The steps involved in the Double Machine Learning (DML) or cross-fit partialling-out approach.

(DOCX)

Bibliographic Details
Main Authors:	Emmanuel Skoufias (11873777), Katja Vinha (11873780)
Format:	Other Non-Article Part of Journal/Newspaper
Language:	unknown
Published:	2021
Subjects:	Medicine Neuroscience Biotechnology Sociology Developmental Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified two empirical approaches omitted variable bias mother &# 8217 early childhood development 2016 &# 8211 xlink "> data much wider set policy design based point estimates based statistically significant relationship hoc specification tend dml point estimates significant direct effect nigeria </ p ad hoc specification child ecd measures hoc specification direct effect much higher hoc manner employs data ecd ) dml specification indirect effect child stature child nutrition younger children urban areas sufficiently large serious enough select controls rural areas robust inferences reducing threats nutritional status internal validity driven methods double machine dml provides confidence interval complex picture chronic malnutrition average level analysis confirms absolute value DML
Online Access:	https://doi.org/10.1371/journal.pone.0260937.s001

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spelling	ftsmithonian:oai:figshare.com:article/17432048 2023-05-15T16:01:12+02:00 The steps involved in the Double Machine Learning (DML) or cross-fit partialling-out approach. Emmanuel Skoufias (11873777) Katja Vinha (11873780) 2021-12-23T18:37:42Z https://doi.org/10.1371/journal.pone.0260937.s001 unknown https://figshare.com/articles/journal_contribution/The_steps_involved_in_the_Double_Machine_Learning_DML_or_cross-fit_partialling-out_approach_/17432048 doi:10.1371/journal.pone.0260937.s001 CC BY 4.0 CC-BY Medicine Neuroscience Biotechnology Sociology Developmental Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified two empirical approaches omitted variable bias mother &# 8217 early childhood development 2016 &# 8211 xlink "> data much wider set policy design based point estimates based statistically significant relationship hoc specification tend dml point estimates significant direct effect nigeria </ p ad hoc specification child ecd measures hoc specification direct effect much higher hoc manner employs data ecd ) dml specification indirect effect child stature child nutrition younger children urban areas sufficiently large serious enough select controls rural areas robust inferences reducing threats nutritional status internal validity driven methods double machine dml provides confidence interval complex picture chronic malnutrition average level analysis confirms absolute value Text Journal contribution 2021 ftsmithonian https://doi.org/10.1371/journal.pone.0260937.s001 2022-01-06T11:38:56Z (DOCX) Other Non-Article Part of Journal/Newspaper DML Unknown
institution	Open Polar
collection	Unknown
op_collection_id	ftsmithonian
language	unknown
topic	Medicine Neuroscience Biotechnology Sociology Developmental Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified two empirical approaches omitted variable bias mother &# 8217 early childhood development 2016 &# 8211 xlink "> data much wider set policy design based point estimates based statistically significant relationship hoc specification tend dml point estimates significant direct effect nigeria </ p ad hoc specification child ecd measures hoc specification direct effect much higher hoc manner employs data ecd ) dml specification indirect effect child stature child nutrition younger children urban areas sufficiently large serious enough select controls rural areas robust inferences reducing threats nutritional status internal validity driven methods double machine dml provides confidence interval complex picture chronic malnutrition average level analysis confirms absolute value
spellingShingle	Medicine Neuroscience Biotechnology Sociology Developmental Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified two empirical approaches omitted variable bias mother &# 8217 early childhood development 2016 &# 8211 xlink "> data much wider set policy design based point estimates based statistically significant relationship hoc specification tend dml point estimates significant direct effect nigeria </ p ad hoc specification child ecd measures hoc specification direct effect much higher hoc manner employs data ecd ) dml specification indirect effect child stature child nutrition younger children urban areas sufficiently large serious enough select controls rural areas robust inferences reducing threats nutritional status internal validity driven methods double machine dml provides confidence interval complex picture chronic malnutrition average level analysis confirms absolute value Emmanuel Skoufias (11873777) Katja Vinha (11873780) The steps involved in the Double Machine Learning (DML) or cross-fit partialling-out approach.
topic_facet	Medicine Neuroscience Biotechnology Sociology Developmental Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified two empirical approaches omitted variable bias mother &# 8217 early childhood development 2016 &# 8211 xlink "> data much wider set policy design based point estimates based statistically significant relationship hoc specification tend dml point estimates significant direct effect nigeria </ p ad hoc specification child ecd measures hoc specification direct effect much higher hoc manner employs data ecd ) dml specification indirect effect child stature child nutrition younger children urban areas sufficiently large serious enough select controls rural areas robust inferences reducing threats nutritional status internal validity driven methods double machine dml provides confidence interval complex picture chronic malnutrition average level analysis confirms absolute value
description	(DOCX)
format	Other Non-Article Part of Journal/Newspaper
author	Emmanuel Skoufias (11873777) Katja Vinha (11873780)
author_facet	Emmanuel Skoufias (11873777) Katja Vinha (11873780)
author_sort	Emmanuel Skoufias (11873777)
title	The steps involved in the Double Machine Learning (DML) or cross-fit partialling-out approach.
title_short	The steps involved in the Double Machine Learning (DML) or cross-fit partialling-out approach.
title_full	The steps involved in the Double Machine Learning (DML) or cross-fit partialling-out approach.
title_fullStr	The steps involved in the Double Machine Learning (DML) or cross-fit partialling-out approach.
title_full_unstemmed	The steps involved in the Double Machine Learning (DML) or cross-fit partialling-out approach.
title_sort	steps involved in the double machine learning (dml) or cross-fit partialling-out approach.
publishDate	2021
url	https://doi.org/10.1371/journal.pone.0260937.s001
genre	DML
genre_facet	DML
op_relation	https://figshare.com/articles/journal_contribution/The_steps_involved_in_the_Double_Machine_Learning_DML_or_cross-fit_partialling-out_approach_/17432048 doi:10.1371/journal.pone.0260937.s001
op_rights	CC BY 4.0
op_rightsnorm	CC-BY
op_doi	https://doi.org/10.1371/journal.pone.0260937.s001
_version_	1766397159363575808

The steps involved in the Double Machine Learning (DML) or cross-fit partialling-out approach.

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