@@ -128,10 +128,10 @@ class PrePostFit(ExperimentalDesign):
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>>> result = cp.pymc_experiments.PrePostFit(
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... sc,
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... treatment_time,
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- ... formula="actual ~ 0 + a + b + c + d + e + f + g",
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+ ... formula="actual ~ 0 + a + g",
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... model=cp.pymc_models.WeightedSumFitter(
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... sample_kwargs={
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- ... "draws": 2000 ,
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+ ... "draws": 200 ,
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... "target_accept": 0.95,
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... "random_seed": seed,
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... "progressbar": False
@@ -140,16 +140,11 @@ class PrePostFit(ExperimentalDesign):
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... )
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>>> result.summary() # doctest: +NUMBER
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==================================Pre-Post Fit==================================
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- Formula: actual ~ 0 + a + b + c + d + e + f + g
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+ Formula: actual ~ 0 + a + g
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Model coefficients:
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- a 0.3, 94% HDI [0.3, 0.3]
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- b 0.0, 94% HDI [0.0, 0.0]
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- c 0.3, 94% HDI [0.2, 0.3]
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- d 0.0, 94% HDI [0.0, 0.1]
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- e 0.0, 94% HDI [0.0, 0.0]
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- f 0.1, 94% HDI [0.1, 0.2]
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- g 0.0, 94% HDI [0.0, 0.0]
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- sigma 0.2, 94% HDI [0.2, 0.3]
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+ a 0.62, 94% HDI [0.61, 0.64]
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+ g 0.38, 94% HDI [0.36, 0.39]
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+ sigma 0.76, 94% HDI [0.64, 0.90]
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"""
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def __init__ (
@@ -771,13 +766,14 @@ class RegressionDiscontinuity(ExperimentalDesign):
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--------
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>>> import causalpy as cp
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>>> df = cp.load_data("rd")
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+ >>> df['y'] = df['y'] - 1 # added for doctest stability
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>>> seed = 42
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>>> result = cp.pymc_experiments.RegressionDiscontinuity(
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... df,
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... formula="y ~ 1 + x + treated + x:treated",
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... model=cp.pymc_models.LinearRegression(
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... sample_kwargs={
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- ... "draws": 2000 ,
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+ ... "draws": 200 ,
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... "target_accept": 0.95,
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... "random_seed": seed,
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... "progressbar": False,
@@ -792,12 +788,12 @@ class RegressionDiscontinuity(ExperimentalDesign):
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Threshold on running variable: 0.5
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<BLANKLINE>
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Results:
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- Discontinuity at threshold = 0.91
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+ Discontinuity at threshold = 0.92
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Model coefficients:
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- Intercept 0.0 , 94% HDI [0 .0, 0.1 ]
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- treated[T.True] 2.4, 94% HDI [1.6 , 3.2]
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- x 1.3, 94% HDI [1.1, 1.5 ]
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- x:treated[T.True] -3.0 , 94% HDI [-4.1, -2.0]
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+ Intercept -0.9 , 94% HDI [-1 .0, -0.8 ]
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+ treated[T.True] 2.4, 94% HDI [1.7 , 3.2]
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+ x 1.3, 94% HDI [1.1, 1.4 ]
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+ x:treated[T.True] -3.1 , 94% HDI [-4.1, -2.0]
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sigma 0.3, 94% HDI [0.3, 0.4]
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"""
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