{"id":9299,"date":"2022-08-30T00:26:26","date_gmt":"2022-08-30T00:26:26","guid":{"rendered":"https:\/\/researchwithfawad.com\/?page_id=9299"},"modified":"2023-12-25T01:39:27","modified_gmt":"2023-12-25T01:39:27","slug":"a-basic-and-simple-model-in-smartpls4","status":"publish","type":"page","link":"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/a-basic-and-simple-model-in-smartpls4\/","title":{"rendered":"A Basic and Simple Model in SmartPLS4"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"9299\" class=\"elementor elementor-9299\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-zdcnbl2 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"zdcnbl2\" 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-d4acc06\" data-id=\"d4acc06\" 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-bee4950 elementor-widget elementor-widget-heading\" data-id=\"bee4950\" 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\">A Simple Model in SmartPLS4<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0f1e7d4 elementor-widget elementor-widget-text-editor\" data-id=\"0f1e7d4\" 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><span style=\"color: #ffffff;\">Learn to Import Data, Design, and Interpret a Simple Model in SmartPLS4.<\/span><\/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-85jp2mz elementor-section-content-middle elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"85jp2mz\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;gradient&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-66 elementor-top-column elementor-element elementor-element-2b10226\" data-id=\"2b10226\" 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-fc6092a elementor-widget elementor-widget-image\" data-id=\"fc6092a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"1280\" height=\"720\" src=\"https:\/\/researchwithfawad.com\/wp-content\/uploads\/2022\/08\/Import-Data-and-Design-a-Basic-Model.png\" class=\"attachment-full size-full wp-image-9302\" alt=\"\" srcset=\"https:\/\/researchwithfawad.com\/wp-content\/uploads\/2022\/08\/Import-Data-and-Design-a-Basic-Model.png 1280w, https:\/\/researchwithfawad.com\/wp-content\/uploads\/2022\/08\/Import-Data-and-Design-a-Basic-Model-300x169.png 300w, https:\/\/researchwithfawad.com\/wp-content\/uploads\/2022\/08\/Import-Data-and-Design-a-Basic-Model-1024x576.png 1024w, https:\/\/researchwithfawad.com\/wp-content\/uploads\/2022\/08\/Import-Data-and-Design-a-Basic-Model-768x432.png 768w\" sizes=\"(max-width: 1280px) 100vw, 1280px\" \/>\t\t\t\t\t\t\t\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<div class=\"elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-1e8e919\" data-id=\"1e8e919\" 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-755d715 elementor-widget elementor-widget-heading\" data-id=\"755d715\" 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\">A Simple SmartPLS Model<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-da54622 elementor-widget-divider--separator-type-pattern elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"da54622\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\" style=\"--divider-pattern-url: url(&quot;data:image\/svg+xml,%3Csvg xmlns=&#039;http:\/\/www.w3.org\/2000\/svg&#039; preserveAspectRatio=&#039;none&#039; overflow=&#039;visible&#039; height=&#039;100%&#039; viewBox=&#039;0 0 24 24&#039; fill=&#039;black&#039; stroke=&#039;none&#039;%3E%3Cpolygon