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SvenKlaassenSvenKlaassen
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rename did multi files for consistency
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-153
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10 files changed

+102
-153
lines changed

‎monte-cover/src/montecover/did/__init__.py‎

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"""Monte Carlo coverage simulations for DiD."""
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from montecover.did.did_multi import DIDMultiCoverageSimulation
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from montecover.did.did_pa_multi import DIDMultiCoverageSimulation
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__all__ = ["DIDMultiCoverageSimulation"]

monte-cover/src/montecover/did/did_multi.py renamed to monte-cover/src/montecover/did/did_pa_multi.py

File renamed without changes.

‎results/did/did_multi_detailed.csv‎

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Learner g,Learner m,Score,In-sample-norm.,DGP,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
2-
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2+
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Linear,Linear,observational,False,6,0.9,0.8918333333333334,2.540792582093424,0.6659145487088738,0.893,3.64735417288717,1000
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22+
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Linear,Linear,observational,True,6,0.95,0.9423333333333334,2.9087792185359564,0.6398322462292214,0.945,3.923376128802193,1000

‎results/did/did_multi_eventstudy.csv‎

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Learner g,Learner m,Score,In-sample-norm.,DGP,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
2-
Linear,Linear,experimental,False,1,0.9,0.8746666666666666,0.42536022351351016,0.11129964461197367,0.856,0.6065601425726624,1000
3-
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Linear,Linear,observational,False,1,0.9,0.9048333333333334,0.4936490463630555,0.11703447731264664,0.911,0.7026803919052239,1000
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Linear,Linear,observational,True,4,0.95,0.8186666666666667,3.5293063192928438,1.0118391967276548,0.771,4.287491165909032,1000
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Linear,Linear,observational,True,6,0.9,0.8851666666666667,2.4823044000101313,0.660809427159733,0.894,3.171860461977204,1000
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Linear,Linear,observational,True,6,0.95,0.9428333333333334,2.957848128834568,0.660809427159733,0.945,3.6158624454294848,1000

‎results/did/did_multi_group.csv‎

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Learner g,Learner m,Score,In-sample-norm.,DGP,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
2-
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Linear,Linear,experimental,False,1,0.9,0.865,0.5332689974285741,0.14125883992697605,0.84,0.684967458838645,1000
3+
Linear,Linear,experimental,False,1,0.95,0.923,0.6354292028822721,0.14125883992697605,0.898,0.7737658489393863,1000
4+
Linear,Linear,experimental,False,4,0.9,0.6613333333333332,2.187885379540459,0.9604906586192218,0.498,2.7575340571302047,1000
5+
Linear,Linear,experimental,False,4,0.95,0.7556666666666666,2.607026227706741,0.9604906586192218,0.602,3.1362004034484614,1000
6+
Linear,Linear,experimental,False,6,0.9,0.8976666666666666,2.2072703099683895,0.5422311709957129,0.907,2.7789385342819997,1000
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Linear,Linear,experimental,False,6,0.95,0.9506666666666667,2.6301247970013075,0.5422311709957129,0.941,3.1616330454003854,1000
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Linear,Linear,experimental,True,1,0.9,0.8643333333333334,0.5331656474907569,0.1416028173409448,0.837,0.6848091387598605,1000
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Linear,Linear,experimental,True,1,0.95,0.9223333333333333,0.6353060538356899,0.1416028173409448,0.904,0.7729755854524409,1000
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Linear,Linear,experimental,True,4,0.9,0.6636666666666666,2.1871578881758738,0.9618357917015027,0.495,2.757365097655949,1000
11+
Linear,Linear,experimental,True,4,0.95,0.7556666666666666,2.606159368279076,0.9618357917015027,0.604,3.1339986032881795,1000
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Linear,Linear,experimental,True,6,0.9,0.8983333333333333,2.2070772542069657,0.5424515866558068,0.899,2.779655081198074,1000
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Linear,Linear,experimental,True,6,0.95,0.9513333333333334,2.629894756872995,0.5424515866558068,0.942,3.16003069657915,1000
14+
Linear,Linear,observational,False,1,0.9,0.902,0.6106049709052258,0.14629034271149396,0.89,0.7831902414227334,1000
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Linear,Linear,observational,False,1,0.95,0.947,0.727580699064038,0.14629034271149396,0.942,0.8844844476393456,1000
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Linear,Linear,observational,False,4,0.9,0.7813333333333333,3.0907797972605278,0.9943909423280353,0.706,3.8523704910840313,1000
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Linear,Linear,observational,False,4,0.95,0.8523333333333334,3.682891284376495,0.9943909423280353,0.809,4.39501177360628,1000
18+
Linear,Linear,observational,False,6,0.9,0.89,2.7865039885472247,0.7301188763670151,0.894,3.468312373428792,1000
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Linear,Linear,observational,False,6,0.95,0.95,3.3203242956346655,0.7301188763670151,0.945,3.9541003782057595,1000
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Linear,Linear,observational,True,1,0.9,0.8946666666666666,0.5896388541244254,0.14371827951522767,0.878,0.7568642372370822,1000
21+
Linear,Linear,observational,True,1,0.95,0.9423333333333334,0.7025980300212064,0.14371827951522767,0.936,0.8549636526386375,1000
22+
Linear,Linear,observational,True,4,0.9,0.777,3.0325048545897997,1.0070643044350587,0.698,3.7834488519755434,1000
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Linear,Linear,observational,True,4,0.95,0.8456666666666667,3.6134524072847696,1.0070643044350587,0.784,4.309691278217546,1000
24+
Linear,Linear,observational,True,6,0.9,0.8863333333333334,2.674147344485724,0.6969076659422232,0.89,3.3341905763684103,1000
25+
Linear,Linear,observational,True,6,0.95,0.9453333333333334,3.1864430966172987,0.6969076659422232,0.943,3.804017709516315,1000

‎results/did/did_multi_metadata.csv‎

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DoubleML Version,Script,Date,Total Runtime (minutes),Python Version,Config File
2-
0.10.dev0,DIDMultiCoverageSimulation,2025-03-21 13:02,3.9300304452578225,3.12.9,scripts/did/multi_config.yml
2+
0.10.dev0,DIDMultiCoverageSimulation,2025-03-21 13:46,3.4916115164756776,3.12.9,scripts/did/did_pa_multi_config.yml

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