival_table_from_events and survival_table_from_events
• added sample size and power calculations for statistical tests. See lifeline.statistics. sample_size_necessary_under_cph and lifelines.statistics. power_under_cph.
• fixed a bug when using KaplanMeierFitter for left-censored data.

Lifelines 0.7.0

0.7.0

• allow for multiple fitters to be passed into k_fold_cross_validation.
• statistical tests in lifelines.statstics. now return a StatisticalResult object with properties like p_value, test_results, and summary.
• fixed a bug in how log-rank statistical tests are performed. The covariance matrix was not being correctly calculated. This resulted in slightly different p-values.
• WeibullFitter, ExponentialFitter, KaplanMeierFitter and BreslowFlemingHarringtonFitter all have a conditional_time_to_event_ property that measures the median duration remaining until the death event, given survival up until time t.

ignore: Merge pull request #132 from CamDavidsonPilon/0.6.0

0.6.0

Lifelines 0.6.0

0.6.0

• Inclusion of the univariate fitters WeibullFitter and ExponentialFitter.
• Removing BayesianFitter from lifelines.
• Added new penalization scheme to AalenAdditiveFitter. You can now add a smoothing penalizer
  that will try to keep subsequent values of a hazard curve close together. The penalizing coefficient
  is smoothing_penalizer.
• Changed penalizer keyword arg to coef_penalizer in AalenAdditiveFitter.
• new ridge_regression function in utils.py to perform linear regression with l2 penalizer terms.
• Matplotlib is no longer a mandatory dependency.
• .predict(time) method on univariate fitters can now accept a scalar (and returns a scalar) and an iterable (and returns a numpy array)
• In KaplanMeierFitter, epsilon has been renamed to precision.

Lifelines 0.5.1

• New API for CoxPHFitter and AalenAdditiveFitter: the default arguments for event_col and duration_col. duration_col is now mandatory, and event_col now accepts a column, or by default, None, which assumes all events are observed (non-censored).
• Fix statistical tests
• Allow negative durations in Fitters
• New API in survival_table_from_events: min_observations is replaced by birth_times (default None).
• New API in CoxPHFitter for summary: summary will return a dataframe with statistics, print_summary() will print the dataframe (plus some other statistics) in a pretty manner.
• Adding "At Risk" counts option to univariate fitter plot methods, .plot(at_risk_counts=True).
• Fix Epanechnikov kernel.

Lifelines 0.5.0

• move testing to py.test
• refactor tests into smaller files
• make test_pairwise_logrank_test_with_identical_data_returns_inconclusive a better test
• add test for summary()
• Alternate metrics can be used for k_fold_cross_validation.

v0.4.4.1

• Makes column ordering explicit.

Lifelines 0.4.4

• Lots of improvements to numerical stability (but something things still need work)
• Additions to summary in CoxPHFitter.
• Make all prediction methods output a DataFrame
• Fixes bug in 1-d input not returning in CoxPHFitter
• Lots of new tests.