points=&#039;9.4,2 24,2 14.6,21.6 0,21.6&#039;\/%3E%3C\/svg%3E&quot;);\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cf39eb3 elementor-widget elementor-widget-text-editor\" data-id=\"cf39eb3\" 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>For Complete Step by Step SmartPLS4 Tutorial Playlist, Click <a href=\"https:\/\/youtube.com\/playlist?list=PLb7vm6tsQ3Kv4YWhYNkP7DizqOjT7ubSX\">Here<\/a><\/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-i4g5bh7 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"i4g5bh7\" 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-100 elementor-top-column elementor-element elementor-element-61ca281\" data-id=\"61ca281\" 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-338057a elementor-widget elementor-widget-text-editor\" data-id=\"338057a\" 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>The session covers the basic starting points in SmartPLS4. The focus of the session is learning<\/p><ul><li>How to Import Data<\/li><li>Design a Basic SmartPLS4 Model<\/li><li>How to Interpret the Results in SmartPLS4.<\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e3c2a98 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"e3c2a98\" 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<h3>Creating a Basic Model in SmartPLS 4<\/h3><p>In this video tutorial (Link at the end of this page), we will delve into the process of developing a simple model using SmartPLS 4. In our <a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/steps-in-data-analsis\/\">previous session<\/a>, we underscored the significance of a meticulous approach to data analysis and results. Having discussed the essential steps involved in data cleaning, we now pivot towards constructing a fundamental model.<\/p><h3>Setting Up Your Workspace<\/h3><p>Upon launching SmartPLS 4, which stands as a cutting-edge development in statistical software, the initial step involves creating a workspace. A workspace, essentially a designated folder on your computer, serves as the repository for all your projects. For your Workspace choose an empty folder that will have all your SmartPLS4 project.<\/p><p>Next, Select New Project from the Toolbar<\/p><p><img decoding=\"async\" class=\"aligncenter\" 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\" alt=\"\" \/><\/p><p>Next, give your project a name<br \/><img decoding=\"async\" class=\"aligncenter\" src=\"data:image\/png;base64,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\" alt=\"\" \/><\/p><p>Next, you have a project created in the workspace window.<\/p><p><img decoding=\"async\" class=\"aligncenter\" src=\"data:image\/png;base64,iVBORw0KGgoAAAANSUhEUgAAAkUAAAB7CAYAAAB6kfQ1AAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAEnQAABJ0Ad5mH3gAAABhaVRYdFNuaXBNZXRhZGF0YQAAAAAAeyJjbGlwUG9pbnRzIjpbeyJ4IjowLCJ5IjowfSx7IngiOjU4MSwieSI6MH0seyJ4Ijo1ODEsInkiOjEyNH0seyJ4IjowLCJ5IjoxMjR9XX1\/\/v26AAAXVUlEQVR4Xu3dCYwU1aLG8TPsCqIgi6IsAoLIIpvgRTSiRMGLLyo+3HF56nU3N0ajxhdf8oxR1HfjFrzmRbk+9xWfiiiKqMgVZBEG8pRFQJAdBmFGZ4bt9XeoM9TUVE9X9dTA9PT\/l5x0V\/Xp6qqeDvVxzqlTBffff\/8+AwAAkOcaeI8AAAB5rWD58uW0FAEAgLxXMHnyZEIRAADIewXTpk0jFAEAgLxSUlJievXqZZo1a2bKyspMeXk5Y4oAAACEUAQAAJBCKAIAAEghFAEAAKQQigAAAFIIRQAAACmEIgAAgBRCEQAAQAqhCAAAIIUZrQEAyHMFBQVm586ddpbn3bt3e2vrtkaNGpnmzZubI444wuzbFz\/KhM1oTSgCACCPKRCtW7fOHHPMMbYobOQChbcNGzbY0qFDh9jBiFAEAAAqKS4uNocffrjp16+fKS0tzarV