Merge pull request #210 from ACCLAB/mini-meta-weight-fix

Fixes mini-meta weight calculation

Author: JAnns98

README.md

@@ -435,17 +435,19 @@ def __init__(self, effectsizedataframe, permutation_count,
  self.__control_N,
  self.__test_var, 
  self.__test_N)
+ 
+ self.__bootstraps_variance = ci2g.calculate_bootstraps_var(self.__bootstraps)
 
  # Compute the weighted average mean differences of the bootstrap data
  # using the pooled group variances of the raw data as the inverse of 
  # weights
  self.__bootstraps_weighted_delta = ci2g.calculate_weighted_delta(
- self.__group_var, 
+ self.__bootstraps_variance, 
  self.__bootstraps)
 
  # Compute the weighted average mean difference based on the raw data
  self.__difference = es.weighted_delta(np.array(self.__effsizedf["difference"]),
- self.__group_var)
+ self.__bootstraps_variance)
 
  sorted_weighted_deltas = npsort(self.__bootstraps_weighted_delta)
 
@@ -753,6 +755,14 @@ def group_var(self):
  in order. 
  '''
  return self.__group_var
+ 
+ @property
+ def bootstraps_var(self):
+ '''
+ Return the variances of each bootstrapped mean difference distribution
+ in order. 
+ '''
+ return self.__bootstraps_variance
 
 
  @property

dabest/_delta_objects.py

@@ -27,6 +27,8 @@
  'dabest/_stats_tools/confint_2group_diff.py'),
  'dabest._stats_tools.confint_2group_diff.bootstrap_indices': ( 'API/confint_2group_diff.html#bootstrap_indices',
  'dabest/_stats_tools/confint_2group_diff.py'),
+ 'dabest._stats_tools.confint_2group_diff.calculate_bootstraps_var': ( 'API/confint_2group_diff.html#calculate_bootstraps_var',
+ 'dabest/_stats_tools/confint_2group_diff.py'),
  'dabest._stats_tools.confint_2group_diff.calculate_group_var': ( 'API/confint_2group_diff.html#calculate_group_var',
  'dabest/_stats_tools/confint_2group_diff.py'),
  'dabest._stats_tools.confint_2group_diff.calculate_weighted_delta': ( 'API/confint_2group_diff.html#calculate_weighted_delta',

dabest/_modidx.py

@@ -6,7 +6,7 @@
 __all__ = ['create_jackknife_indexes', 'create_repeated_indexes', 'compute_meandiff_jackknife', 'bootstrap_indices',
  'compute_bootstrapped_diff', 'delta2_bootstrap_loop', 'compute_delta2_bootstrapped_diff',
  'compute_meandiff_bias_correction', 'compute_interval_limits', 'calculate_group_var',
- 'calculate_weighted_delta']
+ 'calculate_bootstraps_var', 'calculate_weighted_delta']
 
 # %% ../../nbs/API/confint_2group_diff.ipynb 4
 import numpy as np
@@ -319,15 +319,23 @@ def calculate_group_var(control_var, control_N, test_var, test_N):
 
  return pooled_var
 
+def calculate_bootstraps_var(bootstraps):
 
-def calculate_weighted_delta(group_var, differences):
+ bootstraps_var_list = [np.var(x, ddof=1) for x in bootstraps]
+ bootstraps_var_array = np.array(bootstraps_var_list)
+ 
+ return bootstraps_var_array
+ 
+
+
+def calculate_weighted_delta(bootstrap_dist_var, differences):
  """
  Compute the weighted deltas.
  """
 
- weight = 1 / group_var
+ weight = np.true_divide(1, bootstrap_dist_var)
  denom = np.sum(weight)
  num = 0.0
  for i in range(len(weight)):
  num += weight[i] * differences[i]
- return num / denom
+ return np.true_divide(num, denom)

dabest/_stats_tools/confint_2group_diff.py

@@ -392,11 +392,11 @@ def _compute_hedges_correction_factor(n1,
 
 # %% ../../nbs/API/effsize.ipynb 13
 @njit(cache=True)
-def weighted_delta(difference, group_var):
+def weighted_delta(difference, bootstrap_dist_var):
  '''
  Compute the weighted deltas where the weight is the inverse of the
  pooled group difference.
  '''
 
- weight = np.true_divide(1, group_var)
+ weight = np.true_divide(1, bootstrap_dist_var)
  return np.sum(difference*weight)/np.sum(weight)

dabest/_stats_tools/effsize.py

@@ -373,18 +373,26 @@
  " \n",
  " return pooled_var\n",
  "\n",
+ "def calculate_bootstraps_var(bootstraps):\n",
  "\n",
- "def calculate_weighted_delta(group_var, differences):\n",
+ " bootstraps_var_list = [np.var(x, ddof=1) for x in bootstraps]\n",
+ " bootstraps_var_array = np.array(bootstraps_var_list)\n",
+ " \n",
+ " return bootstraps_var_array\n",
+ " \n",
+ "\n",
+ "\n",
+ "def calculate_weighted_delta(bootstrap_dist_var, differences):\n",
  " \"\"\"\n",
  " Compute the weighted deltas.\n",
  " \"\"\"\n",
  "\n",
- " weight = 1 / group_var\n",
+ " weight = np.true_divide(1, bootstrap_dist_var)\n",
  " denom = np.sum(weight)\n",
  " num = 0.0\n",
  " for i in range(len(weight)):\n",
  " num += weight[i] * differences[i]\n",
- " return num / denom"
+ " return np.true_divide(num, denom)"
  ]
  }
  ],

nbs/API/confint_2group_diff.ipynb

@@ -507,13 +507,13 @@
  "source": [
  "#| export\n",
  "@njit(cache=True)\n",
- "def weighted_delta(difference, group_var):\n",
+ "def weighted_delta(difference, bootstrap_dist_var):\n",
  " '''\n",
  " Compute the weighted deltas where the weight is the inverse of the\n",
  " pooled group difference.\n",
  " '''\n",
  "\n",
- " weight = np.true_divide(1, group_var)\n",
+ " weight = np.true_divide(1, bootstrap_dist_var)\n",
  " return np.sum(difference*weight)/np.sum(weight)"
  ]
  }

nbs/API/delta_objects.ipynb

@@ -2403,5 +2403,5 @@
  }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }