<?xml version="1.0" encoding="utf-8"?>
<journal>
<title>Journal of Community  Health Research</title>
<title_fa>مجله تحقیقات سلامت</title_fa>
<short_title>JCHR</short_title>
<subject>Medical Sciences</subject>
<web_url>http://jhr.ssu.ac.ir</web_url>
<journal_hbi_system_id>1</journal_hbi_system_id>
<journal_hbi_system_user>admin</journal_hbi_system_user>
<journal_id_issn>2322-5688</journal_id_issn>
<journal_id_issn_online>2345-2609</journal_id_issn_online>
<journal_id_pii></journal_id_pii>
<journal_id_doi></journal_id_doi>
<journal_id_iranmedex></journal_id_iranmedex>
<journal_id_magiran></journal_id_magiran>
<journal_id_sid>27545</journal_id_sid>
<journal_id_nlai></journal_id_nlai>
<journal_id_science>12727</journal_id_science>
<language>en</language>
<pubdate>
	<type>jalali</type>
	<year>1403</year>
	<month>10</month>
	<day>1</day>
</pubdate>
<pubdate>
	<type>gregorian</type>
	<year>2025</year>
	<month>1</month>
	<day>1</day>
</pubdate>
<volume>14</volume>
<number>1</number>
<publish_type>online</publish_type>
<publish_edition>1</publish_edition>
<article_type>fulltext</article_type>
<articleset>
	<article>


	<language>en</language>
	<article_id_doi></article_id_doi>
	<title_fa></title_fa>
	<title>Tutorial on Methods to Adjust for Confounding Variable in Medical Research</title>
	<subject_fa>اپیدمیولوژی</subject_fa>
	<subject>Epidemiology</subject>
	<content_type_fa>مروری</content_type_fa>
	<content_type>Review</content_type>
	<abstract_fa></abstract_fa>
	<abstract>&lt;div style=&quot;text-align: justify;&quot;&gt;&lt;span style=&quot;font-size:12px;&quot;&gt;&lt;span style=&quot;font-family:Times New Roman;&quot;&gt;&lt;span style=&quot;line-height:150%&quot;&gt;&lt;b&gt;&lt;span style=&quot;line-height:150%&quot;&gt;Background:&lt;/span&gt;&lt;/b&gt;&lt;span style=&quot;line-height:150%&quot;&gt; Confounders can distort the actual connection between exposure and outcome, resulting in skewed results. In research, it is essential to account for confounding variables to preserve the validity of causal inferences.&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;line-height:150%&quot;&gt;&lt;b&gt;&lt;span style=&quot;line-height:150%&quot;&gt;&amp;nbsp;Methods:&lt;/span&gt;&lt;/b&gt;&lt;span style=&quot;line-height:150%&quot;&gt; In this narrative review study, all statistical methods for adjusting confounding variable such as standardization, propensity score, stratification, restriction, statistical model for control, matching, randomization were reviewed.&amp;nbsp; &lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;line-height:150%&quot;&gt;&lt;b&gt;&lt;span style=&quot;line-height:150%&quot;&gt;Results&lt;/span&gt;&lt;/b&gt;&lt;span style=&quot;line-height:150%&quot;&gt;: The five most important methods were reviewed.&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;line-height:150%&quot;&gt;&lt;b&gt;&lt;span style=&quot;line-height:150%&quot;&gt;Conclusion:&lt;/span&gt;&lt;/b&gt;&lt;span style=&quot;line-height:150%&quot;&gt; Adequate adjustment improves the internal validity of findings and elucidates the relationships among variables, underscoring the importance of a comprehensive analysis of confounding for trustworthy research results.&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/div&gt;</abstract>
	<keyword_fa></keyword_fa>
	<keyword>Confounding variable, Adjustment, Statistical methods, Matching, stratification</keyword>
	<start_page>97</start_page>
	<end_page>103</end_page>
	<web_url>http://jhr.ssu.ac.ir/browse.php?a_code=A-10-1445-4&amp;slc_lang=en&amp;sid=1</web_url>


<author_list>
	<author>
	<first_name>Muhammad </first_name>
	<middle_name></middle_name>
	<last_name>Ajmal Dina</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>ajmaljhl@gmail.com</email>
	<code></code>
	<orcid>0000-0003-2034-5084</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Center for Healthcare Data Modeling, Departments of Biostatistics and Epidemiology, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Farzan</first_name>
	<middle_name></middle_name>
	<last_name>Madidadizadeh</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>statlearningeasy@gmail.com</email>
	<code></code>
	<orcid>0000-0002-5757-182X</orcid>
	<coreauthor>Yes
</coreauthor>
	<affiliation>Center for Healthcare Data Modeling, Departments of Biostatistics and Epidemiology, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


	<author>
	<first_name>Anam</first_name>
	<middle_name></middle_name>
	<last_name>Arshed</last_name>
	<suffix></suffix>
	<first_name_fa></first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa></last_name_fa>
	<suffix_fa></suffix_fa>
	<email>anamarshed574@gmail.com</email>
	<code></code>
	<orcid>0000-0009-4907-8814</orcid>
	<coreauthor>No</coreauthor>
	<affiliation>Rahbar Medical and Dental College, Lahore Pakistan</affiliation>
	<affiliation_fa></affiliation_fa>
	 </author>


</author_list>


	</article>
</articleset>
</journal>