5VBQmFOgWbRokfn9999NixYtvFeiIRQBAIBKNm7caPr27WtatmxpA1IuURDasWOHKSwsNO3bt\/fWRsMNYQEAQCXqhmrYsKHZs2ePtyZ3aJ+170mNgyIUAQCQ59RllsslKYQiAADyXFjQyKWSFMYUAQCQx3799VczcOBA07RpU\/PHH394a6NZtmyZWb58ubd0QPfu3c2JJ57oLdWeww47zI4Hmj9\/vjnuuOO8tdEw0BoAAFSiUDRgwIDYoWjOnDnmhRde8Jaquummm8yQIUO8pdrhQtGCBQsSCUWxus9++uknc99995n169d7ayp77bXX7Ou6NC6MXn\/xxRe9pWStWrXKfrYeAQBAdNl0Q73yyives3CZXk9C0t1nsUJRx44d7ePSpUvtY5Ca0WTNmjX2MUhzCXTr1s1bAgAAdYELFi5kRCnpGkAcvf7JJ5+kLcoMYduNU8Q9JiFWKNLkTscff7xZsWKFt+YAtR65Zrew1hq3rnPnzvYRAADUDcGwEaVE8e6776Ytjz32mO2CC9t23JKU2FefaYIntRQFE+Ivv\/xiH0877bSKFiM\/db2p769Lly7eGgAAUFckGS6ievXVV71n2Ul6nxuOHz\/+P7znkWgg1uzZs03Xrl1NmzZtvLXGfP311+bII480J598spk1a5Ydya4Q5EydOtW2MilU+X311Vfm7bffNh9++KH5\/PPPzaZNm+xgKf97RS1Njz76qO3Cmzlzppk0aZL59ttvTc+ePe3N4LZv327mzp1rBg8ebI466ijvXcZMnjzZvPnmmxX1RAHtjTfeMO+99579zB9\/\/NEel+754gQ\/T9vQMahuu3btKn2Go9YyHYf+yNquBn5pQinVb9y4sVdrP\/9x6zi0\/6oXPG6JUxcAgDh0I1idU+JOgvjRRx95z7K3a9cuM2bMGG8pPt2nTfus7KAZuePQZ7dt29ZuQ5NAqsRuKTr22GPtyTjYRabWIY0XcuOO\/OOK1Kq0du3aKuOJFFjUr6jL9q677jpz0UUX2VHwzzzzjNm2bZtXqzKFGW1P9S+88EK7P+l8+umn5rvvvqtUT4HopZdeMq1btzaXX3653Y7C2uuvv27DR5A+T\/uubai+PP\/883Y7fgpEGoWv\/dZx3HzzzfY+Mjo+HaefO269rnqjRo2y35+OOziIPazuwoULbd1M\/bkAAETh74qKWpIStu24JSmxQ5EoxPi7yNx4Io0XUtg4+uijzcqVK71XDwzA9s9ZoFClwKIAocChlpyhQ4ea2267zY5dUstTGG3jiiuusPVPOeUUb21VCg5ffvml3b6\/nlpaFIK0Da3XdvT5I0aMMDNmzPBqHaB9uf76621dldtvv90e37Rp07wa+6n7UN+B6uo41E143nnnmdGjR9sB5i7s+I9br6ue\/7i1z066urrMUZ\/1\/fffezUBAMheWNDIVMKot0jnsyeeeMJMnDgxUgnbdtySlKxCUe\/evW3riWvNceOJ3HghtWr4Q5MCkoKEApOzevVq+6iTvJ+7U6\/CQJhhw4Z5z9JTIFLLj8JPcPuajyDMqaeeaq655hpv6QDNsaB98jvzzDPt8ftbavQ56m4L1nUDyzUHglR33Oeee26l96erq1YvfUdhA94BAIgrLGhkKkHqTVHDgbLAvHnzzGeffRa7qEEk7LMylaRkFYqCXWQ6Offo0cM+F30hW7durQhNCkjBmS3VTabQEiZdcIlC3VouEPmDm6MWIe3b448\/bsdGudcV2Fyo8wsbO+TuxKs+zLiKiorSHrdaotRq5VT3HWncVbqpDwAAiKsm4UJDO8444ww7tvehhx6y5+H3338\/dtF43DiSDESSVSgKdpEp9PjHC7nQpPXqNlII0ayRfqWlpVVaVZKg7iddAaduLI19Kiws9F7ZT60sd9xxhw1pGjg9YcIE8+yzz9rWpTAaPB6VxiQpbGkSSVc0\/shPISzqces7UrDzb88VjTOKM\/MoAADp+FtdohZn0KBB5oILLrCBSBM0ZzveVefGG2+8MfSzMpWkZBWKRN03ChL+8USODkwtHGpBcl1rLig5ag2qjYHCCkRqbdE+nHXWWXacUPBzFOpUR2n2rrvusvuqVKuB2UG\/\/fab96x6eq9\/0LgGRatoPJCfPjvqcas1SPvmthVWAACoqbCgkalIp06dzLhx4+x\/4HVhUk1ceumlpkOHDqGflakkJetQpK4mhSF1QalFJtj1pHCgliIFI53Yg60jOuHrSwyjFpJsLzfv37+\/92z\/nEraR\/\/4JgU5\/5VzajlyA639g5wdXf4e5Mb6+C\/\/cy1U2pYGb+v7UHFdbU6rVq3SHrf2S9+no+Coum5bYQUAgJoKCxqZis7rt956q\/2P\/lNPPVWjho7LLrvMTuUT9jlRSlKyDkU68YsGRAfHC4lO2AokuvIqODeRuJYlfwgQfanapv+KsWypVUZBRYO3HA3+mj59ureUmWbb9P+h9VzrggPHJSzIbdy40Xu2X3XHrbmI\/IOn3Tit4OX\/oibK4DYAAMhGNuFCV0KLprmpSSDSWKTTTz\/dW4on6VAUe\/JGP3WNabyQrggLDghWgnTz\/owcObLKgGUtFxcX20FVbtIkBYJ33nnHTqik5jh\/yEg3OaOT7nW1tnzzzTd2giZNzqj9+uKLL+y+N2jQwHaPaXJGFbUWde\/e3b7PbU8USjS5owLOBx98YB+Vav2TV2p7Clw6Dk0EpdYkhTtNAaCJpdx+BY9bdbV9Hbd+VJdccknFJJN6VF1NkOW+Iw2+njJlip1VXN2DYd8FAABRafJG\/SffTYQYlXo+NFmxJjXOlrrfNI4oW26fNV43ickbaxSKdJt9fRmaQ8edyB3N4KygoBO9\/4oqv5NOOsnWmz9\/vp0FW9tSC5ECUbAVJttQpOfa7pYtW8yAAQNskNH4ps2bN9tw9MMPP9gWLQWMc845x3vXge1dffXV9jgV8DRDtb70sWPHVrSUOVrWZfcKRgpDCngKYQpa+gz\/fvmPW4FNAUotawpEwckog9\/R4sWLbdejQllwnBYAAHEpFKn3I+6M1iUlJfbOEAoXcelcrAaTK6+80luTHe2zwkxSoahg2rRpybU71SMa36MrxzSYmbE7AID6Sj0Q6iVp0qSJbQTIJW6fly9fbhsM4lCo05Xx6lFSo4a2k\/WYIgAAUD+4sTm5WpJCKAIAIM+FBY1cKkkhFAEAkOfCgkYulaQQitLQOCLdy4zxRACAfBAWNnKhJIlQBABAHot7KX5do33XMSSBq88AAMhjmpZGl6PrFhsKGEm3vtSWgoICG4bWrVtnL82PeyeMsKvPCEUAAOQxzdWju0+0aNHCzvWjiY1zwd69e82OHTvsJMe6H6vmH4yDUAQAACpRENIEzJrrRyEjV7rS1EqkfdccS5qAUvseB6EIAABUoVt2qMUoV1qJHLUWqYWoqKjIWxMdoQgAAITSGB3d5zOXus8UZrIdA0UoAgAASAkLRVySDwAAkEIoAgAASCEUAQAApBCKAAAAUghFAAAAKYQiAACAFEIRAABASsHkyZOZpwgAAOSdKpM3FhYWEooAAEBO0KSLmn1bRbNvu+fBohmvNdt1WNGd9YXJGwEAAEIQigAAAFIIRQAAoF5Qt9miRYvMwoUL7fO4CEUAACDnaXxRYWFhpRL3jv+EIgAAkNMUftRCpDJmzBhzwQUXVCzHCUZ18uqzBRsamh82VT2I\/u32mgHH7PGWAABAvglefdawYUOzePFiG4DOP\/9807lzZ\/vaqlWrzJQpU0zfvn1t2bNnT8arz+pcKJq6opG598um3lJVE0aUmVHddntLAAAgn\/hDkQLRkiVLbCAaPXq06dSpkw0\/LjCtXr3aTJ061fTr18\/07t274jL9nAlFw\/\/ncLOjLP3gqJZN95mZV\/\/uLQEAgHziD0WNGjUyjRs3tkXLCkT+UKTQpBC0a9cuW1xrUc6Eon7\/3dx7lt5fh5R7z6pKsovtySefNMOHDzdDhw711lT18ssvm+nTp3tL+91yyy3Vvieqa6+91px99tlm\/Pjx3hoAAPJbMBSpuHFDriVIr4l\/\/e7du5MPRU8\/\/bSZP3++txRu4MCB5s477\/SW4okSijKpaReb+iDfeust+zxTwFEoEhdcli5dah555JHEglESZs+ebd59910zYcIEbw0AALkp2H2m4ONCkLjXFIQcBSEtZ+o+i3312VVXXWU3kI5eU51D6eFZTbxn8SlAKBBNmjTJtGvXzlsbXY8ePcy4cePMzJkzvTUAAKA2BMNOUKbXg2KHotatW5uLL77YW6pKr6nOoVTdmKRM1LqjQJQkdcOp9enee++1XWJqTRKt07IrWvZz73PUKuWvHxTcngKetjFx4kSzadMmu07LAACgqtihSEaOHGm6dOniLR2gdXot323ZssW0bdvWW9pPrU833HCDDVxqTVLAmTFjhl12RXWCwchR\/c2bN1fUVWuUQpaj97kWLpXHH3\/crr\/77rttV55avbReywAAoKqsQpH679Tq4AYwSdi6pAw7fo957rxS8\/XVv5tFN5REKoeKWmc08FqXBvppwLTCkCjcqM4999xjlx2FFwWlIFffH2g0F4Naf1yrkwLRAw88YJ+LQlldGdMEAEBt0QDq7du3m40bN5oNGzbYsn79evuodXpNdaLIOsEEW4XStR7V1L8PLzPPjyo1fdvtNdNWNjQvLWocu7z9YyNva7VDgcV1WamrSi0ywZaiNm3aeM+MKSoqsi03wTpdu3a1QSdI9cV9hiuOgpG250IXAAD5oLi42CxbtsyGHw2UVtGgaTdwWkWvqY7qZlKjZh03fijTOKNs3dB\/l\/nXk3bbCR3HvHWY+c+ZTc3f5jSJXSalglFtUiuQ67ZSqQ2u+ytYCEIAgHyky+vXrFljOnbsaEaMGGF7R8KKXlMd1dV7qlOjUOSuNMt0RVo2RnXdbe4cXF4xw3W2g6c12eN\/jSzzluqGVq1a2RYhdYv5\/fzzz6FXvKWr72R6HQCA+kYtP5qjqGfPnmbnzp22u0yX2q9du9bOZL1y5UqzYsUK21KkOqqbqbWoxgOANCeRSpJ6t9lrHji93Py0rUGNLq+XB4eVm56tD8xVUBeo20ytS24wtKOut7Fjx3pLB6i+7tsSrO\/mSArbngKSxjeJC00AANQX6hpr3ry5nZOotLTUW1uVApPqqK7eU53kR0XXkFp2Jo4uNcWp\/f63j5vV6PJ6jUeqq\/dJ02SPffr0qTRGqLoJHzXIun379pXqK\/k6we1pELfGKIm62NQCpfVckg8AQLg6d5sP3SH\/hFZ7zS2fNDNLtmSf2cb12mUePL36RFjX6ZJ7tRylC0oAAOQbN6O1pr\/RGKEhQ4bY3hE3SaOK1vuXu3fvbubMmWO70HThU2IzWtc23bfskW+b1CgQqfst1wORrihTlxeBCACAg6POhaLtZQVm1q8NvaV4Orbca28W+\/qFf3hrco+blVr3T\/PPOwQAAGpXnes+AwAASCevus8AAAAOBUIRAABACqEIAAAghVAEAACQQigCAABIIRQBAACkEIoAAEDO2rcv88xCUeoIoQgAACCFUAQAAJBCKAIAAEghFAEAAKQQigAAAFIIRQAAACmEIgAAgBRCEQAAQEqdCUUPf7LSlvrmUByXPq\/fw9\/ZInr078PNr\/9oXvrnOm\/p4FmwZmfFfrmiddgvzm\/lUP0NAaA+o6UooqlLtpo\/P\/eDt1Q7kvgMhYy35m00ix48zRbR44OjT7DPDxWdxK\/5x5KK\/VKZctsA8\/HiLV6N5B2MvxkA4NBiRmuktXFHuenYqpm3VDeoRWPNttKKkOYc36rpIQ9rAAA4BYWFhdHiUy1z3QbuJKmWhaFdWprZq3aYWSu223VqWdhcXG5bHEQn\/49v62+fi3vPr9vLbGuJDOt2lHn+8pPsc0cn6b998Yu3ZMxfz+lkrvtTB2\/pwHbemb\/JrCkqNX07tDCF64q9V8O36eg4\/J99\/FFN7XN3XGuLysz5zy2wz2XcoPb2NX2mO05xn5Gufhj\/Z4t\/2zoed4zB5eD7guGlptRN9o9repsBHY\/w1lQV\/M799dPtX3XfTbrvU+Icr9uvOL9DyfQbk0y\/FUm3r8G\/IQDki5KSElNQUGC2bNli9uzZYwYPHmy2bt1q9u7dW1G03r\/ctWtXM3fuXNOoUSPTpk0bs27d\/uEHvXr1Ms2aNTNlZWWmvLy8brcU6aTyl+HH2ROBTng6Af595q922Z0cguMq9J7BnVpW1FELhU4sjp7rxOteV9F7wrbz8L90s6+\/en0fM+GiE+3JT8vVBaJ\/\/vxbxXYv7Ne20glNJn23zp5UXR29rm4ebTPsM9LVD6OTqX8b6cKTn\/Z5bSpEuu3r5J1kl5MbM1RdIHL837k\/EKXbv+q+m3TfZzbHG\/d3GOU3FuW3Utt\/GwBAZXU6FOkE5E6Of+7Txj7q5OT8qeuRtlXIT+8Z1ftobyl1YkmdZN3JRi0Lev73K3rZZUcnT53E\/PyfHUXYtrUfagHwU1BRt5Gjz1m\/o\/Ix+MWtH4fbZ3\/IU8uDWmqSHACtYBJF8DvPtH9xv5tsj9e\/X5l+h1F+Y1F+KwfrbwMAOKBOh6LjvO4EaduiSaVH0ev6n7Sf\/z3i6uskoy4PnaD9J1Lp06GFPdn4BbeTSbptuy4RP7UAuKuvdOILBruguPWj0j6L27YrSQt+t+kEv\/Mo+xfnu8n2eOP