{"id":3152,"date":"2021-08-25T13:39:20","date_gmt":"2021-08-25T13:39:20","guid":{"rendered":"https:\/\/researchwithfawad.com\/?page_id=3152"},"modified":"2021-09-11T05:33:38","modified_gmt":"2021-09-11T05:33:38","slug":"moderation-analysis-with-categorical-variables-using-smart-pls","status":"publish","type":"page","link":"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/moderation-analysis-with-categorical-variables-using-smart-pls\/","title":{"rendered":"Moderation Analysis with Categorical Variables using SMART-PLS"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"3152\" class=\"elementor elementor-3152\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-ydgfewf elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"ydgfewf\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t\t<div class=\"elementor-background-overlay\"><\/div>\n\t\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-80293b9\" data-id=\"80293b9\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-de8583b elementor-widget elementor-widget-heading\" data-id=\"de8583b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">Moderation Analysis with Categorical Variables using SMART-PLS<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-7a97694 elementor-section-content-middle elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"7a97694\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-2ce98a0\" data-id=\"2ce98a0\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a3ef3f2 elementor-widget elementor-widget-heading\" data-id=\"a3ef3f2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Moderation Hypothesis\n<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-66 elementor-top-column elementor-element elementor-element-5b17bf9\" data-id=\"5b17bf9\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-298e6ad elementor-widget elementor-widget-text-editor\" data-id=\"298e6ad\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>A moderating variable is the one that modifies the existing relationship between the independent and dependent variable I-e it holds a strong contingent effect on the association of IV and DV. Although, MV is not influenced by IV but affects the strength and direction of the relationship between IV and DV.<\/li><li>A categorical moderator is a moderating variable that is divided into categories. for example Gender, Job Rank, Type of Bank. <\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-p992cns elementor-section-content-middle elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"p992cns\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-85b149e\" data-id=\"85b149e\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-f1cecd6 elementor-widget elementor-widget-heading\" data-id=\"f1cecd6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Categorical Moderation Hypothesis\n<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-66 elementor-top-column elementor-element elementor-element-39c4fce\" data-id=\"39c4fce\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-dba6bdb elementor-widget elementor-widget-text-editor\" data-id=\"dba6bdb\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In this example i test the following hypothesis with the categorical variable Type of Bank moderating the two relationships. The proposed hypotheses are<br><\/p><p>H1: Type of Bank Moderates the Relationship between Organizational Commitment and Organizational Culture<\/p>\n<p>H2: Type of Bank Moderates the Relationship between Perceived Organizational Support and Organizational Culture<\/p>\n<p><img decoding=\"async\" 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\" alt=\"\"><\/p>\n<p><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-7864f69 elementor-section-content-middle elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"7864f69\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-7a82843\" data-id=\"7a82843\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-b168a16 elementor-widget elementor-widget-heading\" data-id=\"b168a16\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Types of Interaction Effects<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-66 elementor-top-column elementor-element elementor-element-93c8952\" data-id=\"93c8952\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-10c1c3e elementor-widget elementor-widget-text-editor\" data-id=\"10c1c3e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><b>Following option are available when running moderation analysis (Bootstrapping)<br \/><\/b><\/p><p><b>Product Indicator Approach<\/b><\/p><p>When the IV or the Moderator is measured reflectively, use Product Indicator Approach<\/p><p><b>Two Stage Approach<\/b><\/p><p>When the IV or the Moderator is measured formatively, use Two Stage Approach<\/p><p><b>Product Term Generation<\/b><\/p><p>Use Unstandardized if the moderator is Categorical<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-ec57307 elementor-section-content-middle elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"ec57307\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-ffc253b\" data-id=\"ffc253b\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-d8bb30f elementor-widget elementor-widget-heading\" data-id=\"d8bb30f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">R-Square<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-66 elementor-top-column elementor-element elementor-element-86d7766\" data-id=\"86d7766\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a233b82 elementor-widget elementor-widget-text-editor\" data-id=\"a233b82\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>In Moderation R-Square Change is important. One shall run the model before the interaction effect is added and after the interaction effect is added to assess the R-Square.