8DqP8xqL8Vg7W3wYAcEDeDLQOnoAOFXdic10iaoWoTtz6cenk7LbtL3FayarjD6XZqG7\/svluavt4k5RL+woA9UG9C0XBloLF64rtyUV0gtb\/1oMnaH+dbKXbtsaNOOr20Of4x\/oEW7r84taPK90+J0lhVN1CD0+NP1dTdfuXzXdzMI43ym8sym\/lYOwrAKCyeheK1IXiH3Nx7\/vLzB1ndbTPdYJWa8JfXvs\/u+z466TTvuX+k1Q6YSd\/DawNvsd\/otOgYP8VUmGfUV39mnL7HPw+1CWVJI2L0X7riik\/HVd1n5Vp\/zJ9N8Hv82Acb5TfWJTfysH62wBALos6\/5BEqVvvQpGu0Hnwf1dUjMHQsn\/gtVoWNDDWva6iQbD+OmHUZaH\/6at+8OTu6OSvq93cdsXfpaNtaFlXL+n1ub\/sqPK6\/zMy1U+C9rlj6\/2f6Yqu3kuaun00Zsb\/OTouf0tPmHT7F+W7CfubHYzjjfIby\/RbkYP1twEA7Fdn5ilKAnO3AABQv\/nnKdq9e7edp2jbtm2V5iUKzlN0wgkn2HmKGjduXO08RXUiFL08e733rGZ0yXPn1P+sT00FI9TcVUOONQ0KvIUsJfW3RXpXnnqMaVjTPxQA5IjaDEV1ovusceof9CRK6juyJ\/Gw1yjxSxLCtktJtgAAklGvus8AAED9Vu9bigAAAA41QhEAAEAKoQgAACCFUAQAAJBCKAIAAEghFAEAgJwV5fYdUW8HQigCAABIIRQBAACkEIoAAABSCEUAAAApBSUlJdzmAwAA5ITCwsJKt\/kYNGiQKSoqqnRbj+BtPrp06WLmzZuX4TYf5eb\/AUg8FUKV3IekAAAAAElFTkSuQmCC\" alt=\"\" \/><\/p><p>Next, Click on Impact data file to import the data file in formats such as CSV, SAV, or Excel. SmartPLS 4 conveniently assumes empty values as missing, but users can designate specific markers for missing values if necessary.\u00a0<span style=\"font-size: 1rem;\">Once your data is imported, a comprehensive overview of indicators, including variable types, any missing values, mean values, and other statistical parameters, becomes accessible. It is advisable to scrutinize indicators for potential errors by examining minimum and maximum values. This step ensures the integrity of your dataset.<\/span><\/p><p><img decoding=\"async\" class=\"aligncenter\" 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\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\" alt=\"\" \/><\/p><p><span style=\"font-size: 1rem;\">Proceeding to the model creation phase, select &#8220;Create Model&#8221; and specify the model type; in this case, Partial Least Squares Structural Equation Modeling (PLS-SEM). Naming your model, in this instance, &#8220;My First Model,&#8221; ensures easy project management. The ensuing canvas provides a space to graphically represent variables and relationships.<\/span><\/p><p><img decoding=\"async\" class=\"aligncenter\" style=\"font-size: 1rem;\" 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U3kI5eU51D6eFZTbxn8SlAKBBNmjTJtGvXzlsbXY8ePcy4cePMzJkzvTUAAKA2BMNOUKbXg2KHotatW5uLL77YW6pKr6nOoVTdmKRM1LqjQJQkdcOp9enee++1XWJqTRKt07IrWvZz73PUKuWvHxTcngKetjFx4kSzadMmu07LAACgqtihSEaOHGm6dOniLR2gdXot323ZssW0bdvWW9pPrU833HCDDVxqTVLAmTFjhl12RXWCwchR\/c2bN1fUVWuUQpaj97kWLpXHH3\/crr\/77rttV55avbReywAAoKqsQpH679Tq4AYwSdi6pAw7fo957rxS8\/XVv5tFN5REKoeKWmc08FqXBvppwLTCkCjcqM4999xjlx2FFwWlIFffH2g0F4Naf1yrkwLRAw88YJ+LQlldGdMEAEBt0QDq7du3m40bN5oNGzbYsn79evuodXpNdaLIOsEEW4XStR7V1L8PLzPPjyo1fdvtNdNWNjQvLWocu7z9YyNva7VDgcV1WamrSi0ywZaiNm3aeM+MKSoqsi03wTpdu3a1QSdI9cV9hiuOgpG250IXAAD5oLi42CxbtsyGHw2UVtGgaTdwWkWvqY7qZlKjZh03fijTOKNs3dB\/l\/nXk3bbCR3HvHWY+c+ZTc3f5jSJXSalglFtUiuQ67ZSqQ2u+ytYCEIAgHyky+vXrFljOnbsaEaMGGF7R8KKXlMd1dV7qlOjUOSuNMt0RVo2RnXdbe4cXF4xw3W2g6c12eN\/jSzzluqGVq1a2RYhdYv5\/fzzz6FXvKWr72R6HQCA+kYtP5qjqGfPnmbnzp22u0yX2q9du9bOZL1y5UqzYsUK21KkOqqbqbWoxgOANCeRSpJ6t9lrHji93Py0rUGNLq+XB4eVm56tD8xVUBeo20ytS24wtKOut7Fjx3pLB6i+7tsSrO\/mSArbngKSxjeJC00AANQX6hpr3ry5nZOotLTUW1uVApPqqK7eU53kR0XXkFp2Jo4uNcWp\/f63j5vV6PJ6jUeqq\/dJ02SPffr0qTRGqLoJHzXIun379pXqK\/k6we1pELfGKIm62NQCpfVckg8AQLg6d5sP3SH\/hFZ7zS2fNDNLtmSf2cb12mUePL36RFjX6ZJ7tRylC0oAAOQbN6O1pr\/RGKEhQ4bY3hE3SaOK1vuXu3fvbubMmWO70HThU2IzWtc23bfskW+b1CgQqfst1wORrihTlxeBCACAg6POhaLtZQVm1q8NvaV4Orbca28W+\/qFf3hrco+blVr3T\/PPOwQAAGpXnes+AwAASCevus8AAAAOBUIRAABACqEIAAAghVAEAACQQigCAABIIRQBAACkEIoAAEDO2rcv88xCUeoIoQgAACCFUAQAAJBCKAIAAEghFAEAAKQQigAAAFIIRQAAACmEIgAAgBRCEQAAQEqdCUUPf7LSlvrmUByXPq\/fw9\/ZInr078PNr\/9oXvrnOm\/p4FmwZmfFfrmiddgvzm\/lUP0NAaA+o6UooqlLtpo\/P\/eDt1Q7kvgMhYy35m00ix48zRbR44OjT7DPDxWdxK\/5x5KK\/VKZctsA8\/HiLV6N5B2MvxkA4NBiRmuktXFHuenYqpm3VDeoRWPNttKKkOYc36rpIQ9rAAA4BYWFhdHiUy1z3QbuJKmWhaFdWprZq3aYWSu223VqWdhcXG5bHEQn\/49v62+fi3vPr9vLbGuJDOt2lHn+8pPsc0cn6b998Yu3ZMxfz+lkrvtTB2\/pwHbemb\/JrCkqNX07tDCF64q9V8O36eg4\/J99\/FFN7XN3XGuLysz5zy2wz2XcoPb2NX2mO05xn5Gufhj\/Z4t\/2zoed4zB5eD7guGlptRN9o9repsBHY\/w1lQV\/M799dPtX3XfTbrvU+Icr9uvOL9DyfQbk0y\/FUm3r8G\/IQDki5KSElNQUGC2bNli9uzZYwYPHmy2bt1q9u7dW1G03r\/ctWtXM3fuXNOoUSPTpk0bs27d\/uEHvXr1Ms2aNTNlZWWmvLy8brcU6aTyl+HH2ROBTng6Af595q922Z0cguMq9J7BnVpW1FELhU4sjp7rxOteV9F7wrbz8L90s6+\/en0fM+GiE+3JT8vVBaJ\/\/vxbxXYv7Ne20glNJn23zp5UXR29rm4ebTPsM9LVD6OTqX8b6cKTn\/Z5bSpEuu3r5J1kl5MbM1RdIHL837k\/EKXbv+q+m3TfZzbHG\/d3GOU3FuW3Utt\/GwBAZXU6FOkE5E6Of+7Txj7q5OT8qeuRtlXIT+8Z1ftobyl1YkmdZN3JRi0Lev73K3rZZUcnT53E\/PyfHUXYtrUfagHwU1BRt5Gjz1m\/o\/Ix+MWtH4fbZ3\/IU8uDWmqSHACtYBJF8DvPtH9xv5tsj9e\/X5l+h1F+Y1F+KwfrbwMAOKBOh6LjvO4EaduiSaVH0ev6n7Sf\/z3i6uskoy4PnaD9J1Lp06GFPdn4BbeTSbptuy4RP7UAuKuvdOILBruguPWj0j6L27YrSQt+t+kEv\/Mo+xfnu8n2eOP8DqP8xqL8Vg7W3wYAcEDeDLQOnoAOFXdic10iaoWoTtz6cenk7LbtL3FayarjD6XZqG7\/svluavt4k5RL+woA9UG9C0XBloLF64rtyUV0gtb\/1oMnaH+dbKXbtsaNOOr20Of4x\/oEW7r84taPK90+J0lhVN1CD0+NP1dTdfuXzXdzMI43ym8sym\/lYOwrAKCyeheK1IXiH3Nx7\/vLzB1ndbTPdYJWa8JfXvs\/u+z466TTvuX+k1Q6YSd\/DawNvsd\/otOgYP8VUmGfUV39mnL7HPw+1CWVJI2L0X7riik\/HVd1n5Vp\/zJ9N8Hv82Acb5TfWJTfysH62wBALos6\/5BEqVvvQpGu0Hnwf1dUjMHQsn\/gtVoWNDDWva6iQbD+OmHUZaH\/6at+8OTu6OSvq93cdsXfpaNtaFlXL+n1ub\/sqPK6\/zMy1U+C9rlj6\/2f6Yqu3kuaun00Zsb\/OTouf0tPmHT7F+W7CfubHYzjjfIby\/RbkYP1twEA7Fdn5ilKAnO3AABQv\/nnKdq9e7edp2jbtm2V5iUKzlN0wgkn2HmKGjduXO08RXUiFL08e733rGZ0yXPn1P+sT00FI9TcVUOONQ0KvIUsJfW3RXpXnnqMaVjTPxQA5IjaDEV1ovusceof9CRK6juyJ\/Gw1yjxSxLCtktJtgAAklGvus8AAED9Vu9bigAAAA41QhEAAEAKoQgAACCFUAQAAJBCKAIAAEghFAEAgJwV5fYdUW8HQigCAABIIRQBAACkEIoAAABSCEUAAAApBSUlJdzmAwAA5ITCwsJKt\/kYNGiQKSoqqnRbj+BtPrp06WLmzZuX4TYf5eb\/AUg8FUKV3IekAAAAAElFTkSuQmCC\" \/><\/p><p>Further you will now see an empty canvas, select items for each construct one by one and drop them onto the canvas<\/p><p><img decoding=\"async\" class=\"aligncenter\" 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\" alt=\"\" \/><\/p><h3><span style=\"font-size: 2.46667rem; font-style: inherit;\">Constructing a Measurement Model<\/span><\/h3><p>In the example video tutorial (see video at the end of this page), I begin by drawing a simple measurement model. Latent variables, such as &#8216;cc&#8217; and &#8216;op,&#8217; are added by selecting relevant indicators and dragging them onto the canvas. Ensure the latent variables are connected by drawing lines, representing relationships between the independent and dependent variables.<\/p><h3>Assessing the Measurement Model<\/h3><p>To assess the reliability and validity of the measurement model, navigate to the &#8220;Calculate&#8221; menu and choose the PLS-SEM algorithm. Configure settings such as the weighting scheme and calculation options. The resulting output presents graphical representations of path coefficients, loadings, and R-square values. These metrics are crucial for evaluating the model&#8217;s robustness and explanatory power.