<\/li><li>F-Square Effect Size<\/li><li>Effect Size (f-Square) = Included (.570) \u2013 Excluded (.542)<\/li><li>.02 &#8211; Small<\/li><li>.15 &#8211; Medium<\/li><li>035 &#8211; Large<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-f0b4534 elementor-section-content-middle elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f0b4534\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-1f777b4\" data-id=\"1f777b4\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-0a90ee4 elementor-widget elementor-widget-heading\" data-id=\"0a90ee4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Interpretation<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-66 elementor-top-column elementor-element elementor-element-32e722f\" data-id=\"32e722f\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-cb9ce27 elementor-widget elementor-widget-text-editor\" data-id=\"cb9ce27\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>In order to clearly identify how the interaction differs in terms of the groups, including the size and precise nature of the effect, we shall draw an interaction plot.<\/li><li>Review the Steepness of the Line.<\/li><li>The group where steepness is higher, the impact if stronger.<\/li><li>Download Link (Shared in Description)<\/li><li>http:\/\/www.jeremydawson.co.uk\/2-way_with_binary_moderator.xls<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-58a0e46 elementor-section-content-middle elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"58a0e46\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-7094056\" data-id=\"7094056\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-ff09b02 elementor-widget elementor-widget-heading\" data-id=\"ff09b02\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Sample Interpretation - H1<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-66 elementor-top-column elementor-element elementor-element-db9eaef\" data-id=\"db9eaef\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-05a84d3 elementor-widget elementor-widget-text-editor\" data-id=\"05a84d3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><b>Here is the interpretation of H1. For Detail on how to run Moderation, please watch the video at the end of the tutorial<\/b><br><\/p>\n<p>The results revealed a significant moderating role of Type of Bank on the relationship between OC and Collaborative Culture. The plot shows a steeper and positive gradient for private sector banks as compared to public sector banks. Thus, this shows that the impact of OC in fostering collaborative culture is stronger in private banks as compared to public sector banks.<\/p>\n<p><img decoding=\"async\" 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\" alt=\"\"><\/p>\n<p><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-8085d97 elementor-section-content-middle elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"8085d97\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-3fa1819\" data-id=\"3fa1819\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-88af57a elementor-widget elementor-widget-heading\" data-id=\"88af57a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Sample Interpretation - H2<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-66 elementor-top-column elementor-element elementor-element-7ac6152\" data-id=\"7ac6152\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c8f7de0 elementor-widget elementor-widget-text-editor\" data-id=\"c8f7de0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><b>Here is the interpretation of H2. For Detail on how to run Moderation, please watch the video at the end of the tutorial<\/b><\/p><p>The results revealed a significant moderating role of Type of Bank on the relationship between POS and Collaborative Culture. The plot shows a steeper and positive gradient for public sector banks as compared to private sector banks. Thus, this shows that the impact of POS in fostering collaborative culture is stronger in public sector banks as compared to private sector banks.<\/p>\n<p><img decoding=\"async\" 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\" alt=\"\"><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-001516e elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"001516e\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-005ec9c\" data-id=\"005ec9c\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-8702a2d elementor-widget elementor-widget-heading\" data-id=\"8702a2d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">For a Step by Step Guide on How to Perform Moderation with Categorical Variables, Watch the Video<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-6fsrpmc elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6fsrpmc\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-da37464\" data-id=\"da37464\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-80b50c7 elementor-widget elementor-widget-video\" data-id=\"80b50c7\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/youtu.be\\\/d3BgtJ7hNlc&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-f3f4450 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f3f4450\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-5ebe63c\" data-id=\"5ebe63c\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-ebaa69a elementor-widget elementor-widget-text-editor\" data-id=\"ebaa69a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><strong>Reference:<\/strong><\/p><p>Ramayah, T., Cheah, J., Chuah, F., Ting, H., &amp; Memon, M. A. (2018). Partial least squares structural equation modeling (PLS-SEM) using smartPLS 3.0.