<\/p><h3>Interpreting Results<\/h3><p>Factor loadings, beta coefficients, and R-square values are essential components of the model output. Factor loadings indicate how well an item represents the underlying construct, beta values represent the weight of impact and are also referred to as path coefficients. R-square values elucidate the proportion of variance explained by the model.\u00a0<\/p><p>In subsequent tutorials, we will delve deeper into the interpretation of factor loadings, beta coefficients, and other intricacies associated with SmartPLS 4. Thank you for your attention to this introductory tutorial.<\/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-db7340d elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"db7340d\" 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-5a6a379\" data-id=\"5a6a379\" 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-561756f elementor-widget elementor-widget-heading\" data-id=\"561756f\" 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<h2 class=\"elementor-heading-title elementor-size-default\">Video - A Simple Model in SmartPLS4<\/h2>\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-e04f9b2\" data-id=\"e04f9b2\" 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-5557aa8 elementor-widget elementor-widget-video\" data-id=\"5557aa8\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/youtu.be\\\/s19bhLG-bAs&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-8c85e2b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"8c85e2b\" 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-33 elementor-top-column elementor-element elementor-element-53cafbc7\" data-id=\"53cafbc7\" 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-9c476cc elementor-widget elementor-widget-heading\" data-id=\"9c476cc\" 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<h2 class=\"elementor-heading-title elementor-size-default\">Additional Literature Review Resources<\/h2>\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-22dae22a\" data-id=\"22dae22a\" 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-47926623 elementor-widget elementor-widget-wp-widget-ccchildpages_widget\" data-id=\"47926623\" 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<ul><li class=\"page_item page-item-9370 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/convergent-and-discriminant-validity\/\" class=\"menu-link\">Basic SEM Concepts &#8211; Convergent and Discriminant Validity<\/a><\/li>\n<li class=\"page_item page-item-9337 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/structural-equation-modelling-concepts\/\" class=\"menu-link\">Basic Structural Equation Modelling (SEM) Concepts<\/a><\/li>\n<li class=\"page_item page-item-9543 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/categorical-moderation-analysis-using-seminr\/\" class=\"menu-link\">Categorical Moderation Analysis using SEMinR<\/a><\/li>\n<li class=\"page_item page-item-9403 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/how-to-assess-construct-reliability\/\" class=\"menu-link\">How to Assess Construct Reliability?<\/a><\/li>\n<li class=\"page_item page-item-9428 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/how-to-assess-convergent-validity\/\" class=\"menu-link\">How to Assess Convergent Validity (Construct validity)<\/a><\/li>\n<li class=\"page_item page-item-9448 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/how-to-assess-discriminant-validity\/\" class=\"menu-link\">How to Assess Discriminant Validity (Construct validity)<\/a><\/li>\n<li class=\"page_item page-item-9672 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/reflective-reflective-higher-order-construct\/\" class=\"menu-link\">How to Assess Reflective-Reflective Higher Order Construct<\/a><\/li>\n<li class=\"page_item page-item-9490 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/how-to-design-a-measurement-model\/\" class=\"menu-link\">How to Design a Measurement Model?<\/a><\/li>\n<li class=\"page_item page-item-9029 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/how-to-enter-data-in-spss-or-excel\/\" class=\"menu-link\">How to Enter Data in SPSS or Excel<\/a><\/li>\n<li class=\"page_item page-item-9462 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/how-to-solve-discriminant-validity-issues\/\" class=\"menu-link\">How to Solve Discriminant Validity Issues<\/a><\/li>\n<li class=\"page_item page-item-12181 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/how-to-use-necessary-condition-analysis-in-smartpls4\/\" class=\"menu-link\">How to Use Necessary Condition Analysis in SmartPLS4?<\/a><\/li>\n<li class=\"page_item page-item-9634 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/reflecrtive-formarive-model-using-smartpls4\/\" class=\"menu-link\">Reflective-Formative Higher-Order Model using SmartPLS4<\/a><\/li>\n<li class=\"page_item page-item-9800 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/simple-structural-model-in-smartpls4\/\" class=\"menu-link\">Simple Structural Model in SmartPLS4<\/a><\/li>\n<li class=\"page_item page-item-8989 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/smartpls4-tutorials-series-introduction\/\" class=\"menu-link\">SmartPLS4 Tutorials Series Introduction<\/a><\/li>\n<li class=\"page_item page-item-8950 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/steps-in-data-analsis\/\" class=\"menu-link\">Steps in Data Analysis<\/a><\/li>\n<li class=\"page_item page-item-9597 menu-item\"><a href=\"https:\/\/researchwithfawad.com\/index.php\/lp-courses\/smartpls4-tutorial-series\/what-is-a-formative-construct\/\" class=\"menu-link\">What is a Formative Construct?<\/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>A Simple Model in SmartPLS4 Learn to Import Data, Design, and Interpret a Simple Model in SmartPLS4. A Simple SmartPLS Model For Complete Step by Step SmartPLS4 Tutorial Playlist, Click Here The session covers the basic starting points in SmartPLS4. The focus of the session is learning How to Import Data Design a Basic SmartPLS4 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":8833,"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 center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","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":"var(--ast-global-color-5)","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":""}},"footnotes":""},"class_list":["post-9299","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>A Basic and Simple Model in SmartPLS4 - ResearchWithFawad<\/title>\n<meta name=\"description\" content=\"The tutorial focuses on how to import data, Design, and interpret and simple model in SmartPLS4. 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