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-13421ed0 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"13421ed0\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-1f7aafe5\" data-id=\"1f7aafe5\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-8864ed3 elementor-widget elementor-widget-wp-widget-ccchildpages_widget\" data-id=\"8864ed3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"wp-widget-ccchildpages_widget.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h5>Other SmartPLS Tutorials<\/h5><ul><li class=\"page_item page-item-2953 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/how-to-start-data-analysis-using-smart-pls\/\" class=\"menu-link\">How to Start Data Analysis using SMART-PLS<\/a><\/li>\n<li class=\"page_item page-item-3025 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/understanding-convergent-and-discriminant-validity-using-smart-pls\/\" class=\"menu-link\">Understanding Convergent and Discriminant Validity using SMART-PLS<\/a><\/li>\n<li class=\"page_item page-item-3068 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/reporting-measurement-and-structural-model-in-smart-pls\/\" class=\"menu-link\">Reporting Measurement and Structural Model in SMART-PLS<\/a><\/li>\n<li class=\"page_item page-item-3102 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/understanding-r-square-f-square-and-q-square-using-smart-pls\/\" class=\"menu-link\">Understanding R Square, F Square, and Q Square using SMART-PLS<\/a><\/li>\n<li class=\"page_item page-item-3128 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/moderation-analysis-interpretation-and-reporting-using-smart-pls\/\" class=\"menu-link\">Moderation Analysis, Interpretation, and Reporting using SMART-PLS<\/a><\/li>\n<li class=\"page_item page-item-3205 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/mediation-analysis-interpretation-and-reporting-using-smart-pls\/\" class=\"menu-link\">Mediation Analysis, Interpretation, and Reporting using SMART-PLS<\/a><\/li>\n<li class=\"page_item page-item-3267 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/categorical-predictor-variable-using-smart-pls\/\" class=\"menu-link\">Categorical Predictor Variable using SMART-PLS<\/a><\/li>\n<li class=\"page_item page-item-3309 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/concept-of-higher-order-constructs-in-pls-sem\/\" class=\"menu-link\">Concept of Higher-Order Constructs in PLS-SEM<\/a><\/li>\n<li class=\"page_item page-item-3356 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/reflective-vs-formative-indicators-the-concept-and-differences\/\" class=\"menu-link\">Reflective Vs Formative Indicators: The Concept and Differences<\/a><\/li>\n<li class=\"page_item page-item-3397 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/validating-formative-indicators-using-smart-pls\/\" class=\"menu-link\">Validating Formative Indicators using SMART-PLS<\/a><\/li>\n<li class=\"page_item page-item-3423 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/reflective-formative-higher-order-construct-using-smart-pls\/\" class=\"menu-link\">Reflective-Formative Higher-Order Construct using SMART-PLS<\/a><\/li>\n<li class=\"page_item page-item-3458 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/reflective-reflective-higher-order-construct-using-smart-pls\/\" class=\"menu-link\">Reflective-Reflective Higher-Order Construct using SMART-PLS<\/a><\/li>\n<li class=\"page_item page-item-3515 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/how-to-structure-format-and-report-smart-pls-sem-results\/\" class=\"menu-link\">How to Structure, Format, and Report SMART PLS-SEM Results<\/a><\/li>\n<li class=\"page_item page-item-5116 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/how-to-solve-issues-in-convergent-and-discriminant-validity\/\" class=\"menu-link\">How to Solve Convergent and Discriminant Validity Issues<\/a><\/li>\n<li class=\"page_item page-item-5446 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/complex-higher-order-model-using-smartpls\/\" class=\"menu-link\">Complex Higher-Order Model using SmartPLS<\/a><\/li>\n<li class=\"page_item page-item-6872 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/basic-and-advance-data-analysis-using-smart-pls\/analyzing-formative-formative-higher-order-construct-in-smartpls\/\" class=\"menu-link\">Analyzing Formative-Formative Higher-Order Construct in SmartPLS<\/a><\/li>\n<\/ul>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Moderation Analysis with Categorical Variables using SMART-PLS Moderation Hypothesis A moderating variable is the one that modifies the existing relationship between the independent and dependent variable I-e it holds a strong contingent effect on the association of IV and DV. Although, MV is not influenced by IV but affects the strength and direction of the [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":2939,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"site-sidebar-layout":"no-sidebar","site-content-layout":"page-builder","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"disabled","ast-breadcrumbs-content":"","ast-featured-img":"disabled","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"enabled","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center 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